Data Analysis | Learn Data Analysis | Simplilearn 🔥[2026 Updated] - Business Analytics Full Course 2026 | Business Analytics Tutorial For Beginners | Simplilearn

Hey everyone and welcome to Simtie Learn's Business Analytics Filcourse. In this course we will explore the world of business analysis where data is a key driver for smarter business decisions. As a business analyst you will learn how to analyze data and transform it into actionable insights that fuel businesses growth and even success. So with the demand of business analyst expected to sow in 2005 and beyond, now is the perfect time to launch your career in this exciting field.

Throughout this course we will cover core business analytics concepts including data visualization, data cleaning, report building along with advanced techniques to further sharpen your skills. You will also gain hands and experience through real world projects and receive preparation for job interviews and certifications as well giving your career a major boost. So let's get started. Before we comment if you are interested in becoming a business analyst, Simtie Learn offers the perfect certification program to help you achieve your goals.

With this course you learn how to solve complex business problems and gain essential skills all aligned with IIA, BA, Babog, B3 standards including C-BAP and CCB certifications. We will also learn valuable certifications from IB, but in master classes with IB Mixport and gets hands and experience with real world project and how it business case studies. So hurry up and enroll now and find the course, description box below and in the pen comments. It is no surprise that business analytics and business intelligence are two of the fastest growing markets in the world.

Organizations today are generating data at a rapid rate. There is a need to use this business data and make smarter decisions. Businesses are looking for methods and tools to turn business data into actionable insights. This is where business analytics and intelligence can help play a critical role.

Business analytics is the process of collecting, analyzing and drawing valuable conclusions from vast volumes of data available. It helps to improve business performance through fact-based decision making. On the other hand, business intelligence of BI is a technology that enables data preparation, data mining, data management and data visualization. It allows you to analyze data with queries and create reports and dashboards with the help of charts and graphs to be used by business leaders.

Business analytics and business intelligence together create capabilities for companies to compete in the market effectively. Consider this example. Suppose you sell homemade chocolates through an online store. Business intelligence provides meaningful insights into the past and current state of your business.

BI tells you that sales of your milk chocolate have spiked up in Texas the past two weeks. So you decide to manufacture more milk chocolates to keep up with demand. Business analytics asks, why did sales of milk chocolates spike up in Texas? By scrutinizing your website data, you learnt that most traffic has come from a post by a food blogger based in Texas who liked your milk chocolate.

This insight helps you decide to send complimentary chocolates to a few other well-known food bloggers throughout the United States. Using cutting edge business analytics and intelligence tools such as Microsoft Excel, SQL, Power BI and Tablo, Tenenance customer experience, improved efficiency, conduct competitor analysis and accelerate growth. With this basic knowledge of business analytics and business intelligence, let's look at the topics we'll be covering in this video. We will start with learning the need for business analytics and the responsibilities of a business analyst.

Then we will look at the top business analytics skills and learn about business analytics and intelligence with Microsoft Excel. After that, we will see the basics of business intelligence and get an idea about a giant scrum methodologies. Next, we will learn to create reports and dashboards in Microsoft Excel and understand in detail how to visualize data with top business intelligence tools such as Power BI and Tablo. Let's get started.

We will understand the importance of business analyst with a sort and interesting story. So meet Rob. He runs a cafe in a small town far away. His cafe is one of the oldest and most popular eateries in town.

Rob's cafe was usually popular amongst customers and it was doing very well until the onset of the deadly coronavirus. Due to COVID-19, like other eateries, Rob was forced to shut down his cafe too. This took a heavy toll on his business and subsequently he lost his customers. None of his customers visited his cafe and this resulted in a huge loss for him.

He knew he couldn't afford to close his business forever as it would take time for coronavirus to be eradicated. But he was lost. This situation was new to him and he didn't know how to reopen his business amidst this pandemic. After a lot of brainstorming, he recollected reading about business analysts.

He remembered that business analysts are professionals who enable a change in an organization. He felt like a business analyst could help him sort out his current business problems. Hence, without wasting any time, he set out to hire a business analyst. He hired Ted, the business analyst to help him with his ongoing business problems.

Rob entrusted Ted with reopening the business. The first step Ted took was to have a discussion with Rob and understand the business problems and the objectives. That is ideally the first step a business analyst would take. On discussing with Rob, Ted learned that the business objective was to reopen the business and get at least 80% of the customer base back.

In addition to that, Rob also wanted Ted to look for sustainable ways to reopen and continue the business in the long run amidst the pandemic. Ted studied the case and he came up with a few suggestions that he thought was fit for Rob's business. His first suggestion was to develop an exclusive home delivery app for Rob's cafe. This way, Ted knew that business will improve as customers prefer home delivery in the current scenario.

Next, Ted suggested that Rob has work from home meal boxes added to his menu. Many professionals are working from home currently and having work from home meal boxes would be a good pick for such professionals in the middle of a busy day. Ted's third suggestion was to bring down the selling cost by providing discount coupons that can be utilized by customers. Having a discount will enable more customers to order from Rob's cafe.

Of course, it was not possible to get the customer base back without any short of price cuts in the current situation. Finally, Ted suggested that Rob's staff would facilitate home delivery orders. This way, he didn't have to lay off his staff and at the same time, get the home delivery running. So these were a few suggestions given by Ted.

Yes, depending on the situation, business analysts can take up different approaches. So after the suggestions were accepted by Rob for the app, Ted began to make sure that the development went well, collaborating with the IT team. Ted became the intermediary between the IT team and Rob. He provided suggestions to the team, checked the app through user interface testing and made sure that the requirements met well.

The same applied to the other business requirements and changes as well. Ted held regular meetings to gaze the progress and also kept Rob in the loop and updated him with the status of the project. Attending regular catch-ups helped Rob gain an insight into the progress and give his feedback from time to time. Ted made sure that the entire case was well documented.

By doing so, he could always refer to the documents in the future with similar cases as well. Ted made presentations that showed Rob the business growth after implementing the changes and Ted always supported his presentations with data. Rob was very impressed with Ted's business approach. Ted's approach not only helped Rob reopen his business amidst the COVID-19, but also helped him get 80% of his customer base back.

Ted successfully brought about a positive change in Rob's business which was highly beneficial. So that is how Ted, the business analyst, helped Rob make a business sustainable. This was the importance of having a business analyst in Rob's organization. Don't you think every organization should have a business analyst?

Well, yes. Starting on the business domain and the situation, the roles and responsibilities may vary. Let's start off and have a look at a day in the life of a business analyst through a small story. So meet Angela who is working as a business analyst in an application development firm.

Her firm builds applications for clients depending on their requirements. Our next character is Rob. He is a budding entrepreneur with a vision of setting up his own e-commerce app. He plans on selling several electronic gadgets like phones, laptops, cameras, etc.

on his app. So what is Rob's first step? Well, he approaches Angela's firm one day with the vision of creating his e-commerce app. Angela and Rob start talking business and Angela promises to help Rob with his app creation.

She assures him that she will look into his business requirements and coordinate with him to get the app running. Rob is happy about it and increased to cooperate with Angela regarding all the business requirements from his end. Angela as we know is the business analyst. She starts planning Rob's project and without any delay she embarks on this project's journey.

She has a set of planned steps that will help her fulfill Rob's requirements. But what are the steps she takes? Is her approach going to be effective and quick? Let's find out the answers to these questions now.

Up next you can learn about Angela's approach that helps her deliver Rob's project smoothly and without any hassles. These steps that we are going to look at are the typical roles and responsibilities of a business analyst. Here we will understand these roles better with respect to Angela's and Rob's story. First and foremost Angela understands Rob's business objectives, problems and requirements.

Without understanding this do you think Angela will be able to proceed? No. Hence a business analyst like Angela understands the problems related to Rob's business and comes up with the right solution to achieve the goals of the business. She brainstorms around what is best suited for any comments app focusing on electronic gadgets.

In the next step Angela gathers all the necessary requirements. Here she understands Rob's requirements and makes sure that they are on the same page regarding the project and its goals. Both of them together arrive at a stipulated deadline for the project completion. She gathers relevant information based on security of the app, the payment setup, based on login, cost of the products and style to name a few.

Once Angela has an in-depth understanding of Rob's project and gathers all the necessary requirements she starts allocating resources by keeping in mind the budget of the project. Here she recognizes and allocates tasks and resources to the development team. BAs work closely with the development team to design the solution for a problem. Angela ensures that the development team doesn't spend their time understanding Rob's requirements.

In this step along with the development team she finalises the software and tools required to build the project. Angela doesn't rest until the project is delivered to Rob. She continuously monitors the progress and constantly provides her feedback to the development team with respect to the apps layout, design and other features. She gives them suggestions in order to improve the application.

In the next step Angela collects feedback of the prototype version of the app from the users. She notes down if the prototype is fine or if it requires more work. BAs validate if the project is running fine with the help of user acceptance testing. They verify if the solution being worked on is in line with the requirements and ensure that the final product satisfies the user expectations.

BAs also assess the functional and non-functional requirements. After collecting feedback Angela moves to one of her most crucial duties and that is building reports. The data visualization is a key skill for any B.A. In order to gauge the performance of the app and get valuable insights from it Angela builds reports using various data visualization tools like tabloop, power BI and kick view.

Reports can be general reports such as detailed reports or it can be dashboard reports such as visualised reports with multi-dimensional analysis based on display of business indicators. It is not uncommon for issues to crop up amidst this entire process. Hence Angela conducts regular meetings with the developing team and drop to solve problems quickly. Having these meetings will help Rob understand the status of the project and it will also help the teams proceed in the right path.

Throughout this project phase Angela makes sure to maintain transparency. On completion of the project Angela documents and presents the project findings to Rob. Generally business analysts present the project outcomes to the stakeholders and clients along with maintenance reports. Angela notes on all the project learnings and details in a concise manner.

This will help her take better decisions in the future and these documents will save her time while implementing the next project. Now that she has completed all her duties and responsibilities with respect to Rob's project, she is ready to deliver the final e-commerce application to Rob for use. Rob is rest assured that the application developed by Angela's firm is apt for his business and just what he wanted. Angela's streamlined approach made it easier for the project to be delivered within the stipulated time period.

Rob is happy and I am sure he will come back to Angela's firm for projects in the future. So those responsibilities that we saw Angela carry out are ideally the roles and responsibilities for any business analyst out there. Yes, some may vary depending on the company you work for and the project you are working on. Business analyst is a professional who is responsible for bridging the gap between IT and business teams.

They use analytics to evaluate processes, determine requirements, deliver data driven solutions and generate reports to executives and stakeholders. Business analyst is an individual who is a part of the business operation and works closely with the technology team to improve the quality of the services being delivered. They also help in assisting in integration and testing of new solutions. Growing a career in a field with high demand such as business analysis could be a challenge and competition for business analyst positions can be intense.

So you should have a clear understanding of the roles and responsibilities of a business analyst. A BA should successfully identify and recognize the organization's business objective. They should understand the business problems and think of a lucrative business solution. They need to understand and collect the business requirements from clients and stakeholders, allocate the right resources and improve the existing business.

Documentation of business findings is another important key role of a business analyst. BA is interact with the development team to design the solution for solving a particular problem. They often need to spend a certain amount of time in meetings in order to save the development team from spending their time and understanding the stakeholders requirement. They often give feedback on the layout of a software application as to what or features need to be added and what functionalities should the application contain and also implement the newly designed features that a business needs.

While BA's identify the needs, define the features, write use cases, uncover business roles and manage issues, they should also gauge the functional and non-functional requirements in a business. These analysts run meetings with stakeholders and other authorities. Hence, discussing issues with the client face-to-face can do wonders and even help in solving problems quickly. They engage with business leaders and users to understand how data driven changes to products, services, software and hardware can improve efficiency and add value.

They verify and validate if the project is running well with the help of user acceptance testing and the solutions are in line with the client's requirements. They also ensure that the product delivers satisfies the user requirements. Finally, BA's write documentations and build visualizations to explain all the findings and draw business insights. They also deliver maintenance reports.

They need to develop informative, coherent and usable documents for the success of a project. Business analyst skills are a combination of technical as well as non-technical skills, often referred to as soft skills. The skills for a business analyst are not only acquired through training but through experience and combined with the ability to understand situations and the motive behind the problem. So, let's have a look at the top skills to become a successful business analyst.

The first skill we have is understanding the business objective. For a business analyst, it is important to know the goals and objectives of the business. It is advised that business analysts should have a good knowledge of the business operations in his or her organization. A business analyst should understand the problems related to the business and come up with the right solution.

Business analysts should resolve the problems that have been identified and not avoid them. They work on individual actions and tasks that will build towards the achievement of the goals of the business. Businesses of the business can be to expand customer base in order to increase sales, scale up production so that it is in line with the revenue growth, improve revenue streams through increasing perceived product value or increasing marketing budget according to the revenue. Business analysts should have the natural curiosity and determination to continue learning and figuring out how things fit together.

Even as business analysts become managers, it is important to stay in touch with the industry and its changes. The next important skill a business analyst should have is analytical and critical thinking. Now there is a famous code by Thomas Elba edition which says, 5% of the people think, 10% of the people think they think and the other 85% would rather die than think. Business analysts are paid to think.

A business analyst should be able to analyze and interpret the client's requirements clearly. Business analysts require good focus in order to collect and understand the needs of the client. Critical thinking involves evaluating several options before arriving at the desired solution. In certain situations, a stakeholder may give a requirement that is not necessarily tied up to any business value, but rather to their own increased convenience.

Applying critical thinking demands not taking all the statements of the stakeholders for granted. Critical thinking allows the business analyst to distinguish between requirements that add value to the business and those that should be given a low priority. A business analyst must be creative in order to reach stated goals, where resources are limited and the conditions are non-ideal. The third important skill for a business analyst is communication and interpersonal skills.

Understanding and being properly understood is key to any profession. If you are unable to clearly specify and communicate requirements 20 stakeholder, then you may not fully understand the requirements yourself. Being a business analyst is like being multilingual. You have to speak several different languages while conveying the same message.

Business analysts apply communication skills at every point. They use communication and interpersonal skills when the project is launched, while gathering requirements, when collaborating with stakeholders and also while validating the final solution. Listening, reading and writing skills are very critical for a business analyst. This should be capable of facilitating meetings.

Business analysts use verbal and written communication to convey ideas, concepts, facts and opinions to a variety of stakeholders. Non-verbal communication skills enable the effective sending and receiving of messages, but not limited to body movement, posture, facial expressions, gestures and eye contact. Effective listening allows the business analyst to accurately understand information that has been communicated verbally. Fourth in our list of skills, we have negotiation and cost benefit analysis.

Being a successful business analyst requires working with and interacting with many people. These people include clients, business leaders, project team members, project stakeholders, vendors, private sector representatives, industry leaders and so forth. Business analysts negotiate at every turn during the course of a project. At the initial stage of a project, negotiation skills are used to determine what should be included in the vision of the project.

As details emerge, negotiation skills are used by all parties involved to determine which requests become requirements and which requirements have higher priority. As the project progresses, negotiation skills help to determine the functional design which fulfill the requirements. Technical decisions also require negotiation skills. Business analysts also perform cost benefit analysis to conduct an assessment of the benefits and costs anticipated in a project.

When organizations undertake new projects, it is advisable for business analysts that they use cost benefit analysis to establish whether such projects should be embarked or not. Business analysts should be able to achieve a profitable outcome for your company while finding a solution for the client that makes them happy. This balancing act demands the ability to influence a mutual solution and maintain professional relationship. Up next, we have our fifth skill that is decision making.

The quality of decisions made by business analysts is what matters a lot because it has a direct impact on the company's business. Thus, it is important for every business analyst to think from all aspects before presenting the decision or strategy. They must be having good problem solving skills as well. Business analysts should have a act to think out of the box and find a solution to problems.

Majorly, a business analyst follows five major steps while making a decision. These steps are define the problem, find and define the alternative approaches, evaluate the alternative approaches, make the decision based on these approaches and test and finally implement the solution. While some may argue that the technical team is responsible for designing the solution, the business analyst still remains instrumental in ensuring that the design conforms to the requirements that have been approved. Now that we have reached halfway through the skills, I would like to ask all our viewers to please subscribe to our channel and hit the bell icon to never miss an update from SimplyLearn.

Moving on, we have another really important business analyst skill that is idea about programming languages. Business analysts should have a good hands-on programming knowledge for performing better and faster analysis of data. Knowledge of R&Python is highly beneficial. Business analysts can help solve complex problems by writing efficient codes.

Both R&Python have a vast collection of libraries and packages for data manipulation, data wrangling, data visualization and data analytics. Some of these libraries are NumPy, Pandas, Deplier, Tideer, GGplot and Matplotlib. In addition to these, it is good to understand statistical software like SAS and SPSS. Using these programming languages such as Python, R&S, you can analyze and visualize large datasets as well as create machine learning models for making future business predictions.

The seventh skill in our list is creation of reports and exports. A business analyst should be proficient in using various business intelligence tools for creating reports and exports. It is created by business analysts can be general reports such as detail report, group report, cross-stab report, column report, query report, data entry report etc. It can be dashboard reports such as visualized report with multi-dimension analysis based on display of business indicators.

Dashboard reports are developed by business analysts to solve business decision-making problems. Different from the tabular interface of the general report, the dashboard report adopts the canvas-like operation interface. Knowledge of tabloos, power BI and click view are required to make different types of reports depending on the business requirements. Now the eighth skill in our list of skills is database and SQL.

Business analysts often work with data that is structured in nature. Hence, to store and process this data, they should have knowledge of relational databases such as Microsoft SQL Server, Oracle Database, MySQL Database as well as no SQL Database. Also, having hands-on experience with SQL is a must for a business analyst to access, retrieve, manipulate and analyze data. So they should be able to write data definition and data manipulation commands such as create, update, delete and insert.

Microsoft Excel is the ninth skill in our list. Excel is one of the oldest and most popular and powerful analytics and reporting tool used in the industries for working with data. Business analysts use Excel to perform various calculations, budget analysis and data analysis to derive meaningful insights and take decisions. They sort, filter and create pubo tables to summarize the data.

Business analysts can also create different charts and graphs using Excel to generate dynamic reports related to a business problem. Business analysts can use Excel to create revenue growth models for new products based on new customer forecasts. When planning an editorial calendar for a website, business analysts can list out dates and topics in a spreadsheet. When creating a budget for a small product, they can list expense categories in a spreadsheet, update it monthly and create a chart to show how close the product is to budget across each category.

Business analysts can calculate customer discounts based on monthly purchase volume by product. They can even summarize customer revenue by product to find areas where to build strong customer relationships. And finally, in the list of skills we have documentation and presentation. You could have all the industry experience in the world, but if it spared with poor business analyst practices, you could be more of a risk to the organization than a business analyst with no industry experience at all.

A business analyst must be able to document their project learnings and results in a concise and compact form. They should also be confident about presenting their findings and conclusions in front of the stakeholders and clients. Organized documentation will help you communicate technical concepts to non-technical employees. It is important that a business analyst notes down all the details that they learn from their projects.

This will help them take better decisions in the future. Also, if similar problems arise at a later stage, they can implement the same solution, thereby saving a lot of time and unmonded problems. While business analysts are generally not responsible for making decisions regarding project institutions, decision making skills are still important for understanding, gathering and presenting relevant information to assist decision makers with selecting the optimal solution. With that, we have covered our top skills for a business analyst.

If you have any questions related to the skills that we covered, then please put it in the chat section. Our team will help you solve your queries. Now, let me tell you how SimpliLearn can help you grow your career in business analytics and help you become a business analyst. So let me search for SimpliLearn here.

This is the SimpliLearn website. And the search bar, let me look for Business Analyst. You can see there are a few courses related to Business Analyst. So let me open these two courses.

Let's go to the first course. So this is the Business Analyst Master's Program. Now this program is endosed. Education provider is IIBA.

Now if you look on the right, we have the different courses that will be covered as part of this Master's Program. So there is introduction to business analysis, certified business analytics professional. You will also learn about agile and scrum. This business analytics with Excel.

You will also get training in SQL, this tablo training. And you will also get to work on Business Analyst Capsulean projects. If I scroll down, here are the tools that will be covered as part of this course. So there is Microsoft Excel, Zera, Tablo, Power BI, Postgres SQL, then there is Planbox, Target Process and others.

Here you can see the Program Advisors. And if I scroll further, is the entire course content we have. These are the different courses that you will be learning in this course. And after you finish the course, you will receive a certificate which will look similar to this.

So please go ahead and enroll to this course if you want to start your career in Business Analytics. Now let me take you to another program. We have Postgraduate Program in Business Analysis. Now this is in partnership with Purdue University and EndOST Education provider is IIBA.

If I scroll down, you can see here the key features of this course. You get Purdue Post Graduate Program certification, Alumni Association membership, Master classes from Purdue faculties, enrollment in Simpliolence job assist, there is 170 plus R, blended learning, 11 plus hands on projects, custom projects in three domains. First, scroll further on the right. You can see this is the Purdue certification that you will receive after finishing the course.

You will also get the certificate received by International Institute of Business Analysis that is IIBA. Let's scroll down. You also have the advantage for enrolling to Simpliolence job assist program. So you will get IAM jobs pro membership for six months.

Resume assistance and career monitoring will also have interview preparation and career affairs. Now here you can see the program details. So you will learn about an introduction to business analysis, certified business analysis professional, there is a Jailions Scrum, business analytics with Excel, Tableau Training, business analyst, capstone project. And you also have the opportunity to enroll for some electives.

So we have Purdue University Business Analysis Masterclass. You can also enroll to a Power BI course and there is a Jailions Scrum Foundation. So I scroll down. Here you can see the skills that will be covered as part of this program.

So this business analysis, this allicitation and collaboration, requirement analysis, planning and monitoring. Let me click on view more. You have strategy analysis, dashboarding, wire streaming, data visualization, statistical analysis using Excel, SQL database, this requirement lifecycle management and lots more. So these are the tools that will be covered in this course.

We have Microsoft Excel, Zira, FogBurz, PlanBox, it's Rally, Power BI, ProSql, that's version one, target process and others. And now this is the important part. So these are the industry-related projects that you will get to work on once you enroll to this course. So the first project is canteen ordering system for Unilever.

We also have library management system for Stanford University. There is WhatsApp pay and you can see the description of these projects mentioned below. And we also have hospital management system for Mayo Clinic. There are course advisors for this course.

They are directly related to Purdue University. School further, just a learner's profile and how the industry trend has been for business analysts. So please go ahead and enroll to this program if you really want to start your career. Or you want to grow your career as a business analyst.

Now here is a quick roadmap that depicts what a fresher needs to possess to become a business analyst. First, they need to have a graduation degree in a related field. In addition, knowledge of SQL and relational database is very important. Thirdly, a fresher should have good hands-on experience with programming languages and that's a prerequisite.

And finally, they need to have good communication skills to nail the role of a business analyst. Up next, we have the roadmap that depicts what an experienced professional needs to possess to become a business analyst. Firstly, they should have good knowledge of the domain they are currently working in. Next, they should know how to write SQL queries.

An experienced professional should be good with programming languages. In addition to that, they need to have good communication and negotiation skills. Finally, they should be good at creating interactive reports using business intelligence tools. In addition to that, having a certification offered by International Institute of Business Analysis, such as Certified Business Analysis Professional, would be highly beneficial.

Have you ever wondered how companies use data to make important decisions and improve their operations? Well, that's where business intelligence comes from. Business intelligence, also known as BI, is a set of tools and processes that help organizations analyze data and make informed decisions. It's like a crystal ball that helps businesses see into the future and make strategic decisions based on the data analysis.

But how exactly does BI work? Well, it starts with collecting data from multiple sources like transaction data, customer data and social media data. This data is then processed and analyzed using BI tools like dashboards, reports and analytical models. The insights provided by BI helps organizations identify trends, patterns and opportunities that they can use to make better decisions and drive growth.

So in this video, we are going to take you through the core concept of what business intelligence is and why is it so important? So without any further delay, let's get started with what exactly is business intelligence? Well, at its core, business intelligence, often referred to as BI, is the process of collecting, analyzing and transforming raw data into actionable insights for business purposes. It helps organizations make informed decisions, enhance performance and gain a competitive edge in today's dynamic market.

So let's understand these steps involved in the processing of data. The first step in the business intelligence process is data collection. Businesses begin by identifying the relevant data sources for their operations, such as internal databases, customer interactions, website analytics and social media platforms. Once identified, the necessary data is extracted from each source, which can be in various formats like spreadsheets or databases.

For Proceeding, it's important to cleanse the data by removing duplicates, errors or inconsistencies, ensuring it's accuracy and reliability. The second step is data integration. With the collected data in hand, the next step is data integration. Businesses transform the data into a unified format that is compatible and consistent across different data sources.

This transformation involves standardizing data formats, organizing fields and creating a unified data structure. The transformed data from various sources is then merged into a central repository or data warehouse, serving as a single source of truth for further analysis and reporting. The third step is data analysis. Businesses select appropriate analysis techniques based on their objectives, which can include exploratory data analysis, statistical modeling, data visualization or machine learning algorithms.

Using these techniques, businesses uncover patterns, trends and correlation within the data. These insights provide a valuable information about customer behavior, market trends, operational efficiency, product insights and more. To communicate the findings effectively, businesses create reports and visualizations that present the insights in a clear and understandable format. The fourth step is decision making and action.

The final step in the business intelligence journey is turning insights into actions. Armed with the insights from data analysis, businesses make informed decisions. These decisions can range from optimizing operational processes and refining market strategies to improving customer experience and identifying new business opportunities. Businesses continuously monitor the impact of their decisions and actions using feedback groups and iterative processes to refine strategies, adapt to changing market conditions and improve overall performance.

Have you ever wondered how successful people can be after opting a postgraduate program in business analytics? Here it from a learners who have experienced massive success in their careers. Hi, I'm Kudana Rijick. I live in Raleigh, North Carolina and working as a business analyst at Ravajwar.

This is my second job since I completed the postgraduate program in business analytics at Simplenrun with Puget University in December 2021. My experience with Simplenrun was great. The life classes were my favorite because they were very interactive and I could connect with instructors. I have many small gaps and short employment in my career.

I even have a huge two-year career gap. Needed some health issues. However, I think the dark times are not behind me. It doesn't matter how challenging the path may be.

Keep up scanning and one day you will achieve successful life. The next question is, why is business intelligence so valuable to businesses? So let's explore its benefits. The first is enhanced decision making by providing accurate and timely insights, BI enables organizations to make informed decisions based on facts rather than assumptions or intuition.

This leads to improve efficiency, reduced risk and better outcomes, increased operational efficiency, business intelligence, streamlines, operations by identifying bottlenecks, optimizing processes and highlighting areas of improvement. This leads to enhanced productivity, cost saving and overall efficiency gains. BI has a competitive advantage in today's competitive landscape gaining a competitive edge is crucial. BI equips businesses with actionable insights about market friends, customer preferences and competitors, enabling them to make strategic moves and stay ahead of the curve.

Applications of business intelligence. Retail. BI helps retailers analyze customer buying patterns, optimize inventory levels and personalize marketing campaigns, ultimately improving sales and customer satisfaction. Healthcare.

By leveraging BI, healthcare providers can analyze patient data, optimize resource allocation and identify patterns to enhance medical treatments and patient outcomes. Finance. BI enables financial institutions to assess risk, detect fraudulent activities and identify investment opportunities, resulting in improved decision making and financial performance. Let's understand the tools for business intelligence.

A number of BI tools are already present in the market, but let's go through the top business intelligence tools. Power BI. Microsoft's Power BI offers robust data visualization capabilities, interactive dashboards and integration with various data sources. It's user friendly and allows for collaboration and sharing within the organization.

W. W is renowned for its interactive and intuitive data visualization features. It supports advanced analytics, custom calculations and offers seamless integration with multiple data sources. Click V.

Click V provides a comprehensive business intelligence platform with powerful data discovery, visualization and reporting features. It allows users to explore data from various angles and uncover hidden insights. Looker. Looker offers a cloud-based platform for data exploration and visualization.

It focuses on providing real-time insights and collaborative analytics, enabling teams to work together seamlessly. So there you have it, folks. Business intelligence is an essential tool that can help businesses succeed in today's market play. Now let's see what Power BI is.

Power BI is a business analytics service provided by Microsoft that lets you visualize your data and share insights. It converts data from different sources to build interactive dashboards and BI reports. As you can see, we have an excel data about sales. Using this data, Power BI helps you build different charts and graphs to visualize the data.

Now that we have understood what Power BI is, let us look at the important features of Power BI. First is Power BI Desktop. Power BI Desktop is a free software that you can download and it allows you to build reports by accessing data easily. For using Power BI Desktop, you do not need advanced report designing or query skills to build a report.

Second, as already discussed, Power BI supports stream analytics. From factory sensors to social media sources, Power BI assists in real-time analytics to make timely decisions. Third, support for multiple data sources is one of the major features of Power BI. You can access various sources of data such as Excel, CSV, SQL Server, Web files, etc.

to create interactive visualizations. And finally, custom visualization. Custom visualization is another vital feature of Power BI. While dealing with complex data, Power BI's default standard might not be enough in some cases.

In that case, you can access the custom library of visualization that meets your needs. Let us jump into discussing the various components of Power BI. As you can see, there are six major components of Power BI. Now let's discuss them one by one.

First is Power Query. Power Query is the data transformation and mass up engine. It enables you to discover, connect, combine and refine data sources to meet your analysis need. It can be downloaded as an add-in for Excel or can be used as part of Power BI desktop.

Second, we have Power Pivot. Power Pivot is a data modeling technology that lets you create data models. It also allows you to establish relationships and create calculations. It uses data analysis expression language or DAX to model simple and complex data.

Third, we have Power View. Power View is a technology that is available in Excel, SharePoint, SQL Server and Power BI. It lets you create interactive charts, graphs, maps and other visuals that brings your data to life. Next, we have Power Map.

Macosops Power Map for Excel and Power BI is a 3D data visualization tool that lets you map your data and plot more than a million rows of data visually on Bing maps in 3D format from an Excel table or data model in Excel. Then we have Power BI desktop. Power BI desktop is a development tool for Power Query, Power Pivot and Power View. With Power BI desktop, you have everything under the same solution and it is easier to develop BI and data analysis experience.

Finally, we have Power Q&A. The Q&A feature in Power BI lets you explore your data in your own words. It is the fastest way to get an answer from your data using natural language. An example could be, what was the total sales last year?

Once you have built your data model and deployed that into Power BI website, then you can ask questions and get answers easily. Now, let's see what Power BI service is. Power BI service is the software as a service part of Power BI. It is also referred as Power BI online.

To access Power BI service, you need to log into app.power BI.com. Now, let me show you that. I will go to Google, open a new tab and search for app.power BI.com. It is loading.

But this is how the homepage of Power BI service looks like. I have created some dashboards on it. First, you need to log into app.power BI service. You can see I am logged in.

Now under my workspace, if I go to dashboard, here I have created a finance dashboard. You can see the different charts and graphs I have prepared and pinned it to the dashboard. So Power BI service allows you to connect to your data, create reports and dashboards. And you can also ask questions to your data.

Now, as you can see in this dashboard, we have created some charts and graphs. So this is a tree map. There's a pie chart. There's a bar graph below.

You can see there are line charts and donor charts. It tells you the total sales that were made, the total number of unit sales, the sales by product, sales by country, sales by segment and lots more. One of the key features of Power BI is creating dashboards from multiple reports and datasets. Power BI dashboard is a single page visualization to tell a story.

The visualization on a dashboard are generated from multiple reports and each report is based on one dataset. A single page dashboard is known as a canvas. The visualizations you see on the dashboard are called tiles. These tiles are pinned to the dashboard by report designers.

Now, let me go back to my dashboard. So this is called a canvas and each of these are called tiles. So on the top, you can see we have three tiles. Now, let's understand how to create and publish reports in Power BI dashboards.

Power BI allows you to create different reports on Power BI desktop. These reports can be published on the Power BI dashboard using Power BI service. Here, you can see there is a Power BI report created on Power BI desktop. If you click on publish, it will take you to the Power BI service where you can build a dashboard.

Here is the button for Power BI Publish. Once you click on Power BI Publish, it will take you to the dashboard. So this is a single page Power BI dashboard on Power BI service. Now, let's understand the Power BI architecture.

Power BI architecture is a service built on top of Azure. There are multiple data sources that Power BI can connect to. Power BI desktop allows you to create reports and data visualizations on the dataset. Power BI gateway is connected to on-premise data sources to get continuous data for reporting and analytics.

Power BI services are basically the cloud services that are used to publish Power BI reports and data visualizations. Using Power BI mobile apps, you can stay connected to their data from anywhere. Power BI apps are available for Windows, iOS and Android platforms. Hey there, have you ever looked at a pile of data and thought, how do I make a sense of this?

Well, that's where Power BI comes in. Imagine turning boarding spreadsheets into stunning interactive dashboards with just a few clicks. That sounds exciting, right? And in this video, we are diving into Power BI from the basics to transforming data, creating charts, visualizations and even building a real dashboard in our demo.

So whether you're a beginner or looking to sharpen your skills, this is the perfect place to start. So let's get started. Welcome back everyone to Simprila. Today, we are diving into the exciting world of data visualization with Power BI.

Where we will explore how you can transform raw data into powerful insights and visual stories. Whether you are a business professional, a student or an IT beginner, this session is designed just for you. We will go through the introduction of BI, see how we install Power BI, then we'll see the data transformation. We will deep dive into visualizations principles and creating charts and graphs.

After creating charts and graphs, we will go ahead and create an interactive report in Power BI. Before diving into Power BI, let's first talk about business intelligence or BI. BI refers to tools and processes that helps organization to collect, analyze, and use data to make smart decisions. Think of it as your compass in a sea of information.

It points you to trends, predicts outcomes, and help improve general performance. Let's see how Power BI helps us with its feature to analyze and make informed decisions. Now, Power BI is one of the most popular BI tools out there. It is developed by Microsoft and allows you to connect to different data sources, create interactive visualizations, and share insights seamlessly.

Whether your data lives in Excel, SQL databases, or even web applications. Power BI can connect to it. By Power BI, you ask because it is user friendly, powerful, and widely used by businesses worldwide. Plus, its visualizations help you to present data in a way that's easy to understand.

Let's dive deeper. These are three major components of Power BI. First is Power BI desktop application. Second is Power BI online service.

This Power BI service can be your server, where your organization data decides and can go ahead and share your reports across your teams within your organization. And then the next year you have Power BI mobile application. All these three make sure that the reporters developed and shared across. Plus, it can be viewed by the end user easily too.

We are going to create your ports in Power BI desktop application. Let's go through the installation and setup of Power BI. Installation and setup is very easy. We can simply go ahead and download this desktop for free.

If you want to go ahead and explore the sharing, then only you need the online Power BI. However, to understand and learn Power BI desktop, you only need, you can go ahead and simply download. You can click on download free button, enter the required details and start and get started. You can also go ahead to Microsoft applications if you're working on Windows.

And from there also you can go ahead and download Power BI desktop application. Once you have downloaded, you can simply follow the honest cream instructions and download, install and download the application on your system. Once it's installed properly, your Power BI desktop might reply to us. Here you have events on which features are displayed.

On the left hand side, you will have a vertical menu card, where the report view, table view, model view and query view. On the right hand side, you will find three paints, filter, visualizations and data. You might have a vertical pane on right side too, where we can go ahead and switch on and off these selections on the pane. Similar to X-SIA, you will also find here page one.

You can simply click on plus sign here and add more pages and reports here. Once you have the extra, we need to go ahead and connect with the data sources. Power BI can connect to multiple data sources, that is 95 plus data sources and the connectors available there. The most popular ones are Excel, text and CSV files, SQL servers, web APIs and more data connectors.

Power BI makes connecting to data incredibly simple. You can pull the data from Excel, perfect for small data sets like sales reports or projects. SQL server are go to four larger databases, web data sources, imagine pulling live data from APIs or websites, and other connectors are Power BI supports countless connectors for any data that we need from other applications, software, cloud and servers. For beginners, start with an Excel sheet or a CSV.

It's familiar and Power BI integrates with that beautiful. Before we go ahead and look at the visualizations and Power BI, let me show you how to be connected with a simple text or a CSV file. This is a server Power BI text from. Under the home tab, we can see we have data and queries here.

We want to connect with a simple CSV here. So we go to the get data drop down. We click on text or CSV. Actually, I'm going to connect with a CSV data set, a simple retail sales data set, everyone.

See here, you can see right now, this is the date region, category, sales and profit. And the deal in which we are going to scomma, all these columns are automatically identified from a simple CSV file. Now, we have three paths to select, load, transform data and cancel. Load here, we directly load this particular data set into the Power BI text from.

Transform data will take us to another window, which is Power Query. Within Power BI, desktop Power Query is one of the components which will help us to connect with data, the components that we see in data group and in the query group. These both belong to Power Query. They both belong to Power Query.

Power Query helps us in ETL process. ETL is extract, transform, load, data set. We can see here, we do have two options. That is load and transform data.

Both the paths here are from Power Query. So let's go ahead and have a quick look into what is Power Query and how does it look like? So we are clicking on transform data here. And we are directed to Power Query Editor here.

Power Query Editor is going to be a separate window. This is our Power Query Editor. This Power Query Editor window, you can see we have our tabs here, here it comes. These ribbons are majorly concerned with transformation and cleaning of data set.

Also observe there are three paints, queries. This is the view. In Power Query Editor, we have three paints, queries, which are data set that we are extracting from the data source. Second is this is our preview paint.

And third is query settings. Currently, we will deep dive into visualizations for and into cleaning and transformation. We will see that another video. We will listen, go through the basics here.

So first, look at the state. We can see the preview that this is a date column. We can click on this calendar item. And we can change the data type that we have here.

Usually, Power BI is successful. And I need to find the data type. As you can see right now for the region, that has a successful identified text for number, but set as a number and likewise. We also have a vertical bar.

We help a horizontal bar. We can explore other columns that we have in some data set. As you can see, the data type is properly identified. We are only going to go ahead and change the name of the data set.

Currently, it's a retail data set. So let's rename the story, deal data set here. And now we will go ahead. Closing the Power Query Editor and applying and loading the data set into the Power BI extra.

We do have an option to only apply and not close the editor. We do have the option to only close and do not load the data set there. Currently, we will be closing and loading the data set there. Closing and loading the data set into the Power BI extra.

You can see the data set is loading up here. It's a small data set upon the draws. Now here we have a retail data set. Once we have a data set loaded, now we can go ahead and start working on creating visualizations.

But before we create visualizations, we should be aware about the basic. Interface of Power BI and the terminologies related to Power BI interface and extra. First of all, there is not much space here to work. You can see the dotted line square here.

Next, understand visualizations. The visualizations. All visualizations are images created from data. We help you see patterns, trends and insights at a glance.

In Power BI, we can create visualized, pie-jots, blind juts, maps and deepwits. Pie-jots are very close to the proportions like the entire image. Let's discuss them one by one. Power or follow-juts.

Power or follow-juts are created to see the distribution between one. Get a goalable variable at one-mile goal variable. As in the example you can see, you are looking at month-wise sales variance and cost of age. Or you simply want to go ahead and see the average selling area size for two different store types here.

Line and area charts. Identify trends over time, light-luxite traffic, sales from last year and next year. Or to look at a certain patterns, seasonal or cycle. Line charts and area charts are typically created over time series.

Time to meet us any component of age hierarchy or time hierarchy. Meaning year, moderate, month, weeks or days. CIRC, pie-jots, dou-r-jots and penitents. Tuts are great for certain proportions like sales-wide engine, sales-wide different chains or categories.

Similarly, dou-r-jots can be used for similar reason to show percentage, distribution across certain dimensions and category to the radius. Per-end charts may show proportion, in percentage here. As you can see right now, opportunity count by sales-stakes. We are looking at the sales-wide right now.

How many leads we have? How many? So how many can qualify it out of that? How many have we have provided distribution for?

Then out of that, how many may be needed? The whole world today. And how many? Out of the 100% were at last finalized and converted.

So part day of this, for core, Belgian map wish codes, you have to be present in kind of trouble to the leaders. So your display of the data, which has sales-wide concern, may be by state or any other location or the particular location. Based on data. There are core Belgian maps.

Postures will be set above map. They can be created like these near here, for example. Another is Feldmap. Feldmap is where the area, the vertical area inside map is filled with colors.

Third is ArcGIS map. ArcGIS map is an online-collected map, which can show you any need for this text. It is interactive and done. It has many more features as compared with simple, bubble map and Feldmap that we have seen.

Last one is Shearplaps. Shearplaps are good for highlighting. In Shearplaps, we get on her daily books and make him own highlight or color, the nature which we are seeing. Let's begin with creating charts and reports in Barbier.

Hi, Luvan. Welcome back to Simplion. Here we explore the world of Leonardo X and visualization. Today, we will dive deep into Power BI to create a variety of charts and explore how to make interactive, engaging dashboards, just like this.

We will go up with the sample details dataset. The visualized scheme metrics like sales, profit, unit sold, at the end of this video, you know how to create bar charts, line charts, pie charts, donut charts, stag bar charts, and even a map visualization all on one page. So grab your laptop, open Power BI and let's get started. Now, we are in Power BI.

In this part page, you might find a few new things. On the right hand side, vertical corner, you can see a data, paint, you have to click on the second build paint, which will give you the options for visualizations. The third icon here is to form a whatever object or chart that is right. With the plus sign here, you can customize and get more icons from the insert menu here.

If I click them on again, we will be vanish from your view. You can show and hide the paints by clicking on these items. The left hand vertical paint remains unchanged. Here are your report view.

These are table view and here you have the model view. Today, we are going to explore different type of charts in Power BI. To create and explore the different type of charts, we are going to work on a very simple retail data set, which is a CSV file. You connect with text or CSV.

Different text or CSV. Our usual, you can see we can see on here same as text to columns and Xion. It has identified comma, a video limit. Now we are going into, we are going to click on transform data.

This will take us to the power query. In power query, there is a let's check data type right now. We have date with the date property that I hear. Sales profit is in decimals.

Then we have container state, which is text. This all seems fine with us. Let's close and apply. Always remember that the interface might look different as Power BI gets updated.

Every month not interface, but the power BI and power BI online service that tool. Once we are connected with the say here, here, today, sales, we can see we have category country date and profit. Let's set their properties first. Technically is fine.

It is simple. Text and we are okay with that country is a geographical data set. So we go here and we consider we will describe this categorize this as country. It will it is not recognized as geographical data set.

Same goes with the state here. We will decide that this is a state. We communicate this to power BI. It is a geographical data set.

Now, let's begin here. While exploring different type of charts. As you can see the data set we are using in the sample details dataset, which includes date, region geographical location, category, the product category, sales from a division will amount from a division date total sales amount. Profit and on that particular date.

And the total number we are sold for that particular category. We have started by importing this data to power BI and now we are moving on to visualization. Let's see some basic visualizations here. First, let's create a bar chart.

You can see here we have a bar chart is a stock bar chart and here also we have a bar chart. Let's create sales by region. Click on the clustered bar chart visual in the visualization thing, which is it was shown the third icon here inside the build pane here. On the right hand upper corner you can see the preview of this bar chart.

As soon as you have the preview of bar chart here, observing below the build pane. We have y axis x axis legend and more options here. Add region to the x axis field. You can also go ahead and check on region.

Can we get the dragging drop or you can simply check on region. Region gets added into the y axis. And drag sales to the values we that is x axis here. So here is sales.

We are dragging this to x axis here or we can simply check on sales here. As you can see a bar chart is created. You can resize it and keep it here. Now let's format this chart.

Let's see the formatting options for the bar chart. This is only formatting options. I will go to the right hand side in the vertical options. I will click on format.

Once I click on format here, you can see this particular format pane. Consist off all the formatting options designed only for this bar chart. First, let's switch on the data labels. We just scroll down and switch on the data labels here.

Switching on data labels will give more information about each other rather than going and comparing with the y and x axis. Once we see the numbers here, they are not much visible. So we can expand data labels. For values and increase the font size, may be change the font style here.

And you can see now they are pretty much visible. You can also decide what units we would like to see here. Maybe we would like to see thousands with one decimal point. Now see these numbers right now are written at the end of the bar.

As you can see and the position is one decided. You can scroll up here and within the options just above the value and the title. You can see the position currently is automatic. Automatic means whenever you will change the font style or size, the position is decided automatically.

If you want to fix the position, you have the options here like inside end. Outside end. Inside center. Outside base.

Currently, I am liking it better at the inside end. I would also like to go ahead and change the color of the bar, which is by default blue. In an organization, you might have been given template to follow. A color template to follow.

You should go ahead and follow that template. Currently, I am following the basic color here. Format under the wish verb format settings. We have changed the part color and given the data labels and formatted them too.

In the format, we do have properties. These properties are not specific to the chart. These properties appear on every chart. For example, the header icons.

You want two tips to be there. This is the tool tip. When you hover over the cursor, what do you see? You do have advanced options here.

Okay, whether we do have advanced options here to all these are common to each chart. Visual here. You have size and style. The size and position of this particular chart, it can be created from here.

You can also decide the background, visual, border and the shadow of this particular chart. Currently, I am going to switch on orders and the shadow here. To show you how the basic formatting looks like. Below the size and style, we have title.

Currently, title is sum of sales by an agent. Usually, we don't write like sum of sales by region. Instead, we will be writing total sales by region. Or only sales by region will work too.

You can also decide what kind of font should be there. Always, already font given by the organization. You will have a fixed font to be used. You can also decide the font style, font size.

If you want to give any background color to it. I also remember that. It is once it is given and can be reused multiple times. So, in A&O, we don't have to do it multiple times.

We are formatting this only once. So, this is a simple bar chart, maybe formatting techniques. Now, we want to build up another chart. So, let's see, align chart, everyone.

Let's figure out, trend over months. To create another chart, make sure that you click outside and none of the options should be visible for this particular chart. So, click outside and we blank area. And automatically, we will see only the format option remains.

Okay, that is the simple format for the page and we will pick up. Once you are outside, let's go ahead and create a line chart, everyone. You might find the line chart here in the build pane. So, click on the line chart and here we have the line chart.

I am going to place it up here on the second quadrant of the screen. You can see a preview of the line chart here. Now, since we are creating a line chart, always remember, line chart is always created to show a time series pattern and trend. Meaning, we need a time series or date column here.

So, we do have a date, we will simply check on date and by default, that date goes into x-axis. You can see we have added EF, Portram, month and day, everything at once. Because date is hierarchy, everyone. It's a natural hierarchy.

So, when you click on date here, or it will add up to the date. Since, let's see the sales trend over months. So, we are not looking for day, we are not looking for quarter, we are only looking for year and month. So, we will simply add year and month.

We can simply cross it off here. Once we have the x-axis here, we want to see total sales here over trend over month. So, you will check on sales, it will go to the y-axis. However, we are not looking at the line chart.

We have here the single dot. Now, let's figure out why. See here on the x-axis, it says that on going to any tree, this is the total sales. It means we have a data for only one year.

Also, observe now you have multiple arrows, icons and the corner of your chart. These multiple arrow icons are the options to drill down. Currently, we can see here, why sales here. See this, two parallel arrows.

It says that, go to next level in hierarchy, the next level in our data hierarchy is month. So, if I click on double parallel arrows here, now we can see monthly pattern here. We will drill up with a parochie here. You can see a single dot again.

Similarly, you see this fork here. This will expand down to all the levels in the hierarchy. It looks like a hierarchy flow chart. When you click in here, it will show you year and month both.

See the icon here. See the x-axis here. You have got 10, we will tree, mid-vary, tree, to line with tree. And here we have a trend.

So, we have successfully made a line chart, which showing us sales trend over month. It's format this properly everyone. I'm going to switch on the format to keep the size here. I'm going to switch off data label for now.

I have switched off data pain for now. Here is the format everyone. In this format, now you can see we have size in a time. That is fine with us.

Now we have a scroll down. We have something else other than the data labels. Always remember in the line chart, we don't switch on the data labels. If you want to show the numbers on a line chart, it is always advisable to create the column chart or a table with the same date and the numerical value to show the numbers.

Because here, line charts are only created to show trend and patterns and to predict those patterns there. It's what we have here as markers. When you switch on the markers, now you can see where each month lies that we cannot see on the x-axis here. When you increase the size of the line chart, you might be able to see a little bit more.

When we are switched on the markers, when you scroll down, you do have the option to change this shape of the marker. As you can see right now, you can also increase the size of the marker. You can also go ahead and change the color of the line. Now how to change the color of the line here?

So we scroll up here, all of our markers, above the markers here we have lines. And the lines here, can be we have just one line. So we are going for all. The line is solid dash or dotted.

So currently we are going with the solid line here. Join the type is downed. We have here, myter, the well, okay, it doesn't show anything here. This is the birth, everyone, and keeping it drowned.

This one. So I'll show any changes here. Now this is the birth that you can increase here. Okay, and currently we are going to keep it either linear.

We have got a smooth option here. It looks like this. And here is this step option. Currently, I'm going to go with linear.

And remember that it might not be available in your bar B and this is the latest version we are working with. Of course, you can go ahead and change the line. Color from here. So this is the line chart, everyone do remember.

You need to still work with the title. So we scroll up. Go resize and style which is common to every chart here. We can scroll down here.

We have visual waters and shadows. If you want below that, you'll find the title inside this title. We are going to look. In this sale streamed over months.

Here try to be. So give exactly similar. So here we have got line chart. I'm going to resize both of them so that they are looking.

Align on average. Dash. We have seen a simple bar chart and a line chart. Next is a pie chart.

A way. As usual to create another chart, we click outside in the area. But then the report. Now we can see a pie chart on the belt paint.

Then the video of pie chart will see sales contribution by category. So I'm going to click on pie chart. I'm switching off the format to have a better space. Now we can see the pie chart here.

You want to see sales distribution by each category. So let's click on category everyone automatically. You can see it is going to legend right now. I just want to show the percentage distribution values here.

So let's check on sales directly go to the values. And automatically you can see here it is calculating the percentage for us. We can see category numbers category numbers are also here. With the list of category legend here.

So we do have what colors we have got name or categories that decides as literally here to make it readable and a better visualization. Let's go ahead and format this pie chart. There are a few things that we are going to fix here. Postes divide in colors.

Second is I can see the number and the percentage. However, to connect it with which categories we have to still match the colors. With the legend instead of that we'll bring the name of the legend within the data label itself. So again, I will switch off data.

I also want the format option here. The format options specifically for the pie chart. You must have experienced by now for every chart. There is a different options to format.

First fix the detail labels everywhere. So here we are they are not calling it data label. They are calling it detail labels because we can add any details you want here. For example, we are not looking for number.

We are looking for percentage and the name of category. So the details options here or position is outside. This is where we prefer here. Now we can go to label content find here category and person told.

We do have more options here. We are going with category and person to photo with most logical options right now. Now we can see both of them are here. Right.

Now we will expand the values. Again, you have the option here to change the color so that they are more visible. Maybe make them bold or increase the font size here. Now we can see here are there any units right now.

There are no units is the percentage click on them. It do have the option to percentage decimal points. We can type to this is our detail labels. Our detail labels here.

We have the rotation. For example, if you want to show it is one first, you have the option to rotate it and show the highest slice first. That all depends on you which kind of rotation are you looking for. These settings are similar to what you have seen in Excel so far.

We find the exact same settings in Excel to. Now last is the biopin colors and the legend. So we don't require legendary move. You can simply switch it off here.

Let's fix the colors. What I'm going to do here is I'm going to simply select the lighter version of each color. Remember that usually you will have a template given to you by a organization. And you are supposed to follow that template and the colors that are associated with the brown.

And it is a much better way to go. Currently, picking up the colors which are more suited to the eyes and have a good contrast to be seen with each other. So this is our pie chart. Everyone now in this pie chart here, we do like to go ahead and edit the title and the background and the shadow right now.

We can actually do we have what we can do here is we can again go here to size and it's time. With size and style, we have the usual border and the shadow and below that we have got tighter and this item here. This is sales contribution by category. So let's name it proper.

Say it's contribution by category. We can increase the size. We can change the quality style right now. We can give a background color here and make it a center.

Now this is our pie chart. Everyone let's start as donut chart. Let's explore the donut chart. Let's figure out profit by region.

So we have profit margin here with the buy region. To do that, to see profit margin by region here. Let's see it by donut chart. I repeat a donut chart here.

It is just beside the pie chart again. Click outside in the region. We are going to click on the donut chart here and it's donut chart. We have the exact same portion here.

Remember that donut chart and pie chart are exactly similar and concept. However, they do look different. As you can see here right now, you can see the preview of the donut chart. It is quite different from pie chart.

It is still showing the percentage distribution here, but the center part of the pie. It looks like a ring. So let's go ahead and view how does donut chart look like. We are simply going to check on region and the profit as we did for the pie chart.

Now we would like to go ahead and you can see here it is exactly like the pie chart with the middle circle is gone. We would like to go ahead and format it similar to the pie chart where all the regions written here, the only region and the percentage of the profit here. And of course, we would also like to try the title here as it is. But since we are in power BI, we don't need to go ahead and format it every time.

Since we are in power BI, we are not supposed to do redundant steps here. We will simply go ahead and select pie chart. We can click on format painter. We can come back here.

You can see the paintbrush is here. Now click. And here we are. You can see the title has been changed.

You can see the labels are here. Only thing that is not changed is the colors. So we now open the format. This is only data here.

In the format, I will go to slices and again, I am going to simply select a shade lighter than the original color here. Here we are. You can see some of profit by region. Of course, you would like to go ahead and change to a proper title.

So let's give the title as profit margin by region. As you can see, there is no okay button. Whatever changes you do in the format paint and belt paint, they will automatically apply for it. Other store region by VFC 4 charts, bar chart, mine chart, a pie chart and donut chart.

Now next is we will see a little bit advanced visualizations. For that, I am going to the next part here. I have added one more sheet named basic charts too. And you can see I have a background here.

For all the other basic charts that we are going to see. In here, we are going to see stack bar chart, drill through line chart and a map visualization. Let's first see what is a stacked bar chart. We are into the belt here.

The first chart that you see here is called as a stack bar chart. I stack bar chart as you can see here. It looks like a normal bar chart. However, we do have the option.

We do have the option here. To add within one categorical value and see the distribution over one single numerical value here. For example, here we can see units sold by region and category. Region and category being two categorical variables.

And we want to see the distribution of units sold by region and category. So first check on region. Then on category, you will see automatically. We will place themselves.

Since there are four regions, regions will go to X, Y, X is here. Legend is coming back to category. Now we check on units sold everywhere. And it goes directly to the X axis here.

And here is our stack bar chart. Of course, it is the exact same bar chart, right? Or with each bar is getting divided into individual regions here. So here category we have groceries and region both.

I don't want to go ahead and do the formatting all over again. So we can go back here. You can select the bar chart. We can format paint it and paint it out here.

Now let's understand this bar chart effectively. Each color represents individual category. So as you can see here, okay, we have got loading electronics, furniture and groceries. And each of these numbers represent in number two.

That's sold in that particular category in that particular region. It means that three C2 units of groceries have been sold in this region. And within one bar, we can see the differences here. This is unit sold by region and country.

It has a stack bar chart, everyone. Let's resize and keep it here. Let's explore the formatting options that we have here. You will find the formatting options are exactly similar to what we have seen before.

We have seen data labels, but here we do have total labels here. Total labels will give us total by whichever we have only by excess. Right now, I don't see much use of the x-axis right now. So we can scroll up.

We can go to the x-axis and we can say that I don't want to see neither the values here, nor the title. It will give us a bit of space. It will give us a bit of space here. This is a stack bar chart.

Now let's learn in detail what is a drill through line chart. Let's learn. When it's done about the drill through line chart, you might be thinking that we have just seen a line chart. We have drilled through that.

Yes, we did. But now we have to actually learn a difference between the continuous and discrete drilling down in line chart. So let's see here. We are going to go ahead and explore the line chart again.

So click outside please. Then click on the line chart here. The line chart appears as you can see here right now. As we're aware, line chart requires a time series.

So we go ahead and we check on date hierarchy which automatically goes into x-axis here. Now the state hierarchy actually goes ahead and gives us the drill down ability. We don't want to drill till individual day here. We are looking for only a quarter and a month.

Usually we only have one line that we have seen so far. So we go ahead and check on sales for now. Now we are aware that dry current area showing us only by ear. That's why we are just one dot because we do not have multiple ears.

And we are also aware that we can go to the next level in hierarchy. This time the next level in hierarchy is quarters. So when you go ahead and go to the next level in hierarchy here. Okay.

What you're looking at quarter wise total here. Some of sales for each quarter. Centres it is only one year. This particular sales of quarter is fine.

It shows us quarter one tool chain for however. If you had multiple years like when you do two, 23, 24 and so on. Then it will still show quarter one to the sales from all of the years. Meaning currently it is showing us discreetly only for quarters.

It is not considering that quarter belongs to a certain year. Similarly, you can see right now since we have one more hierarchy left. That is month we do have this is still activated. If you go in here, we do have monthly distribution of sales over the month.

And you're also able to aggregate every year month sales over all the years that are present. So it is just one year. It doesn't show much difference to us. Now I will drill up again.

And we see quarters again and then here we see years. Now if I go ahead and switch in here, expect all down to one level in hierarchy. Here you can see St. January April July and October 23 here.

However, it does write month on the XXS. But this line chart shows only as per quarters. You'll also find that currently this will also ask you that a here is still the scope of drilling down is a better problem. So we go ahead and we click here again and here we are having exact same mindset as we have seen before.

After the till town. What is meant by doing downward here? So here you can click on the start here. Now since we are going to basic charts here, let's also explore right now.

We have only just one line. We have always added only one line and a line chart. That's also go ahead and add profit here when we line chart. Now you can see we have got two lines everywhere and now body lines can be drilled up or can be drilled down.

And we can compare deep trend between profit and sales. Again, we will go back to basics charts here for the formatting. We will go ahead and get a format feature here. And use a foreign painter to format our line charts.

Since we have got two lines here, we might want to go ahead and change the colors. So we will go scroll down here. We do have lines. We can decide the color for individual line.

So remember that when we go to the lines here, you decide which line you want to change the color for. So for example, I'm going for some profit. We will scroll down here and we expand the color. Now we can change the color here for the profit.

Right. As you can see, this word and everything will remain exactly same as the formatting the code below the lines here. We do have markers again for the markers. You can choose which particular line are you looking forward to go and change the markers for.

I'm simply changing the color for the markers here. So right now what we have what we can see here as some of sales and some profit here. You can see here it says add a legend title right now. This is for some of sales and some of profit, but we don't see the title as required.

So we can collapse these options right now. Scroll up and find the legend. The legend here, I do require the sum of profit and some of sales this particular explanation here in the legend that what these lines represent. It do have the option right now to switch off the title.

We don't need the title anymore. So we can see the titles right here. If you think that these are too small to be seen, you can increase the one size here. And it in the scientific position of the legend to you can keep them at top right.

So at the end here, you can see that what these lines are for. You can also decide to keep them here to. So it all depends on you where you would like to keep the legends. Granging I'm going to keep them at top and center.

So these are the line charts where we have two lines in one single chart here. Of course, you want to go ahead and set the title here. You can always go to the title and change the title here to monthly sales and profit trend. Sales and profit.

Do remember that these drill two options will be available to the end user to whether they are editing rights or not. So it's one of the interactive features in Power BI. And next, the most interesting one here is the map. As you can see right now in Power BI, we do have multiple different type of maps.

This is our basic bubble map. Another is filled map with the shape map. This is an adsorb map. Yes, it is related to adsorb.

We have to go and you'll see in map from there. Another map is our TIS map that on all these maps are needed to be. This map here, simple map is available to everyone. This doesn't need to be activated here.

So first, let me show you how to activate the map visuals here and then we'll go ahead and create a map. I'll here everyone. We go to options and settings and options and settings we go to options. Options we have two types of settings global settings and the current file settings will do our global settings here.

The global settings go to security. In security scroll down, scroll down and you can check on, you can go ahead and check on RTA is for Power BI. You can also check on map and filled map visuals. We are simply activating them.

After activating them, Power BI might ask you to restart the whole software application. Remember that restarting means closing each and every instance of Power BI that you have opened up currently. After security, you have regional settings and then you have review features here. Now these preview features here might differ in your case and this particular version here.

As you can see, the first to check boxes shape map visuals, simply check on that piece. You can also go ahead and explore other options here. These are not related to the map for now. Simply check on shape map visual.

So we have done two settings here everyone. First setting was security and the second is preview features. So it's only maps. And then click on OK everyone.

It might ask you to restart it. Yes, you need to restart to activate the maps. So save your file and restart. Preity maps are already activated in mind so I will continue to show you the map visualization.

To create the map visualization, as usual click on the blank space here. This is the first map that we are creating. As you can see, it shows that it's a bubble map. I can see the bubbles here and the great out preview feature too.

To create a map here, we are going to use the geographical columns here like country in a state. When you're creating a map, look at the options that we are available here. Location, legend, latitude, longitude, bubble size and two tips. You don't need to have latitude and longitude here.

Since we have country and state, please remember that any data visualization tool. If you have the ISO standard spelling of country and state correct spellings as per ISO standard, then any data visualization software can go ahead and fetch the latitude and longitude and place them on the map visualizations. If you require to pinpoint a certain geographic location, which can be a pin code or maybe it is a particular district or a street area, then you might require the exact latitude to be a program here. For now, you will check on country and state.

When you check on country in a state, the bubble charges and look good. Why? Because by default, you can see the country is getting added into location and the state will be going to the legend. However, you want our state to be added below the country.

So, we will drag and drop the state below the country here. As usual, you can see the close of the legend from here. Now you can see we have got bubbles across here. Right?

We country is here and we do have the option of trail down. Once we trail down here, we will see few more bubbles across. So now, it is showing us individual states in each country. That's good for now.

So here bubble here, if you will scroll down, you will also find currently these bubbles are only shown in the position right now. If they scroll down here, we have few more options like legend. Then we have options here like bubble size. It means that we can use the bubble size here to see how much sales has happened there.

And as soon as a drag and drop the sales into the bubble size here, it is some of sales right now. And we can see the size of the bubble has changed and we can figure out the highest sales here is in a spotlight. Similarly, we have legend. In the legend here, if I will go ahead and bring the state again into the legend, you will find that each state is colored separately.

We can see the legend up here. Let's go ahead and format this map. To format this map here, everyone, we will go ahead and switch on the format options here. In the format options, we do have very less options to in the format visual settings here.

First is our legend which is not properly visible. So we can switch on the legend right now. The position is top left which is not properly visible. We can go ahead and keep them on the left side of the tag like this.

Now they are pretty much visible to us. We don't need the title right now. We know these are states. So we can switch on the title here.

We have... Now we have the whole map in front of us. We do have few map settings. In these map settings here, we have different styles of map.

This is our roadmap right now. We do have an area map which we are accustomed to. We have a dark themed map and we like themed map here. Please do remember that if you are using dark theme, your whole report has to be dark themed.

So we have a great roadmap. It's a simple roadmap here. By its color roadmap because it will zoom in, you can actually see the rolling screen. The status.

Next year is controls of the map. Controls of the map here, currently it is automatic zoom here. For example if I click on best here, it will show me only west region and it will automatically zoom. Now that particular part.

We can also add these zoom buttons out here. So you will have plus and minus zoom buttons here too. This is all in the maps. So currently what we have created is a bubble map available and we can see each bubble here where we have the size.

Now it depends on you. How would you like to keep your legend and add more colors to it? And as usual, okay, we want to go ahead and form a title here. So we can always go ahead and use form a picture and we can have the title painted here.

Use the form a picture to paint the title here. Of course, we can always go ahead to the title here. And what we are looking at here is the sales distribution by location. So let's give a proper title everyone.

It's a sales distribution by location. You might have observed that there is no option here to add data labels here. We do have category labels, category labels, those simply go ahead and switch on. They name on the state and the country.

If you have city and district name 2, it will add that to here. However, we cannot go ahead and show the labels out there. So I don't like these state labels always, okay? It crowds your map and it is not property visible.

And we will switch on the category labels right here. So everyone, these are Stackbar Chow, Multiple Line Chow and Bubble Bomb. Now let's go ahead and create a report out of these charts that we created so far. In this report here, we will also add few more objects.

And we will make our report interactive. Now in Power BI, there is a difference between a report and a dashboard. In general, what we call a dashboard is the collection of multiple charts and other objects, which are either interactive or static, but they should serve and solve a particular objective or a function. However, in Power BI, whenever we are working in Power BI Desktop, each of these pages that you open up, and when you have multiple charts on it, the score is an individual report.

When we will publish this into Power BI service, or you can call it online Power BI, currently we call it Microsoft Power BI, then there we create a dashboard. And that dashboard can create charts from multiple Power BI reports. Not only one data set from multiple data sources too. So, dashboard is a different part, what we are going to create here is an interactive report.

Now that we have all charts on individual report page, let's go ahead and copy page features here, within the pages too. The core page, we are going to design it as per the objective of analyzing our sales and profit for this particular region store. First, let's get a title to be report everyone, to give a title here, and you won't have, we will go ahead and click on text box. It text box here, I am going to simply type right now, that's an annual sales performance report, with annual sales performance report.

And we are keeping it for details. So, we already have three points. Now this is a text box, I am going to increase the size of the text box here, of course, the data that they have written here, it is not visible. So, you can control A or select as I have done right now.

I am going to change the font size here, I am going to keep it bold, let's keep it at the center. I am going to change the size of this three sales, three that I have written here, like this, and here we are. So, this is the annual sales performance report. What I am going to do here is showing you another way to create this.

I am going to select this whole thing, I am going to make it a little bit gray. Of course, wide and gray is not visible, so we go ahead and open the corner option for it, and then the corner option, the size and the style here, we are going to give it a background color. We are going to give it a darker background color here, and here we are, much better. We will give it a border to, and a shadow here.

So, this is going to be our title for the report. You can size and place the title. What is the title is here? You do have the options like pattern, what does that mean as how far it is from your D-bottles here?

If you want, you can go ahead and decrease or increase them as per your choice. Then the visual borders here, you can change the color of the border here. The corner is rather than a rectangle here, you can have the rounded corner rectangle. You can see it looks like this, here.

You see the rounded here, rounded corners here, it looks like this. So, right now, this is the title that we have given. After the given title, let's go ahead and get few charts. So, first I am going to go ahead and get the simple bar chart.

I am simply copying and pasting corner and keeping them at a certain pace. I am also going to get our line chart and the map here. As you can see right now, we are resizing it. Every chart is getting resized here.

So, as we are bringing all the charts together to create a certain report that can give us the performance for sales here. I am also going to bring our pie chart, pie chart and a doughnut chart. It does look very small and compact. However, it is because we are currently designing, it is zoomed out version here.

As in, we will resize it to a proper viewing capacity of your laptop screen and the general 16 by 9 size. It is going to be perfectly visible. So, we do have our all charts here. Let's go ahead and add a few more objects that are required in the reports.

Few other objects are first, let's go ahead and add a slicer for country. One of the sales distribution by region, by category and by location for each country. To bring all the slicer here, click outside on the... Here is the slicer everyone.

This is how the icon looks like. What is a slicer here? Slicer here is an interactive filter, which the end user can directly interact with. You can change the view of the whole report.

And this particular slicer by default will be connected to each and every chart here. So, I press select here for example Australia. You can see it zoomed in in the Australia here. I can see over the time here.

You can see the contribution of the category and region to. If you want to clear a dot, again go ahead and clear selections from here. I will do have an option. So, if I open up the form, and adding options here for slicer, we go to slicer settings.

We have vertical list, that's good. This is what we are looking for. In the selection, we can go ahead and switch on the select all button. Select all button, make it easier for the end user to understand what's going on here.

And if they want to go ahead and uncheck any selection here, we can simply go ahead and select all two. It gives them flexibility to understand how the slicer works. Now to the slicer here, I would like to keep my KPIs and the aggregate numbers on the display here. To do that, we have multi select multi-row cards.

So, again click outside here. I'm going to click on multi-row cards. Cards are the display cards here. In these cards, we can go ahead and display any numbers that there are people.

I'm going to show the cards here. I'm simply placing it in the available space here. It's like this card. As you can see here, we're in the format and the build.

It simply has one option to fill that is fields. In this fields here, let's go ahead and check on our numerical variables like we've got sales here, profit here and number of units sold. When you check on these, when we format here, we do have the option here to make it invisible. For example, we can go ahead and decide the font here, which kind of font you will be looking for, for values and the labels to.

So, I'm going to increase the font's time for values. Okay, we can go ahead and also decide the font's time to. These are category labels and these are the numbers here. It adds here.

Okay, you can go ahead and decide the background color for any visual card too. Now, there are multiple formatting options available for us. If you want to go ahead and get border to, these, okay, you can go ahead and get the border to. Next.

Okay, so now here are our multi-cards. Multi-cards, we can have our KPIs, a place like we can see our sales, total sales, total profit and these are the next two. This is multi-cards here. When you talk about objects on our board here, okay, now we have got a slicer and the multi-card here.

Now, we can also have an image. How to insert an image here? You can always go to the insert drop down here. You can see here, you can see image.

This is an image that we have here. Let's find another. Here, I'm using one image right now. Okay, I'll just go here.

Here for something else. As you can see, the image is right here. I'm going to keep it here. Now remember that this image can serve multiple purpose too.

You can add actions into it. You can add multiple formatting options too. So right now, I'm not giving any title to it. And in this our image is style.

Currently, the scaling is normal. Either we can fit it to the size here or we can ask it to fill whatever size that we create here. It all depends on us, that how we would like to go ahead and view this image. Add this and save this image here.

Right? It all depends on what kind of scaling you are looking for here. So here we have added an image as a logo everyone. I'm keeping the scaling as normal.

So if you're working with me here, congratulations. You have created a full interactive Power BI dashboard with bar charts, line charts, by charts, and mavisualization too. Now let's go ahead and decide the interactive part everyone. Here whenever you click on a chart here, you will find two extra tabs called a Format Data Syndrome.

Let's go to the Format here. So I've currently am selecting the bar chart here. I go to the Format. In the Format here, we have on the left and upper corner, we have edit interactions.

This editing interactions here decides that how each chart decides to behave with another object and charts available on this particular report. When we switch on edit interactions, you can find that this particular bar chart is currently filtering out the map. It is, we have three options here. Highlight, Filter, and Strong.

Meaning, now, so currently it is highlighting the donut chart, highlighting the pie chart here, filtering the line chart, and filtering the map. What does that mean? So let's see here, if I click on West, bar chart, you can see the line is getting filtered out. Your bubbles are changing.

However, look at your pie chart. Your pie chart currently has highlighted a certain area of certain slice. Of that particular West region. And within the West region here, it is trying to highlight within the donut that how much percentage is here.

So for West, it only highlights West as 30 percent. But I can change that. We would like that only filter, should work. So we go ahead and highlight filter, and highlight filter here.

We can go ahead and decide the interaction for individual charts too. So if I click on the pie chart here, I would like it to filter out the bar chart, and filter out the profit margin chart too. I click on the donut chart, I will make sure that it filters out the bar and the pie chart here. Similarly, we decide for the line chart here.

Okay, it is going to filter out each chart here. Mindy for everything is set on high. Same with the map here. We can select on map here.

You can ask it to go ahead and filter out each chart that is associated with it. If you want that no one should be able to click on the line chart and filter out anything else, then you can go ahead and select none. If you select none, then it will not be parted out here. Once you are done with the settings for individual charts, you can go ahead and switch up edit interactions here.

And remember to save your work. Now let's see how does it look like. This is our panel report every month. If I want to go ahead and see what's happening in Australia, I can click here, this slicer.

Okay, we can see the Australia here. Over the time, how was the sales, how was the profit there, what was the how these sales we have sold out clothing at 41%. And the highest crossing in the region has the invest here too. So if I click on vest within Australia, the West region, we can see the West here, we can see the South here.

Okay, we can see the North and East here too. In a similar manner, we can go ahead and check for another country too. And you can see how easily and smoothly the map moves. And we can go ahead and give multiple filters by using slicers and multiple charts too.

If you want to go ahead and give multiple filters, always remember, you can select on individual chart by holding on to control on your people. Just like this. So vest into clothing store, this is how the sales and the profit has been working. Australia if I want to go ahead and see the West and only the clothing, this is the trend that we see.

We can select only for UK, this is the trend that we see in UK and US too. So here, we are applying multiple filters too. So congratulations everyone. You've created a fully interactive Power Bay Dash port with multiple charts and interactions.

Remember, always choose the light visualization for your data. Avoid clutter and focus on insights. Use interactivity to make your reports engaging for the end user. Thank you very much everyone.

If you found this video helpful, please like, share and subscribe to our channel. See you in the next video with text measures. Thank you very much. In this session, we will start with certain exercises which we will perform in tableau in order to understand some basic concepts.

Now, in order to learn tableau, the basic first step is to import a sample data. So in our case, what we have done is we have imported a sample super store which is an Excel format, a sample super store.exe, which has three work sheets in it, orders, people and returns. So by importing this data into tableau first of all, we will create relationships between these sheets in order to identify who all have placed orders and how many people have returned the orders. We will do some analysis on the orders placed by certain set of people and order returned by certain set of people.

Now, as we have imported the sheet, we will make certain joints. So the first step is to drag the orders table, the orders sheet on the relationship canvas here. And you can see the data, sample data, the first 100 rows over here. Then, now we need to create an inner join with people's table between order and people.

So if you see, it has automatically detected the field names on which the inner join has to be created. So on the order side, you have region and on the right hand side, which is the people data, you have also a region. So both these columns are common and that's how we have made a join between orders and people data. So if I close this box and go and check the people's data, open.

So see the region and the person, these two columns from the people table have now been joined with the orders table. So it means that these are the orders in a particular region which have been placed by in this region. Now, let me show you the sample super stored Excel file. Now, this is the structure of the file.

You have a sample list of transactions, basically the orders which are placed by customers across multiple regions, south, west, of USA, south region, west region. Then you have a list of order IDs which have been returned. So basically the order ID in the returns sheet matches with those orders in the orders table. And then you have the people sheet in which you have region and a person associated with that region, the sales person associated with that region.

Okay, so basically when we are combining joining orders with people, we are joining that which orders belongs to which region and who's the sales person associated with it. So what we have done over here is we have made a inner join means all the orders should belong to particular region and that region is in the people's sheet. And then in the second step, now we will make a left join between returns and orders. Not in a join, we will make a left join between returns and orders and we will make a join using the order ID.

Okay, so just edit this, click on left and select order ID as the join column. Now what does left join means? Left join means is that consider all the orders from the orders table and only consider the orders from the returns table which have data means which are returned. Otherwise show null for the order IDs which are not returned.

So if you see, these are the two columns from the returns table and these are null because this is relevant to the order IDs which are not returned. Okay, which has been accepted by the customer, but these are the orders for which you see data in the return and order ID column. It means that these have been returned. Now with these joins in place, please save your book and now we have our relations created in the in the tabloon.

Now we are ready to create certain reports and extract certain KPIs using this relationship model. Now we will move to sheet 1 and first we will place state and person on the rows sheet. Okay, then I will go to my numbers and put the profit or the so per state per person how much profit I am making as a company. Okay, this is my goal to check.

Now, sought by highest to lowest. So California is giving me the maximum profit of 76,381 then New York, then Washington. So this is the sorted order in which I have listed my profit in descending order. Now I can also check what are the number of orders placed and check the distinct count.

So out of 120 out of the total orders of 127. Okay, so this is the number of total number of orders which have been returned for California is 127. It's 16, 29. So the sorted order is as per the revenue, as per the profit and this is the details of the orders which have been returned per state.

So if you see for connecticut for a cancest there are zero returns. So you can also extract data. Table to refresh is orders and identify new rows using order daily. So as and when new data is being added, you can refresh it.

Now say extract and now you can save this information. Profit by state and click save. So this is the extraction of this particular report which is possible in table. So this is the first exercise which we have completed for reviewing and analyzing the profit per state highest to lowest.

And within that per state what are the number of orders which have been returned by all the customers, the distinct count of order IDs which have been returned. Now let's start our second exercise on creating calculated fields in table. Now in this exercise we will be doing certain activities like we will be creating a set to show the states which have more than 100 customers. Then we will be creating a calculated field to show an average sales per customer.

Then we will create a calculated field to show the sales goals and then show emerging and developing states. So these are the four KPIs which we have to derive. Now the first thing we have our sample superstar data already imported and the relationships created inner join with people and left joined with returns. Now we have our sheet to in which we will create the states a list of states which has more than 100 customers.

So what we have to do is we have to click right click on the customer name and click create set. Okay. Now we have to give the name as states with 100 plus customers and then go to the condition tab select by field and then apply condition as count of customer name greater than equal to 100 and click. Okay.

Now we have this set created states with 100 plus customers. Now to determine average sales by customer we have to now create a calculated field. So go to the analysis and click on create calculate field. Okay.

Now name it as average sales per customer and now we will say average. We will use a... Okay. So we are saying that per customer we are using a level of definition function include which means that per customer what is my average sales right.

I've already used a function aggregated function called average. So we are saying per customer give me the total and then give me the average per customer. So we are going to click okay. Now create another calculated field you can also create from here and name it as sales goal.

Now in this we are going to type the formula if minimum states with 100 plus customers equal to true then some of sales into 1.3 else average sales per customer. So we are saying that if the customer belongs to the set of states with 100 plus customers then the sales target should be 1.3 times the actual sales as of today. Else it should be 100% of the average sales per customer. Now let's create another calculated field which we call as emerging or developing state.

If distinct count of customer name is greater than equal to 100 then the state is tagged as developing state. Else it is called as emerging state. So we have now three calculated fields average sales per customer emerging or developing state and sales goals. Now we will use this in our reporting.

So we will drag sales goal under the columns and then I will drop my state. So now this is the state wise sales goal depending whether the state has 100 plus customers or not then add your customer name. Make the measure as count distinct and make it as discrete. So if you see this we have the count of customers per state and the sales goal for that particular state.

And now I will put my sum of sales, the total sales which I want which is there per state. Now go to show me and select this particular chart, bullet graph. Now to bring sales goals to column right click on the sales axis and select swap preference line fields. Now from the left hand panel drag and drop emerging or developing state on the color panel.

So emerging state is the orange one and the developing state is the blue one. And save the sheet as developing and the emerging states. So if you see this it's an emerging state because the customer count is less than 100. Its sales goal is 5, 7, 3, 8, 4 but the actual sales is 1951.

So now this is a developing state its count is greater than equal to 100 and its sales goal and its sales is exactly the same it matches. So that's why you are saying the bar and the blue bar is ending exactly where the vertical bar is. So what we are trying to depict is that whether the state is going beyond its target sales goal or it's behind it and you can see that using this particular vertical bar like for example Michigan its sales goal is 71, 9, 52 but its actual sales is 76, 7, 2, 7, 0 average sales. So that's why it is the above its target and its a developing state because it has more than 100 customers.

So you can even sort by the count of the customers higher to lower. So all your developing state will group from at the top and the emerging states will group at the bottom or you can sort by the sales goal. So the orange bar is the sales goal or the blue bar so depending what sales goal is being derived for each state. Hello and welcome to this new session on tabloon.

Now in this session we will talk about how to prepare dashboards and how to interlink reports within the dashboard. So in order to start this session we will first create couple of reports and then include them in the dashboard and then link them together. So for this session as usual we are using the sample super store data set for our example. Now first we will create a report where we are going to show profit by region per region.

So first we will drag the region in the rows column and we will get all the regions and state. So we have all the states per region in our report now and then we will drag sales and profit. So now we have our sales and profit measures the column level. Now just also drag now the region to the color section.

So now we have each region colored the entire sales and profit per region is distinguished by the different colors Central East South and West. Now click on the colors. Now we want to show the labels using the marks card. So we want to show the region.

So we need to include the show the marks labels just a second. So enable the labels say show mark labels. So you have on the left this is the profit and this is the total sales. Now rename this sheet as region and state analysis report.

Now let's create another worksheet. Now in this sheet just drag the state on the marks card. Now automatically tablo will detect that you know you have dropped a particular state and we have the states of United States. So it has identified the state names and showed you the identifiers of the states on the map and automatically identified the latitude and longitude which are generated by tablo and given you the markers on each and every state.

Now drag the sales measure to the color panel. So now this is sales per state in the color scheme with the color scheme. Then now drag the profit to the size. So now each state you have the color the profit and the sales.

Now you can edit the colors and you can select a particular scheme of colors and say apply and okay. So now you are able to distinguish the colors on the state. Now after this just rename the sheet as profit by state report. Now create let's create another report.

Now in this report drag the subcategory to the column section and sales and profit measures in the rows. Now click on the right click on the sum profit pill and check dual access. Now click right click on the profit access and say synchronize access. Now select some sales from the card, mark card and change the notation as bar and for profit change the notation as line.

So now this is a fair display of subcategory wise sales and profit representation that these are the sales and what is the profit. Now go to the marks all marks and drag the category section as the tool tip. Okay so for each and every bar or line item you should now see the category also. Save your report and rename this now report as sales by and profit by subcategory report.

Now let's create a new dashboard. Now the reports which we have just now created first our dashboard size let's make it as automatic. Okay then let's show the dashboard title click click on the dashboard title. Now drag the reports which you have created profit by state sales and subcategory report and region and okay.

So you have all your three reports in a single dashboard now profit by state sales and profit by subcategory and region and state analysis report. Now we will link these reports so go to dashboard click on actions add a action called new filter. Select source sheet in the source sheet dashboard to only select region and state analysis report. And in the target sheet just deselect region and state analysis on the source sheet keep the run action on select and click okay.

Now whatever state you select over here that particular state will be used as a filter across both these reports. So it means in north Dakota you have all these categories subcategories being sold and their associated profit and on the map profit by state report you can see the north Dakota state being highlighted or only selected and the relevant profit and sales. Okay so here is the total profit and sales in the profit by state report and in their sales and profit by subcategory report you have the breakup of the profit and sales across the categories. Similarly you can select any other state and automatically the filters will get applied automatically see this marine main.

Okay so with this we cover our example of how to create multiple reports and then connect them or encapsulate them in a single dashboard for a single view across all these reports. We are going to take example of the Netflix database which we have and we will prepare certain reports in order to identify what kind of reports we can generate from such a data set. So currently on my screen what you can see is the tabloom the Netflix data sheets the data sources where you have the Netflix shows movies their associated duration what kind of shows or movies are there they're release here the associated rating description and a key which is the show ID. Now this is the unique identifier for each show in this Netflix title sheet and with this show ID all other sheets are related like you know who are the directors of the show in which country the show was released.

What is the cost of each show all that information is in this sheet and to which particular category basically the listed in category is being listed in this particular sheets. So what we are going to do is first we are going to import the sheet into tabloom. And then create relationship between them using the tabloom relationship canvas. So first our the primary transaction table the sheet in which all the information related to movies is there or shows is there is in Netflix titles and then we will drag sheet like Netflix cast titles cast now W has automatically identified the relationship between the two.

Between the show ID of titles and show ID of titles cast and it has made a joint. So if you double click this you can see this relationship cardinality and the related fees. Similarly I will drag relish titles category countries and directors. Now by virtue of this all the sheets have now been joined with Netflix titles and with this relationship ready we can start preparing our reports.

Now let's create a basic report where we can just glance the data like you know whatever we were seeing in the Excel. So how it looks in tabloom so you have all the types of movies then for example I drag the release here. Now first I do not want to consider it as a dimension so I just release here you know per category per type there is a release here. Then I will drop the listed in.

So now these are the categories of per year the details of the categories right and then you can drag the title and the associated rating. This is just a view of your data we can name it as shows listing report. Now let's try to create some report for some measures some numbers etc. So now let's check in which country how many movies or titles were released you know what is the count.

So first let's drag the country. So as soon as we drag the country feel it is identified that it has the geographical names and identified the latitude and longitude details. So tabloom internally does that automatically and it has identified the spots across the globe of the relevant country. Now let's drag the listed in on the color section.

Now what it is doing is it is showing in which country what different kind of category wise movies are or shows are being released like in Sri Lanka document is have been released in India action in adventure United States action in adventure like this. Now let's put account of the titles right. So if you see 247 action in adventure movies or shows have been released in United States. So this is one inference by this particular report you can identify.

So let's see this report as listed in by country. Now let's create another report. We will call it as the per year statistical report in this first I'll put the release years in the column. Now count of Netflix titles.

So this is the count of Netflix titles per year 2017 2016 14 and then count of Netflix titles in the countries. This is the second word chart. Now what I'll do is I'll combine it into one. So one report we are moving in the bar creating the bar and one in the line.

Now I just have to. So we will click on the count of Netflix titles by country right click market dual access. So now as soon as you click this both the charts have been combined and right click over here and say synchronize access. Okay.

Okay. So now if you can see see right in 2017 you had a 2303 Netflix releases across all categories and one one five nine titles right 1063 titles. In 2017 so this is a descending representation of the count of titles release per year across category and across titles. So let's call this as per year stats.

Now let's create another report number of shows per title. So or sorry per rating so we will drag the rating column and we will count of titles and. So. Any count of titles and unique count of show IDs.

Okay. One is bar and one is line. Okay. So this is a report which shows rating wise titles and the show IDs.

So in the tooltip you can see the distinct count of titles and show ID per rating. Okay. So let's call it shows per rating. Now let's create another sheet call it as shows by cast.

So in this what we're going to do is first drag the cast column on the rows section you have name of all the cast and then we drag the show ID on the column section and put a count D and sort it. Okay. You can remove the null cast and this is your sorted order and on the label section you can say show mark labels and you will see the count that unoppom carrier has done the maximum then on the shower of car own curry and us with being sure. So this is the details on the sorted order that who has done how many shows.

Then next is shows by director similar to shows by cast drag director into rows or differently if you want to prepare into columns and then count of show ID. Okay. Sort it and you can actually filter out the null director value and this is the account put the label. So you can see Jans Twitter has the maximum shows.

Okay. Then create another report shows by category. Now similarly drag the listed in in the rows and show ID count remove the null category and sort labels show mark labels. So international movies are the highest category.

Grammas the next comedy international TV shows this way you have your category. Now let's create a dashboard in which we want to bring combined all these reports and take a common view. So first let's drag listed in by country then shows by director also please let's set the size as automatic. Then let's drag shows by category and shows by cast now these four reports are on a single dashboard we will link them to each other.

So go to worksheet actions add action filter select dashboard one only select shows by category here. And in target dashboard one except shows by category keep everything else and in the source she just select click select click. Okay. Now whatever category you will select over here that related category data will automatically be shown in other reports like see international movies across the globe across countries.

Directors of only international movies who has done the maximum johnny toe and shows by cast right that who has done the maximum international movies or dramas or comedies. See paris travel has the maximum number of comedies and then if you see the comedy movies you know these are the count of comedy movies release across the countries and the who is the director. Another very interesting report which you can prepare is that for example you want to check in which country maximum duration of your. Maximum duration of movies have been released so.

First let's create a measure. Okay. If you see maximum duration of the movies or the entire Netflix content is maximum United States then India these many minutes next is United Kingdom and you can also change the colors. Whatever you feel is as per your standards or as per the convention you can change the color combination.

So there are multiple ways you can generate reports and hope you have understood how you can leverage such a data to create your report. And now if you're not aspiring business owners then try giving a short to simply launch post-charge your program and business analytics from her university in collaboration with IBM the course link in the description and comment should take you to the program being offered. Today we are going to talk about power BI what are its features what are the basic advantages of using a visualization to like power BI. And we will talk about how to install power BI and other features it provides and the basic setup.

So let's discuss what's in it for us today. Now we will first talk about why power BI you know why it's a popular tool and what problem it solves what is power BI. And what are the primary features of power BI which you can use in your day to day data analytics visualizations creating fancy reports creating meaningful intelligent reports for your organization for your personal use for crunching numbers for generating reports real time etc. Now the most popular tool for power BI the power BI desktop I'll show you certain aspects of power BI desktop and then I'll show you the steps how to install power BI desktop on your machine.

And then definitely power BI desktop is a free tool provided by Microsoft but then you can also subscribe for an enterprise version which is primarily used by enterprises for publishing their data. So we'll see the difference and then overview of dashboards which can be created you know what kind of dashboards can be created in power BI. So this is the agenda for us today. Now why power BI so generally you know visualization tools reporting tools are required in order to create and prepare and analyze.

Meaningful data it could be a data for an organization it could be a social media platform data it could be a data from IoT devices but something which needs to be analyzed and some intelligent inferences and data mining has to be done on top of it. Now imagine there are today we are in a world where terabytes of data and information is getting generated on an instant tenious places on minute by minute basis. So it becomes very essential to turn out something meaningful something intelligent out of it in the market there are lot of other tools where which are available like clinics, alt tricks, tabloos and power BI. So power BI is a Microsoft product which is one of the most popular products and it comes as a free to download product Microsoft power BI desktop which is available and I'll show you couple of ways how you can install it on your machine.

But why power BI is popular is because it provides a lot of out of the box features drag and talk features which we will talk about in our subsequent sessions and you know classes. But today's session is primarily focused on giving you guys an introduction on what is the purpose of power BI and what all problems it solve in the real world. So power BI allows you to view analyze and visualize huge quantities of data and the data could be any format excel CSV text or it could be a direct connection to a database like SQL, my SQL Azure or a cool anyone IBM DB do so it supports n number of you know data types or data sets and it's very powerful in terms of data connectivity. So it uses powerful compression algorithms to import and cache the data within the dot pdi x file.

So it's as convenient as a simple software if suppose you import a data and then you prepare a report and then you can easily share the reports with your peers or someone who is co developing with you either through power BI cloud services or even you can share the pbi x file in an email or through any other means and you can share the data set with the concern and they can then work on the report independently. So there are different ways there is no kind of a limitation for you know working on power BI there are multiple ways and it is very fast it is the most fast tool to work with excel because definitely excel is also a Microsoft technology so it works very fast on excel based data and gives you numbers and reporting at a very high speed. So now once you have imported the data power BI allows you to model the data allows you to work intelligently on the data it allows you to model data in a way that if you are importing data from multiple excel sheets importing data from multiple tables you can easily create a relationship between those tables or data sets in power BI and then create visually appealing reports meaningful reports as I've been in the past. As I've been emphasizing and make sense out of the data no data in silos is of any use data in silo means a single worksheet or a single data set will not turn out any meaningful information unt and unless you basically join it club it merge it union it append it with some other data sets because a single data set will never be able to hold that much of it.

So it is a very important amount of information which is generally required for a you know important report. So it has easy drag and drop functionality with features that allow you to copy all formatting across similar visualization. So just like in Microsoft excel we use format painter to copy the format of one cell to another similar features very very similar to excel products for Microsoft product. So I did that if you have applied a particular thing on a report you can easily replicate that on another any other report the font the header size background color you don't need to do it again and again.

So there's lot of reusable features which are also available. Now as I said excel is a Microsoft product power b i's a Microsoft product so they have inter compatibility you can publish data from excel to power b i now with the latest developments and enhancements as of today excel has also plugged in a new feature called power pivot which I'll show you later down the line. But that also allows you to do a quick analysis not you can't create of course complex reports or fancy reports like power b i but power pivot allows you to create you know quick measures quick functions quick calculations on your data quickly only in excel. So it's an excel plugin but whereas you know you can power b i is also compatible with excel so when you create a report in power b i it gives you in build feature to export your power b i report into excel format directly you don't need to do any programming for it also.

You can easily publish when you publish your power b i reports it allows you to give some inbuilt intelligence of analyzing your reports in excel and it gives you all those all those features of exporting your power b i reports into excel which is not available in any other tool or otherwise those tools have to create plugins create add in the probably they might charge for it but power b i comes with lot of out of the box features which are. Very very helpful for analyzing data in excel and vice versa azure cloud now azure itself again is a Microsoft cloud or text act so using power b i with azure allows you to analyze and share large volumes of data so azure basically azure database or azure cloud servers are meant to hold huge amount of data and power b i allows you to have seamless connection. You can easily collect to azure data lake you can reduce the time it takes to get insights and increase collaboration between business analyst data engineers and data scientists so azure data lake becomes the central focal point where all your analysis engineers can keep working on on the centralized piece of data and turn out the reports data scientist primarily job is to keep the data in a structured way optimize way. Optimize the input output operations disk operations and memory utilization so that the reports also get turned out in a faster manner so every you know every person has their own role in order to give a quick refreshable report quick rendered report any report which is taking huge amount of time to get rendered will not eventually be used by the business users because then it does not solve the purpose the report should be fast report should have.

You know appropriate filters slices and dices you should be able to you know create the reports or dynamically or you should be able to analyze visualize the data dynamically so all those visualization features are available in power b i and it works seamlessly either it is small data or huge data it allows that you to work on those kind of data you know seamless fashion. So this is just a very quick example of how a typical dashboard looks like dashboard is nothing but you know you have clubbed couple of multiple reports on a single page and you know if you change a filter a single filter on the page all the reports will honor that filter and the numbers will change accordingly. So if you see this in this example there is a filter or a drop down of product ID product name, employee name or supervisor or a date range so whatever date range or filter you will apply all the reports on this dashboard will get changed based on the filter you have selected. So power b i allows you to get insights from data and turn insights into action to take data driven business decision and that is the ultimate goal of any visualization tool that is the purpose for which visualization tools are bought and purchased by the organizations and data is fed into them.

Now power b i fetches data from factory sensors social media sources to get access to real time analytics so that you are always ready to make timely business decisions. So basically there is a feature of live connection or cut off data connection so either you can work on data which is deciding on a machine and you can just work on the cut off data like for example there's a data which is available for sales 2017 2018. And you're just working on a historical data it's a cut off data or it could be possible that you want to be connected live to a real time IOT based sensor based data or social media data like Twitter Facebook feeds or you know you're connected to live Google worksheets that is also possible you just need to publish your Google sheet for a public domain and bet that you are into power b i and then whoever updates that Google sheet. Automatically the power b i report will also start honoring and consuming the new data which is added in the Google sheet so all those kind of real time streaming analytics is also possible and that is one big feature and very important feature of power b i which is widely used and has a very huge you know market acceptance and market utilization.

Now what is power b i power b i is a business analytic service provided by Microsoft that lets you visualize your data and share inside right so earlier you know power of Microsoft used to have a technology called s s a s now they have replaced actually s s s and s s are is with power b i so basically you can use power b i on the data which is the most important thing. So you can create these fancy meaningful visualizations like for example there's a geographical map if you are importing data for a country or a continent or a region power b i will automatically detect that it's a geographical information in the world. So you can give you a map with latitude longative information and you just need to plot your numbers on the map either you can use bubbles or either you can use trying or whatever data structure you want to use but all the mapping will be available geographically then you can create pie charts which is shown in this visualization you can create three maps you can create cards where you know you can highlight the most important numbers like sales total sales. So you can create a lot of sales of your company across all the regions or the growth chart or the month on month you know sales of your organization or number of total number of products or units sold so whatever is important and to be highlighted for the management to take any meaningful decision or any insights you want to share power b i visualization tool the power b i visualization chart allows you to drag and drop and create a lot of things.

So what are the features of power b i so power b i desktop is something a standalone tool which you need to install on your machine it allows you to build reports by accessing data easily you do not need advance report designing or query skills to build a report though yes it is beneficial that if you know some SQL programming analytics programming or you are aware of advanced features of any analytical tool that might help you but that's not a showstopper you can easily build reports in quick turnaround time without needing any technical background you just need to have some analytical mindset and you can create savvy visualization and you know analytical reports. Stream analytics as I mentioned you can create a live connection with any kind of data it could be IOT it could be media social media it could be Google dogs it could be you know any other kind of you know live connection it could be a live database connection itself so any insertions or auditions or deletions happening will automatically reflect in your report. Yes multiple data sources and that has to be the primary criteria for any tool to be popular if any visualization tool is limited to certain data sets then you know it will not be highly acceptable in the market. And custom visualizations right so as I showed you certain examples in the past in the previous presentation that features very important because someone might want to look the KPIs look at the KPIs from a different perspective some management might want to look at the KPIs from a different perspective so you need to you need to have that capability to create different visualization from the same data set now let's take a look at the data set.

So that how to install power BI desktop on your machine so basically what you need to do is. You need to go to this URL power BI dot Microsoft dot com in us desktop okay and you need to just enter this now you can download it for free so just click over here and it will open Microsoft store so basically now what Microsoft have done in the latest operating system is that when you're trying to download you can actually directly go to the Microsoft store and search for power BI. So let's wait for a couple of seconds right here so power BI desktop in Microsoft store for me it's already installed so it's asking me to open it I'll open it in a while but for you for anyone who is not installed he will see the button up install over here. And it will automatically install in your machine and then you can easily go and open power BI desktop now if I click open over here.

Now this is the UI of the power BI desktop I'm not going to go right now in creating reports right away we will talk about that in a subsequent session with sample data sets and we will cover the features of power BI desktop one by one but this is what it is this is the whole tool of power BI which is having the visualization pain all the different visualizations are. You know can be created from this pain then this is the pain which allows you to select the data data fields then there is a report view data view and relationship view the data model view where multiple relationships you can create you can view the data in the grid of the tables which you will create and the reports so you can create multiple reports on multiple pages you can keep adding pages either you can. Drag create multiple reports on a single page and it will become a dashboard or you can create separate independent reports on the single page. And these are the menu options which we will talk about how you can change color scheme you can do data modeling you can create new reports and you can also transform data which is the biggest feature extract transform and load the data apply different logic.

Changing data types massaging the information creating new joins upending the data you know adding new columns etc etc we that is what you can do in transform data so this itself is a whole different world it's a dedicated topic we will talk about that in a subsequent sessions so what's in it for us today we will be learning how to connect to data different data types data files like. Excel PDF then what are the different data importing modes and then I will also show you practically different sets how to import them in power via and use it for your visualization purpose now what are the steps to connect to data so now we will go directly into power via and try to import one by one few most commonly and popularly used data sets which are most commonly used. In a day to day activity rest of course there are power BI supports n number of data sources but we will do something practical on the most popular ones so let's let's open our power BI. Now this is my power BI and first I want to show you that how can I import data directly from a web page and import the data now it is asking for a URL in order to import data so what I have done is I have created a Google Excel sheet with simple data with rows and columns and what I have done is I have shared this story with you.

I have shared this story with you and I will show you the web page and I will show you the web page and I will show you the web page. Now I will show you the web page you are talking about in this video and I will show you the web page. Now I will show you the web page and I will show you the web page and I will show you the web page. You need to wait for a while while it is reading.

Okay, now it has read one of the HTML tables so I will select this one. Now you can see it has, it is showing me a preview of the table which is there on my Google sheet right. It has 11 rows so it has all showed all the 11 rows. So now I can go and transform this data because I can see my headers are there starting from the second row.

So there is an opportunity for me to transform the data so I will go and transform it so that it looks clean. So first is I need to remove the first row which is the null row, remove the top rows. And then I need to use the first row now as a header. So you just click this option, use first row as headers.

That's it. So now if you see my row ID, order ID, order date, shift date, all my data is now ready. So I can say close and apply. Click apply changes.

Now this is an example of web data import. You can go and preview your data right. Now the biggest advantage of this data connection is that it's a live data. So for example, I insert another row.

So I have some exchange some basic stuff and I, it's auto saved, control S. Now I will go to my tab loop and I will refresh. Now you can see as I refreshed my power query data, I click refresh all and I got my new row which is there in the live data. I got that fetched from my, okay.

I got that row, the row ID number 12. So I have to say close and apply. Now you can see the new row, the row number 12 is now available in my new data set, in the data set because it's a live connection. It's a live connection with the web based Google sheet, okay.

So this is one important way in which you can import data. Now let's try to import data from a text file. Now I have already prepared a text file called subcategories.txt. Now let me just open it in a load pad.

Now it's a very plain simple file, tabs separate file in which you have products subcategory, ID subcategory, name and product category key. So basically to which product category this particular sub product belongs to, right. So what I'm going to do is I'm going to go back to my get data option and I'm going to select text slash CSV option and I'm going to select option, more products subcategories.txt. So now Power BI has identified that it's a tab, the limited file, it has recognized the headers, etc.

and I can now directly load this file. So now once the data is imported in Power BI, it is like relevant to me. It's a composite data import I'm doing, right. So in my presentation, when I'm talking about importing data, there are different importing modes, right.

Import data import can happen through different ways, okay. So here is the data query mode in which I create a live connection to the database which I'll also show you using my SQL and MS SQL server and also you can do a composite mode in which you can have data imported from Excel plus you can have direct query modes. So you can have multiple modes to connect and create a composite data model and that's what we are doing right now in our practical. So what we are doing over here is one we have imported data from the web, second we have imported data from a text table.

Now after doing text, now our next task is to import from CSV. Let's try another one. So now I have imported product subcategory, now I'll import a CSV file. So again, I'll choose the option text last CSV and now in this CSV file, let me open this CSV file and show you what in it, is it.

So this is a list of all my products, product key, products subcategory, key products stock keeping unit, etc. A simple CSV file and I'm going to import that. Okay, so now it is identified the delimiter is comma rather than a tab and it has already recognized the headers correctly, so I loaded. Okay, so now my products are there, products subcategories are there.

For product categories now, what I have done is I have created a Excel mode now. So now Excel, I'm using to import my product category. So now I have to click on the option of import data from Excel and I'll say product categories. Like the sheet load and now so my products product categories, products subcategories dope with different data storage types, but still now the data is imported into power BI.

It is a composite data module. Now another very important data type which you can import is the PDF also, right? So what I have done is I have created a PDF called customers. My customer's data is lying in a PDF.

So what I've done is I've created a PDF which has data for some columns are there like you know customer key prefix, personally last name, birthday, Marital status, gender, email address, annual income, total children, etc, etc. So this is the data set which I have created in PDF. So what I'm going to do is I'm going to select PDF now and import customers.pdf and see it has recognized my table on page one which I'm going to load. Okay.

You can rename this as PDF. So basically these are the different type of data types. We have imported PDF, Excel, text, CSV and web page. Now let's take a look at another interesting data set which you want to import is the MySQL server data set.

So what I've done is I've already installed MySQL server on my local instance and there's already a schema of SQL like tutorial over there and I have certain tables already prepared over there like department, employee, etc. So my goal is now to import this data or create a live connection with this data set. Now in order to import my SQL database connection in Power BI, you need to first download a connector, MySQL Power BI connector. So you need to go to this link and then click on download and install the MySQL connector based on the operating system you have.

You click on download and install it. After you have done this, go back to Power BI and then give the IP address of the database in my case it's there in this local machine and the schema which I want to import is SQL Live Tutorial. So I'll give the name, click connect. Now it's connected.

So now it is asking you which particular tables you want to create a connection with. I'm choosing department and employee and I'm just loading it. Okay. So now this is the exact data which is there in the employee and department in MySQL.

Okay. So this is one example of how to create connectivity between Power BI and MySQL. Now I want to do the same thing using SQL Server, Microsoft SQL Server. So I have also installed Microsoft SQL Server on my machine and I have used the SQL Express.

So this is the name of my server. So which I'll copy the server name and go to get data, select SQL Server. And for now database is optional, I can say direct query, click okay. Okay.

Now it is showing me what all tables I can import. So in my SQL Server tutorial, in my SQL Server, I have I have these three tables, customers, employee tuition, Olympic events. So I can use probably the customers one which is. Now you can see this is the data, the customer's data which is lying in my SQL Server.

Okay. So I can preview it and load it. So now you can you can preview the data in Power BI. This is the data.

So I can rename is customer's strong MSSQL. And this is from mySQL and okay. So now this is not the only data sets you can import. Now if you take a look at the options which Power BI gave of what different type and variations of data, it can it has compatibility to import from.

Okay. So we can just take a look at the categorization on the left hand side first. There are five ways like Excel text XML. JSON is also possible.

You can even need directly import entire folder and within the folder whatever data types of files are there. It will detect it PDF, Paa key or even shape point folder which is Excel for Microsoft technology. Then different kind of databases SQL Server and my SQL we just saw but it's not only limited to this. You can connect to Microsoft access SSAS Oracle database IBMDB2 Postgres, Cybase, Terra data and then SAP databases Amazon Redshift, Impala, Vertica, Snowflake and N number of databases which are there in the market today Amazon etc.

Then it also allows you to connect with its own power platforms, Power BI platform, data mart, Power BI data flows, data words etc. Azure, there are different kind of storage mechanisms in Azure and Azure itself is a Microsoft technology. So it has a compatibility of it a lot of Azure based data shortages like Azure SQL database, Blob storage, Azure data breaks, Azure HD Insights Park. So if you have those kind of services running on your Azure cloud services you can even import them over here.

Now online services like you know you have ERPs running or some data which is shared on the internet if you want to import it that is also possible through certain products. Dynamics 365 Microsoft Exchange Online Sales Force, Google Analytics, Ado Analytics, GitHub, LinkedIn Sales if you want to do some analysis of some social networking you know feeds that also you can import. Then other miscellaneous are also their web based high R script, Python script which is something to import data from Google sheets like Vishno or one example in our video right now. So there are multiple options available.

Now once you have imported the data which is relevant to you in our subsequent sessions we will see how to create relationships but just giving you a glimpse that whatever data you are importing power BI auto detect certain relationships and it will create for you but then you can go and manually also change. So this is the composite data model which is getting created in the backend while you are importing the data you can easily go and manage these relationships either keep the masses you can delete and create new ones manually so there is no limitation in that. So this is what we have witnessed we have imported data from different files types data types and then you know we have tried events it is imported into power BI then there is no limitation of how you use it you can create visualizations across different data sets and then create your standard reports. So this is the example of importing data from web importing data from a database from a PDF and then once you have data you can shape and combine data you can basically do whatever transformation you want to do you want to make joins merge the data.

So for example if we go back to our power BI and if I go back to my transform data section now as I have now different data sets available with me I can do any kind of you know operation transformation on the data right. So like I showed you I upgraded the header row because one of the imported data was not showing the header correctly or this column like this exact one column is extra I can remove the column right all those transformations whatever I do in the backend gets captured in the applied step section right. This is the customer data you can create you can merge it you can append it you know with other data sets right looks for example I want to create a merge data set of my categories and subcategory so I can say merge selectors to data sets and say merge queries as new and I can select product categories and product subcategories select product category key on both sides and then they do a left auto lens whatever product categories are there I'll get the subcategories associated with it and I'll create a new table which will have now I have the table which has the category and a subcategory and subcategory in one table itself so I can rename it now to as category subcategory table it's a it's a merge basically it's a joint between category and subcategory and now I have a common table right and I can close and apply so imagine I have created a new table which is imported created from one data set is which is excel page and another data set which is text base see this category subcategory table so now I can use it the way I want in my visualization reports so that's what the presentation says right that once you have the imported data you can shape you can combine you can adjust you can do whatever transformation you want to do and create your visualization okay so what topics we are going to cover today we are going to talk about different types of data modeling and the most important part and aspect of data modeling is the cardinality the cardinality which you basically decide after reviewing the nature of data and after we imported it what kind of cardinality you have to basically highlight right and there are different type of cardinality which you might have heard earlier also if you are from PLCQ background like one is to one one is to many etc we will we will talk about that now what are the different types of data modeling now dimensional data modeling is one of the most popular and most widely used modeling in dimensional data modeling you have master data like for example customer data date store data product data so these are like you know less frequently changing data sets so there is an organization right and you have set of customers the email ID phone numbers etc that will change less frequently as compared to the sales transactions because transactions are happening every day every minute so sales is a more fast changing data set in dimensional modeling which is in the terminology of data is also called as a fact and customers store product which are like more of static data and less changeable data is sometimes called a dimension so this is a typical dimensional data model which is typically used sometimes right and then there is another model which is relational model this is a typical model which we have been using in data based design like you know primary key foreign key relationships so for example you have a customer who has purchased a product so probably he might have the customer might have the details of the product which he has purchased and you will make a join between customer and product table and even you can make a join between product or product type or customer or product type customer table will also have a key to the product type so this is less conducive for reporting but it is more of a transactional relational model but of course this is also feasible but from the power BI perspective when we talk about reporting and visualization this is the most extensively used dimensional data model and this is what we are going to see in our example now so what I am going to do is I am going to show you certain data sets first we will prepare and create certain of our data sets and then we will import in our sample power BI file and then slowly slowly we will create the relationships now one important thing which you need to understand that in power BI if you go to power BI there is an option that that power BI auto detect new relationships after data is loaded and import relations from the data source on first load so for example if you are importing the data from a database where you have already defined the primary keys and the foreign key relationships so that is the first option which power BI will auto detect and secondly if suppose you are importing two different kind of data sets one in the excel one is CSV and if power BI detects a common column key columns it will auto detect a relationship which you can go and later change modify manage in your relationship menu manage relationship menu in power BI which I am going to show you okay so if I open a power BI and this is where the option lies go to file go to options and setting options data load and these are the two options which are by default check you can uncheck it and auto and manually prepare relationships there is no limitation to that but if you keep it checked then power BI will towards job to detect the relationships okay now coming to the next important factor cardinality now before I start playing around with my data and start showing you certain relationships it's very important to understand these four types of cardinalities one is many to one right so basically many to one means that many orders contain data of one customer so per order one customer is there so from customer to order or product or delivery address it's a one to many relationship and from the other side from order to customer perspective it's a many to one relationship okay second other cardinality is one is to one one is to one relationship is only applicable when you are saying it's an extension of the current table so for example in one table you have employee details and you are extending the details of the employee in another table like employee address employee ID so that is like one is to one there's no multiple records of a single employee in the address table only one employee exists right now one is to many as I said is the reverse side of many to one is a in customer table only one customer record exists per customer and one customer can place many orders for multiple products and can also have multiple delivery addresses so that way this is a typical one is to many relationship we will be seeing this example also in our sample data set and last is the many to many relationship now many to many is a very typical example so which I'm going to show you practically and in our case we will see that like for example you have placed an order for a particular product you know but there are multiple fulfilments which has happened so suppose you made order for 10 products but at the back end when the company is fulfilling it is first fulfilling the first two products then the rest three so basically you the fulfilment is happening in batches so one order ID might have a multiple fulfilment for the same order ID so there will be a multiple many to many relationship which I'll show you practically so now with this background let's start importing our data now the first important thing which we need to import is the master data so first I'll import all my master dimensions which are which I'm going to you know use in my example so first is the customers table customers data so this is the customer details the customer key prefix first name last name birth date marital status and gender some redundant columns are also a present but we'll remove it so my customer data is loaded now today's session is all about this section of modeling so we will keep our focus over here okay now some columns probably some blank columns are there I can select them and say delete from model yes okay so now this is my customers data with the relevant columns and the key per customer customer key now there's no relationship in this model right now right because only single table is there and the associate data is only importing now let me also import my another important master table is the products select the product data product key product subcategory product SKU product name modeling product description color size so just see all the relevant information only specific to the product is available so I'll import it okay now see there's no relationship between product and customers directly because until unless a customer makes an order places an order for a particular product there is no join right so now between these two tables the most important now another table which will now make sense is the sales order table sales table now I am assuming that power BI have auto detected the relationship now you can see that because I've already ticked that check box now let's see what power BI what relations power BI has auto detected let's first check the relation between customer and sales I'll double click this join now what it has done is it has created a join of many to one between sales and customer so what does that mean is that one customer has can place many orders right and that is that it has detected by the quality of the data and the data sampling which power BI has done you can also reverse this relationship here I can select customers and I can select sales now it has become one to many so that you can also do manually so that is what I said whatever power BI is detected it is up to the description of power BI internal configuration and algorithm but you can go and change so this is now you can this is by default active so we want to keep it active one customer many sales orders cross filter direction means that only from customers to sales is the filter applicable not reverse I'll come to this with my another example but first let's change the relationship so one is too many means from one customer and many sales orders similarly let's see what has happened at the product side of the relationship similarly power BI many sales orders for one product you can for simplicity sake you can say products sales product key is the join now just focus one more thing please also see the column on which the join is is the grade column grade out column product key is also here and product key is also there and it is what we wanted so one is too many relationship from product to sales table and active now looks fine this is something which is looking logical and probably now we can proceed further to create a report now let me explain the cross filtering within example now for example I want to check in a report that what is the count of products which which a particular customer has ordered okay so what I'll do is I'll select the product count of product name now if you see and for each customer in front of each customer name the count is coming as 293 293 it is repeating repetitive because because there is a one way filter direction filter between customers and sales and sales and products right so this join is single-sided it means that from customer to product you can't find a relationship because it's a single-side cross filter right what does us if I change it to both it means that it is equal to a join between product and sales and every product detail now is appended to the sales table so if I want to make you visualize you need to go here I'll first open my sales table we can also open it here let's make click this okay now if I click okay you can see the single arrows change to double arrow it means that's it's a both side filter so when you say a both side filter it means that implicitly within power BI you can imagine that all the product columns now will get appended because of both ways filter you have applied and if you go to your report now see the change of the numbers now for t20 so the total count of products across all my customers come out to be 293 now the report looks correct if I change the relationship from back to single between product and sales then you can't make a join between customers and product basically you can't derive the product count from the product table see this if you have to live with it then you would have to go to the sales table get the product key and get the value of count of product key but that is not correct okay so if you want a report in which you want the count of product name and even if you want a count of distinct product name so this will not come correctly you would have to go and change the direction of the filter which is from single to both so this is a typical example they where you want to use a two directional filter now let's proceed further can import other data set in order to show you another example now I want to show you an example of one is to one so I have another table which is called customer details so the key in this table is again customer key but only email address annually become totally children education level etc other details of the customer is there so I'm loading the customer details now you see it has auto detected of one is to one relationship but what is the meaning of one is to one means one customer key only has one entry in customer details there is no multiple entry so if you click this button it's a one is to one and the cross filter can be both or single doesn't matter because one customer will have only one value you can make this is active okay and if you go to the customer report table you can now easily associate a email address with the first name you will get one is to one record so now you can see that with one is to one relationship with the first name I have associated the email ID and for each email ID there is a associated first name with that so this is an example of one is to one relationship so in this example what we have explained is that for each customer there is an associated customer detail right so you have the first name email address education level home or occupation and total children count so in this report what we have done is if you click over here so the first name and the email address okay so there's a one is to one relationship and then and if you drag customer key report takes time to render and even if you can so this is the reporting output you have the customer key first name associated email address and the count of product names which the customer has ordered now this is an example of one is to one now I want to show you an example of many too many now for that I'll import my full filament dataset okay now in my fulfillment dataset there is a column for order number so basically what I'll do is I'll drag order number from here to here okay so now what has a power we are detected I do one thing I'll select sales over here fulfillment over here and order number to odd number okay so it's a many too many relationships so it means that per order I have created multiple batches to fulfill that optical order now many too many relationships is a definitely a candidate for both ways cross filter detection direction but you can you can check that but definitely power BI shows a warning that this relationship has cardinality to many too many and this should only be used if it is expected that neither column contains unique values okay so we know that fact that's why we are accepting this relationship as many too many because we know there are multiple order numbers over here in the sales table which are mapped to the multiple order numbers in the fulfillment table we'll click okay now you want to keep the direction as both ways or one direction that is up to you the way you want to map the report so I can double click over here and you can even click so now you can select from which way single filter you want from fulfillment to sales or sales of fulfillment I'll prefer sales of fulfillment I'll click okay okay now we have our all our different kind of relationships over here which we have tried to shortlist one too many many to one one to one which is this example and many too many now if I show you further relationships which you can keep on hiding like for example I have the example of territories now in which particular territory the sales was done so I can map it over here okay so now it's a typical one is too many relationship because territory is my master table where I have a static list of continent country region and it is mapped to the territories which are in which my orders have been placed so it's a typical one is too many so that way you know you can keep on adding data then you have details of returns now this is another transactional table which is about the orders which have been returned rather than being you know returned by the customers so you have a product key and so automatically power BI has detected a relationship between the product key and the product table right and even if you can join the territory key in which territory the return has happened right so mostly the most common relationship which you will observe is the one is too many because as I told earlier the most common relational model is the dimensional model the static data the slow changing dimensions the SCDs are the master tables and the most frequent changing are the fact tables so if I talk about a typical dimensional model the fulfillment table sales table and the territory stable sorry the fulfillment table sales table and my returns table are the fact tables of my data model now so far what we have done as per our last session is that we did data modeling on the different data sets which we had imported in power BI like products sales data returns fulfillment customer details and customer master data calendar details etc so in the last session we prepared a data model and established the relationships between these different data sets like one is too one one is too many many to one one is too one etc and we saw the examples now once our relational model is prepared our data model is prepared now our next activity is to create certain additional columns which we want to derive basis the data which we have imported so for example I'll start with my product data set now in my product data set I want to introduce a column which basically categorizes that if any product which has a color you know red black or gray I am going to tag it as a colored product rest I'm going to say not a colored product right so all these are like example of byte type product SKUs so for that now in order to introduce a new column you just need to do what you need to select the table in the data grade go to the table tools and say new column okay so column will get upended to the right most part and you will start seeing a a formula section typical to like you get in your excel now I'm going to say that the name of my column is going to be byte type color okay and I'm just creating a if condition if product color is equal to black okay or or if it is equal to red or if it is equal to gray then say yes it's a colored product L say no okay so now you can see basis the product color red and black they are saying byte type color yes blue is no multi is no etc etc so this is a classic example of an if and else condition conditional column okay so you can create such columns now second column custom column which I want to create is I'm going to call as discount now basis the pricing of my products I want to associate certain discounts which I am ready to give to my customers basis the product category like what is the pricing of the category again I'm going to use make use of if else but in a next straight way so if I'm seeing if my product price is less than 100 then I will give 0% of 0% of discount so 0 into product price just to keep it consistent now I'm seeing else if less than 100 then 0 else I'll check again that if the price is less than 500 then I'm ready to give 1% discount on the product price else I'll move further so like this I have created a formula so what I'm saying is if product price is less than 100 gives 0% if it is less than 500 then give 1% less than 2000 then 1.5% less than 3000 then 2% and otherwise else less than 3000 if it's 2% else 3% right now after this column is created now you can check right so this see the product price for this particular product it is less than 100 so that's why there is no discount it is between 100 to 200 then this has been given a 1% discount so like this all the discount column is now calculated now this column is available just like a regular column in my product table now after this I'll go to my sales table now in sales table I want to identify create a column called as cost there is no product cost column over here so that will be derived so let's create a column called as cost and it is derived by order quantity into now the cost of the product is in the product table and I know I've already created a relationship between product and sales table so I just need to select the product cost column now only keyword which I have to use in power B.I. is the related keyword so this will pick up the relation and now for this particular sale order the cost has already been derived so this order number this is the cost for which the product is the costing of the product for this particular order okay okay now I'm going to create another conditional column over here called as order status I'm saying if any order whose order quantity is greater than 2 then for my organization it's an urgent order else it is a normal order oh sorry I lost it so this is my order status column and I have my order quantity urgent or normal so any order which has order quantity one is normal any order which is having order quantity as greater than 2 is urgent you can see this so this is a this whole power B.I uh tabs and sheets allow you to also review the data what you're doing so it's very convenient now I have my sales data now what I want to bring within the sales is my discount column so here also I want to bring the discount which I have created so I'll say discount discount will be order quantity into related product discount so the discount calculated column which I had created under products I'll bring over here now I am creating the order level discount so if you see for this particular order there's a 25 uh you know for 25 ruby discount at the cost is 100,000 ruby okay and what is the order price now so I have taken the order cost the discount now I have to create a column call as price order price so that will be again order quantity into related price which is per product price and okay so now I have the cost the discount and the price right available with me now I want to calculate the total uh total revenue total profit and loss right so first I'll calculate per order how much revenue I'm generating so now I have to generate a column called as revenue revenue revenue is price so minus 25, 7800 minus 25, 2071 minus 42 and if I want to calculate the profit per order, then it is revenue minus cost.

Okay, so now you can see you know typical custom columns, calculated columns which you have created are all playing around with the numeric values, numeric data primarily and trying to give inferences into per order cost, discount, per order price, revenue and profit. So typical calculation columns which I have prepared in front of you. Now let's take a look at other different variations of custom columns. I'll create certain columns for text-based custom columns, calculated columns using text-picks data.

So I'm now moving towards my customer table in which I have customer key prefix, first name, last name, birthday, marital status and gender. Now I want to create a new column in which I want to derive the age of each customer as of today. Right? So I'll use another function, a date function called as date-diff.

Now date-diff. So I want the difference between the birth date of the customer and as of today in years. Okay, so this customer as of today 68 year old, 174, 68, 57 etc. So this is one derivation of calculated column of age.

Let's take another example. Now this is a text-based column where I want to derive the full name of the customer. Now here I will say first, lowercase. In lowercase I'll concatenate the prefix, then ampersand, space, ampersand, first name, ampersand, space, ampersand, last name and closing brackets, etc.

Full name. Okay, so this is an example of full name in lowercase. Now another calculated column, conditional column, at the customer level, I want to identify a flag which says who is my target customer, basis the demographics shared over here, target customer. So I'll say if the marital status is equal to m and total children, and total children and will income.

Okay, so let me change the logic a bit. So marital status is m and age is less than 50. These customers are my target customers. Okay, so I would say, yes, else no.

See this, he's a marital status is married, logon, d.as and age is less than 50, else everyone. So if I try to filter, so these are my target customers. 69 out of 1178. So this is just a conditional column, but a logical condition, an example which I'm trying to highlight over here.

Okay, now let's look at certain calendar, date oriented columns, calculated columns. Very typical, like now I have a simple date column. Now I'll keep adding certain columns, which you know, which help you, which will help you understand how we can do some calculations on the dates. So like for example, I want a date which is 12 days after the current date, the date in the column.

So just simple 12 days after, select the date and add 12. Now if you see the date format, you can go and change the format at the top and if whatever you feel like, like this, now see 12 days after first Jan 2015 is 13 Jan 2005, you can go and change the format and other details. Let me also show you, if I go to my cost and other columns, I can go and change the format. This is like a currency, cost is currency.

So I can go and select the chain, the currency type and you can even show the dollar value or whatever currency type it is. So the numbers you can do currency or text or dates, you can select the format. So this is available at the column tools level. Now in customers, like we had our column of full name.

So now what all things are available format as text, okay, data type text. So very minimal options are there with date, you have options of the date format. Now next, I want a column which defines the expiry date, okay. So 8 months prior to the expiry date with this which is coming up in 8 months.

So I will create a column called as 8 months expiry and then there is a E date function. I will use that. I will use my date in the data set, comma I will say 8. So now this date column will append 8 months to my actual date and again I can go and change the format.

Correct. Now another important column like I want to know the date name. So I will use a function called as format and I will select my calendar date column and I will say give me the dddd format of it. So it will give me the day name, the day name of on that particular date.

Next, years in between. So I want the years in between the today's date and the date of my calendar. So equal to date date, the calendar date, comma today, comma year end. Seven years 2015 to 2022, then last date of the month.

So if I want the what is the last date of this particular calendar month, I will use a function EO month which is there available in the Power BI. So I will say last date of the month equal to EO month, then just select the calendar date, comma zero in months in the end. Change the format. Then similarly start of the month.

So I will use a function called start of month. So for all January dates end of the month is 31st Jan and start of the month will remain first of Jan. Change the format. Next, I want to know what is the weak number of that particular date.

So now there is an inbuilt function called weak number, weak number and just pass the date and you will get the weak number. First week of the year, second week of the year etc. Now another very good example is whether the week day is a week day or a weekend. So what is it?

It is a weak type. So I will say I will put a if condition and there is a function called weak day and I will pass the calendar if it is less than 6 it means it is a week day, else it is a weekend. So all Saturday and Sunday day names will come as weekends and else everything else will come as windy. And now if you are not aspiring business owners then try to make a short assembly on the post-charge program and business analytics from the university in collaboration with IBM, the course link in the description and in comment should take you to the program being offered.

Now today we will discuss how to create relationships and different kinds of data models within Power BI based on the structure of data you are importing. Okay, so what topics we are going to cover today? We are going to talk about different types of data modeling and the most important part and aspect of data modeling is the cardinality. The cardinality which you basically decide after reviewing the nature of data and after we imported it, what kind of cardinality you have to basically highlight.

And there are different type of cardinalities which you might have heard earlier also if you are from PLCQ background like one is to one, one is to many etc. We will talk about that. Now one of the different types of data modeling. Now dimensional data modeling is one of the most popular and most widely used modeling.

In dimensional data modeling you have master data like for example customer data, date, store data, product data. So these are like you know less frequently changing data sets. So there is an organization right and you have set of customers, the email ID, phone numbers etc. That will change less frequently as compared to the sales transactions because transactions are happening every day, every minute.

So sales is a more fast changing data set in dimensional modeling which is in the terminology of data is also called as a fact and customers, store, product which are like more of static data and no less changeable data is sometimes called a dimension. So this is a typical dimensional data model which is typically used sometimes right and then there is another model which is relational model. This is a typical model which we have been using in database design like you know primary key foreign key relationships. So for example you have a customer who has purchased a product.

So probably he might have the customer might have the details of the product which he says and you will make a join between customer and product table and even you can make a join between product or product type or customer or product type. Customer table will also have a key to the product type. So this is less conducive for reporting but it is more of a transactional relational model but of course this is also feasible but from the power BI perspective when we talk about reporting and visualization this is the most extensively used dimensional data model and this is what we are going to see in our example now. So what I am going to do is I am going to show you certain data sets first we will prepare and create certain of our data sets and then we will import in our sample power BI file and then slowly slowly we will create the relationships.

Now one important thing which you need to understand that in power BI if you go to power BI there is an option that power BI auto detect new relationships after data is loaded and import relations from the data source on first load. So for example if you are importing the data from a database where you have already defined the primary keys and the foreign key relationships. So that is the first option which power BI will auto detect and secondly if suppose you are importing two different kind of data sets one is excel one is CSV and if power BI detects a common column key columns it will auto detect a relationship which you can go and later change modify manage in your relationship menu manage relationship menu in power BI which I am going to show you. So if I open a power BI and this is where the option lies go to file go to options in setting options data load and these are the two options which are by default check you can uncheck it and auto and manually prepare relationships there is no limitation to that but if you keep it checked then power BI will towards job to detect the relationships.

Now coming to the next important factor cardinality now before I start playing around with my data and start showing you certain relationships it's very important to understand these four types of cardinalities one is many to one right so basically many to one means that many orders contain data of one customer so per order one customer is there so from customer to order or product or delivery address it's a one to many relationship and from the other side from order to customer perspective it's a many to one relationship okay second other cardinality is one is to one one is to one relationship is only applicable when you are saying it's an extension of the current table so for example in one table you have employee details and you are extending the details of the employee in another table like address employee ID so that is like one is to one there's no multiple records of a single employee in the address table only one employee ID exists right now one is to many as I said is the reverse side of many to one is so in customer table only one customer record exists per customer and one customer can place many orders for multiple products and can also have multiple delivery addresses so that way this is a typical one is to many relationship we will be seeing this example also in our sample data set and last is the many to many relationship now many to many is a very typical example so which I'm going to show you practically and in our case we will see that like for example you have placed an order for a particular product you know but there are multiple fulfilments which has happened so suppose you made order for 10 products but at the back end when the company is fulfilling it is first fulfilling the first two products then the rest three so basically you the fulfilment is happening in batches so one order ID might have a multiple fulfilment for the same order ID so there will be a multiple many to many relationship which I'll show you practically so now with this background let's start importing our data now the first important thing which we need to import is the master data so first I'll import all my master dimensions which are which I'm going to you know use in my example so first is the customers table customers data so this is the customer details like customer key prefix first name last name both date marital status and gender some redundant columns are also a present but we'll remove it so my customer data is loaded now today's session is all about this section of modeling so we will keep our focus over here okay now some columns probably some blank columns are there I can select them and say delete from model yes okay so now this is my customers data with the relevant columns and the key per customer customer key now there's no relationship in this model right now right because only single table is there and the associate data is only imported now let me also import my another important master table is the products select the products data product key products subcategory product SKU product name modeling product description color size so just see all the relevant information only specific to the product is available so I'll import it okay now see there's no relationship between product and customers directly because until unless a customer makes an order places an order for a particular product there is no join right so now between these two tables the most important now another table which will now make sense is the sales order table sales table now I am assuming that power BI have auto detected the relationship now you can see that because I have already ticked that check box now let's see what power BI what relations power BI has auto detected let's first check the relation between customer and sales I'll double click this uh join now what it has done is it has created a join of many to one between sales and customers so what does that mean is that one customer has can place many orders right and that is that it has directed by the quality of the data and the data sampling which power BI has done you can also reverse this relationship here I can select customers and I can select sales now it has become one to many so that you can also do manually so that is what I said whatever power BI is detected it is up to the description of power BI internal configuration and algorithm but you can go and change it so this is now you can this is by default active so we want to keep it active one customer many sales orders cross filter direction means that only from customers to sales is the filter applicable not reverse I'll come to this with my another example but first let's change the relationship so one is to many means from one customer and many sales orders similarly let's see what has happened at the product side of the relationship similarly power BI many sales orders for one product you can for simplicity sake you can say products sales product key is the join now just focus one more thing please also see the column on which the join is is the grade column grade out column product key is also here product key is also there and it is what we wanted so one is too many relationship from product to sales table and active now looks fine this is something which is looking logical and probably now we can proceed further to create a report now let me explain the cross filtering within example now for example I want to check in a report that what is the count of products which which a particular customer has ordered okay so what I'll do is I'll select the product count of product name now if you see and for each customer in front of each customer the count is coming as 293 293 it is getting repetitive because because there is a one way filter direction filter between customers and sales and sales and products right so this join is single-sided it means that from customer to product you can't find a relationship because it's a single-side cross filter right what does us if I change it to both it means that it is equal to a join between product and sales and every product detail now is appended to the sales table so if I want to make you visualize this you need to go here I'll first open my sales table we can also open it here let's make click this okay now if I click okay you can see the single arrows change to double arrow it means that's it's a it's a both side filter so when do you say a both side filter it means that implicitly within power BI you can imagine that all the product columns now will get appended because of both ways filter you have applied and if you go to your report now see the change of the numbers now 40 20 so the total count of products across all my customers come out to be 293 now the report looks correct if I change the relationship from back to single between product and sales then you can't make a join between customers and product basically you can't derive the product count from the product table see this if you have to live with it then you would have to go to the sales table get the product key and get the value of count of product key but that is not correct okay so if you want a report in which you want the count of product name and even if you want a count of distinct product name so this will not come correctly you would have to go and change the direction of the filter which is from single to both so this is a typical example they where you want to use a two directional filter now let's proceed further can import other data set in order to give you another example now I want to show you an example of one is two one so I have another table which is called customer details so the key in this table is again customer key but only email address annually become totally children education level etc other details of the customer is there so I'm loading the customer details now you see it has auto detected a one is two one relationship what is the meaning of one is two means one customer key only has one entry in customer details there is no multiple entry so if you click this button it's a one is two one and the cross filter can be both or single doesn't matter because one customer will have only one value you can make this is active okay and if you go to the customer report table you can now easily associate a email address with the person and you will get one is two one recall so now you can see that with one is two one relationship with the first name I have associated the email ID and for each email ID there is a associated first name with that so this is an example of one is two one relationship so in this example what we have explained is that for each customer there is an associated customer detail right so you have the first name email address education level homeowner occupation and total children count so in this report what we have done is if you click over here so the first name and the email address okay so there's a one is two one relationship and then and if you drag customer key report takes time to render and even if you can so this is the reporting output you have the customer key first name associated email address and the count of product names which the customer has ordered now this is an example of one is two one now I want to show you an example of many too many now for that I'll import my fulfilment dataset okay now in my fulfilment dataset there is a column for order number so basically what I'll do is I'll drag order number from here to here okay so now what has a power be I detected I do one thing I'll select sales over here fulfilment over here and order number to odd number okay so it's a many too many relationships so it means that per order I have created multiple batches to fulfill that over to your order now many too many relationships is a definitely a candidate for both ways cross filter detection direction but you can you can check that but definitely power be I shows a warning that this relationship has cardinality to many too many and this should only be used if it is expected that neither column contains unique values okay so we know that fact that's why we are accepting this relationship as many too many because we know there are multiple order numbers over here in the sales table which are mapped to the multiple order numbers in the fulfilment table will click click now you want to keep the direction as both ways or one direction that is up to you the way you want to map the report so I can double click over here and you can even click so now you can select from which way single filter you want from fulfilment to sales or sales to fulfilment I'll prefer sales to fulfilment I click okay okay now we have our all our different kind of relationships over here which we have tried to shortlist one too many many to one one to one which is this example and many to many now if I show you further relationships which you can keep on hiding like for example I have the example of territories now in which particular territory the sales was done so I can map it over here okay so now it's a typical one is too many relationship because territory is my master table where I have a static list of continent country region and it is mapped to the territories which are in which my orders have been placed so it's a typical one is too many so that way you know you can keep on adding data then you have details of returns now this is another transactional table which is about the orders which have been returned rather than being you know returned by the customers so you have a product key and so automatically power via as detected a relationship between the product key and the product table right and even if you can join the territory key in which territory the return has happened right so mostly the most common relationship which you will observe is the one is too many because as I told earlier the most common relational model is the dimensional model the static data the slow changing dimensions the SCDs are the master tables and the most frequent changing are the fact tables so if I talk about a typical dimensional model the fulfillment table sales table and the territory stable sorry the fulfillment table sales table and my returns table are the fact tables of my data model I wondered what those people with fancy charts when their computers are doing they are probably business analyst so what's a business analyst think of them as the Sherlock Holmes of the business world they look at lots of information and figure out how to make companies run better and guess what it's a pretty cool job right now lots of companies are trying to hire these folks want to know how much they make when average about 85 thousand dollars per year some of them even make over 120 thousand dollars not bad right but here's the thing to be really good at this job you need to know some special words it's like learning the secret code of business and in today's video we are going to look at the 10 important words every business analyst should know and by the time we are done you'll be talking like a pro so let's start with the little story made john john works at a company and is always overwhelmed by all the data terms his colleagues use during meetings so words like kpi's data warehouse and analytics were thrown around and john often fed loads he knew understanding these terms was crucial for his career growth so he decided to dive into learning about business intelligence john started by learning what business intelligence actually means it is covered that bi in most strategies and technologies that have companies analyzed and managed their data for example if you worked at Spotify bi could tell him which songs are getting the most place when people listen the most and even predict the next bit it this realization made john see how powerful bi could be for making informed business decisions all right so let's dive in and let's understand what business intelligence actually is imagine you're running a popular ice cream shop and business intelligence is like having a super smart helper that tells you everything about your business cool right so what exactly is business intelligence it's all the tricks and tools companies used to understand the data better it helps them makes smart choices based on facts known just guesses for example let's say you use a tool like power bi in your ice cream shop it might show you which flavors sell the most on hard days what time your shop is busiest and which toppings are most popular with gates this info helps you makes smart decisions like stocking up on popular flavors or hiring extra staff for busy times business intelligence is super important because it turns boring numbers into useful information that helps businesses grow and succeed it's like having extra vision for your company next let's talk about data visualization so data visualization is the graphical representation of information and data by using visual elements like charts graphs and maps data visualization tools provide an accessible way to see and understand friends outliers and patents in data for example a bar chart showing the most popular pizza toppings in a delivery app this is crucial for presenting data in an easy to understand format moving on we have analytics so analytics involves the systematic computational analysis of data for example using analytics to understand which times of day are busiest for a pizza delivery app this term is important because it helps in making sense of large amounts of data and aids in decision making next up is kpi that is keep performance indicator so kpi is a measurable value that demonstrates how effectively a company is achieving keep business objectives for example tracking the number of pizza sold each month as a kpi to measure business performance kpi is essential for measuring performance and progress towards strategic goals now let's discuss data so data warehouse is a centralized repository for storing large volumes of structure data from multiple sources for example storing customer data from different gym branches in one place for analysis it is used for reporting and data analysis and is a core component of business intelligence data warehouses are important for consolidating data from different sources and making it available for analysis next we have database so database is an organized collection of data generally stored and accessed electronically from a computer system for example a database storing member records for a gym databases are foundational for storing and managing data efficiently and are critical for any business intelligence processes moving forward let's introduce data mining so data mining is the process of discovering patterns and knowledge from large amounts of data for example a gym analyzing member attendance to identify the most popular class times data mining is important for extracting useful information from large datasets next let's talk about dashboard so dashboard is a business intelligence tool that allows users to track key metrics and kpi's for example a dashboard for a gym showing daily attendance most use equipment and membership growth it provides a visual representation of data and helps in monitoring performance at a glance dashboards are crucial for real time data monitoring and decision making next up is reporting reporting refers to the process of organizing data into informational summaries to monitor how different areas of a business are performing for example a monthly financial report summarizing income and expenses reports are essential for tracking progress identifying trends and making informed decisions finally let's discuss sequel that is structured query language so sequel is a standard programming language for managing and manipulating databases for example writing an SQL query to retrieve all gym members who joined last month it is used to query insert update and modify data sequel is fundamental for anyone working with databases and business intelligence tools remember whether you are running a multi-million dollar corporation or a neighborhood laminate stand these bi tools and concepts can help you mix smarter decisions and grow your business they turn grow data into valuable insights helping you understand your customer better optimize your operations and stay ahead of the competition so with that guys we have come to the end of this session I hope this video has helped demystify some key business intelligence terms for you if you found this video helpful don't forget to give it a thumbs up and subscribe to our channel for more business and tech insights if you have questions about BI or want to share your opinion you can comment down in the comment section below well get ready to unlock your career potential I know you're curious already about what specific skills made the cut stick around to find out and prepare to level up your business analyst game forget the outdated list we are talking about the critical thinking cutting edge tools data driven insights agile methodologies and much more that will put you at the forefront of business transformation feeling overwhelmed already don't worry we will break down each skill into digestible chance with practical tips and tricks to ensure you master all of them whether you are a data with streaming new challenges a communications expert ready to bridge the gap or a problem solvo seeking the perfect toolkit this video has something for you so hit play only sure in a analysis and let's unlock the secrets to success in 2024 that said if these are the types of videos you would like to watch then hit the like and subscribe button and the bell icon to get notified just a quick info for you if you want to upskill yourself to master business analytics skills and land your dream job or grow your career then you must explore simple and scope out of various business analyst programs simply on offers a post graduate program in business analytics from Purdue University in collaboration with Amazon Google and Microsoft through this program you will gain knowledge and work ready expertise in the skills like prescriptive and predictive analytics regression classification and overdozles others check out the link in the description box and pinned comment to find a business analytics program that fits your experience and areas of interest so without further ado let's get started firstly let's understand what is business analysis think of it as an adventure exploring the hidden business treasures data magic tapping out to new possibilities and communication skills to unlock a business hidden potential technically business analysis like an art of detecting a business to find ways to make it better it's a process of analyzing business data understanding problems recommending solutions and implementing changes that benefits the stakeholders so who does this all who is a business analyst a business analyst is a person who processes interprets and documents business processes products services and software through the analysis of data imagine them as detectives or treasure hunters for business efficiency a business analyst is a program solver and translator who bridges the gap between the business needs and technological solutions they analyze data understand processes and communicate effectively to help businesses run smoother and smarter let's bounce back to a major topic of discussion now the top 10 skills that a business analyst must know in 2024 so the skills listed are a combination of technical and non technical skills most of the time non technical skills play a vital role for a business analyst let's begin with non technical skills and circle back to the technical skills critical thinking and problem solving critical thinking and problem solving ensure strategic decision making optimizes processes and mitigates any potential you need to have expertise to analyze complex business challenges identify the root causes and develop innovative solutions the main idea is to leverage analytical rigor to deliver data driven solutions for enhanced business performance collaboration and communication as a business analyst you must possess exceptional interpersonal skills bridging the gap between businesses and technical teams to achieve shared objectives it helps you to effectively collaborate with the diverse stakeholders fostering clear communication and consensus building to facilitate a smooth project execution aligning business goals with technical solutions and driving stakeholders buy in cost benefit and negotiation a business analyst must be capable of demonstrating financial acumen and negotiation progress ensuring value driven decision making and favorable partnerships you need to evaluate proposed solutions using financial modeling and cost benefit analysis skillfully negotiate contracts and resource allocation this maximizes return of investment and secures optimal terms for the organization project management and documentation every organization employees proven project management methodologies to deliver solutions on time within budgets and exceeding expectations as a business analyst it's your responsibility to organize and execute project efficiently utilizing agile methodologies and best practices create clear and concise documentation for stakeholders ensuring project success for meticulous planning risk management and timely delivery in fact a certification in project management and agile methodologies will definitely add weight to your profile domain knowledge you need to have an in-depth understanding of the specific industry business function or technology sector relevant to the role a business analyst must possess demonstrable expertise in the target domain providing a significant advantage of the competitive edge and strategic insights these facilities seamless integration into the business operations enables insightful analysis and build trust with stakeholders these are just brief summaries each skill encompasses a multitude of sub skills and find restrictions that further emphasize your expertise and value as a business analyst i am now circling back to the technical the color of business analyst hinges equally on mastering these essential technical skills to deliver accurate reliable and high performing results so let's get started with the most essential technical skills for modern business analyst number one Microsoft excel Microsoft excel houses many powerful capabilities and advanced understanding of formulas functions data manipulation and automation techniques will help a business analyst to efficiently analyze and interpret large datasets create insightful reports and automate repetitive tasks or number second database and SQL SQL is the most widely used data querying language versions like post grade sequel or Rackl sequel and my sequel are widely used in the industry from latitude with relational databases and query languages like SQL would benefit you in easily extracting transforming and analyzing data stored in various databases enabling you to earn deeper insights data analysis as a business analyst you need to master the fundamentals of data analysis explore a tree data analysis with Python in the art mathematics and statistics data analysis is a combination of statistical analysis high-polysis testing and identifying trends and patterns from data it helps translate raw data in actionable insights defines action items informs decisions for business and drives improvements or number four we have data visualization the critical part of business analysis is trying to establish solid communication between the technical team and the non-technical stakeholders enhancing the understanding of insights to facilitate decision making across all levels is mandatory one good way to do is by creating compelling charts graphs and dashboards this helps effectively communicate the complex numerical data into visuals that speaks for themselves tab you power BI and click view are some of the leading data visualization tools in the market ERP and CRM tools a business analyst needs to understand the enterprise resource planning or ERP and customer relationship management or CRM systems it helps to better understand and establish business acumen giving the organization a competitive advantage to streamline data analysis processes and gain holistic views of business operations and customer interaction tools like Oracle Fusion analytics sales force etc. awesome of the ERP and CRM tools mastering these skills empowers business analyst to shine in today's data driven world of businesses to unlock valuable insights and drive strategic decision making proceeding further we will discuss the important part of today's session salary trends of a business analyst business analysts are one of the top paid professionals around the world according to GlassDawd in India the average base pay of business analyst ranges from 5 black rupees to 12 black rupees per annum in united states of america the average base pay of business analyst ranges from $17,000 to $100,000 per annum imagine you are trying to figure out what most people in your neighborhood love to eat for desert you could ask everyone right but how do you make sense of all of these answers that's why statistics comes in it's like your personal data detective helping you gather organize and analyze all the information to spot patterns and trends with statistics you can easily discover if most people love ice cream or if brownies are the hidden favorite all about turning numbers and facts into useful insights helping you make smarter decisions and understand bigger picture hello guys welcome back to simpilance youtube channel and today i will walk you through the basic understanding of descriptive statistics inferential statistics frequency statistics and kurtosis statistics and more then i will take you through the differences among the various types by the end of the video you will know only one to know about statistics and its types without any further delay let's get into the video first things first let us understand what statistics actually is statistics is a branch of mathematics that help us collect organize and analyze data understand patterns trends and make decisions it's like having a big group of information and breaking it down to learn something useful for example if we survey 100 people about their favorite fruit statistics help us figure out what most people like what fruit is least and how confident we are about these results here after we have a basic idea of statistics let us get into the various types of statistics the first one is descriptive statistics descriptive statistics is a branch of statistics that focuses on summarizing and describing the main features of a dataset this is further divided into measures of central tendency measures of spread and data let's start with measures of central tendency and this is further divided into three types the first one is mean the average of all data points the second one is median the middle value when data is arranged in order the third one is mode the most frequently occurring value let's break down the measures of central tendency mean median and mode with an example imagine you have the following scores from a math test taken by seven students 72 85 91 89 85 76 and 90 now you want to calculate the mean now to calculate the mean you have to add up all the scores and divide with a number of students therefore the mean is 84 it means the average scores of the students is 84 now moving on to find the median to find the median we need to take the same example and we have to arrange the scores in a sending order the median is the middle value so in this case the middle value is 85 since it is the fourth number in a list of seven so half of the students scored above 85 and half scored below 85 now moving on the next is to calculate the mode the mode is a score that appears most often so we take the same example and we see that 85 occurs twice more than any other score so the most common score in the test is 85 now moving on to the next that is the measures of spread unlike central tendency which tells you whether the data is centered spread tells you how scattered the data is it is three components range variance and standard deviation range it is the difference between the highest and the lowest values in the set and variance it measures how much each score deviates from the mean and standard deviation it is the square root of variance let's use an example to understand measures of spread range variance in standard deviation which help us understand how spread out or dispose the data is consider the test scores of five students now we want to find the range therefore the range is the difference between the highest and the lowest values in the data set that is 85 minus 65 is equal to 20 the scores span range of 20 points from 65 to 85 now moving on we want to find the variance for the same example the various measures how much each score deviates from the mean on average squared first we calculate the mean so to calculate the mean we take the total of the scores divided by the total number of scores and that is equal to 75 next we find the squared differences from the mean for each score and here it is 65 minus 75 whole square is equal to minus 10 whole square and that is equal to 100 and in this way we perform the same for each score now the sum of this square differences divide by the number of data points is the variance and that is taking the total of the squared differences divided by five that is equal to 50 the variance is 50 meaning that on average the square differences from the mean are 50 now moving on to find the standard deviation the standard deviation is a square root of the variance it tells us how spread out the data is in the same units as the original data the standard deviation is the root over of 50 that is approximately equal to 7.07 now moving on the third major subdivision is data distribution let us use an example to explain data distribution which tells us how data points is spread or organized across a range of values imagine you have the following test scores for 20 students one way to understand data distribution is by creating a histogram the histogram groups the scores into ranges or beams and shows how many scores fall into each range for this dataset we could create bins like 50 to 60 there are three students 61 to 70 there are seven students and 71 to 80 we have five students and in this way 81 to 90 we have three students and 91 to 100 we have two students now moving on to the normal distribution the second one under the data distribution in some cases data follows a normal distribution which forms a Bell-Shaped curve and this means most data points are around the mean with fewer data points as you move away from the mean in other direction and normal distribution curve it means most data points are around the mean with fewer data points as you move away from the mean either direction in a normal distribution the mean median and more at the same data is dramatically spread around the center. Now moving on in our example, the scores are somewhat concentrated around 7 to 2.8. But the distribution is not perfectly normal because there are more students scoring higher.

That is the right skew. Therefore skew distribution, if a data set is not symmetrical, we have skew distribution. And that is further divided into two. The right skew that is the positive skew and the left skew that is the negative skew.

In right skew, more data points are on the lower side with fewer higher values. And in the left skew, more data points are on the higher side with fewer low values. Moving on, in our test, score example, we have a slightly right skew distribution because there are more students with lower scores, that is to 55 to 70. Compared to higher scores that is 90 to 100.

And this is known as right skew distribution. Now moving on to the second type of statistics that is inferential statistics. It uses sample data to make predictions and generalizations about a larger population allowing researchers to draw conclusions beyond the immediate data set. inferential statistics comprises several techniques for drawing conclusions.

Here are some common types. Hypothesis testing. Second one is confidence intervals and the third one is regression analysis. Now moving on to hypothesis testing.

Hypothesis testing is a statistical method used to determine whether there is enough evidence in a sample of data to support a specific claim about a population. Let's work through the process of testing whether a new teaching method improves student test scores breaking it down step by step with some explanations to make it easier to follow. Step number one is hypothesis. We always start by stating what we want to test.

In this case, we want to see if the new teaching method helps students score better compared to the traditional one. To do this, we set up two hypothesis. 8-0 that is the null hypothesis. And that is the average test score with the new method is equal to 75.

This means that the new method has no impact and there is no improvement in the test scores. H1 that is the alternative hypothesis. The average test score with the new method is greater than 75. This suggests that the new method does improve test scores.

In simple terms, we are trying to figure out if the new method makes any difference compared to what we normally expect, which is a score of 75. Now moving on to the next step that is significance level. Next we need to decide how confident we want to be in our conclusion. The significance level helps us measure this.

It tells us the probability of mistakenly rejecting the null hypothesis when it is actually true. Type 1 error. A common choice for this significance level is 0.05 or 5 person. This means we are willing to accept a 5% chance of making a mistake by rejecting the null hypothesis when it is true.

So we set alpha is equal to 0.05. Step 3. Collect data. Now we need some actual data to test.

Let's say we taught 30 students using the new method. And their average test score came out to be 78. This is our sample data and they will compare it to the population mean, which is 75, the traditional method score. Now moving on to the next step that is perform statistical test.

The t test. With a data in hand, we need to perform a statistical test. For this test, we will use a t test, which will help us compare the sample mean 78 to the population mean 75. The t test checks if the difference between the two means is significant or if it could just be due to random chance.

Moving on to the next step that is the p value. The p value from the t test is the number that tells us the probability of getting the sample data if the null hypothesis is true. Let's say the test gives us a p value of 0.03. This means there is 3% chance of seeing this level of improvement if the new method doesn't actually improve scores.

Now moving on to the last step that is decision. Now we compare the p value to our significant level alpha. If the p value is smaller than 0.05, it means the results are statistically significant and we can reject the null hypothesis. In our case, the p value is 0.03, which is less than 0.05.

So we reject the null hypothesis. Now moving on to the second part, that is confidence interval. A confidence interval is a range that tells us how sure we are about an estimate from sample data. It gives a range of values whether the true member likely falls.

For example, suppose you survey 100 men in a city to estimate the average height. The average height from your sample is 175 cm and the standard deviation is 10 cm. You want to calculate 95 percent confidence interval to estimate the true average height of all men in the city. Now let's move on to the steps.

Sample mean the sample average is 175 cm. The standard error is calculated as 10 by root over 100 that is equal to 1. Now the confidence interval formula for a 95 percent confidence level use the critical value 1.96. The confidence interval is 175 plus minus 1.96 into 1 that is equal to 175 plus minus 1.96.

The result, the 95 percent confidence interval is 173.04 comma 176.96. You can be 95 percent confident that the true average height of all men in the city is 173.04 cm and 176.96 cm. Now moving on to the third one that is regression analysis. Regression analysis is a way to understand how one thing affects another.

For example, if you want to shop and want to know if spending more on advertising increases your sales, you can use regression analysis. In this case, advertising spending is a thing you control that is the independent variable and sales is what you want to predict by analyzing the past data. Regression helps finding a pattern or relationship. For example, you might discover that for every dollar hundred you spend on advertising your sales increased by dollar to hundred.

This means you are positive relationship between advertising and sales. Now if you plan to spend dollar 500 on advertising, you can predict and increase in the sales by applying that relationship. Regression analysis gives you a formula or model to make such predictions. Based on the pattern, you identified.

In short, regression helps you logically predict how changes in one factor affect another. Next, I will be talking about is frequency statistics. In statistics, frequency refers to how often something occurs in a dataset. It simply counts how many times each value or event appears.

Frequency is useful for understanding the distribution or pattern of data. Let's say you survey 10 people about their favorite food and the results were four people chose apples, three people chose bananas, two people chose oranges and one people chose grapes. Here's how frequency works. Apples have a frequency of four as four person chose it.

Bananas have a frequency of three oranges have a frequency of two and grape has a frequency of one. In this simple example, frequency helps you see that apples were the most popular food choice while grapes were the least popular. Last but not the least, let's talk about kurtosis statistics. Cortosis is a statistical term that describes the shape of the distribution of data, especially how the data is concentrated in the days.

It also understand if the data has more or fewer extreme values compared to a normal distribution. It is further divided into high kurtosis and low kurtosis. High kurtosis has more extreme values and in low kurtosis the data has fewer extreme values. In short, high kurtosis means more extreme heights while low kurtosis means more consistent evenly spread heights.

By now, you speak curious to know about the differences among all the types of statistics. So here we go. Differentiating them on the basis of purpose, the scribbled statistics summarizes the main features of a data set. For example, mean, median and standard deviation.

Inferential statistics makes predictions or generalizations about the population based on sample data. Frequency statistic counts in specific values or even software in the data state. Kurtosis describes the shape of the distribution focusing on the days and extreme values. They're appreciating them on the basis of data focus.

Descriptive statistics deals with the entire data set at hand. Inferential statistics uses a sample to infer conclusions about a larger population. Statistics focuses on the frequency of individual values or categories. Kurtosis focuses on whether the data has many or few extreme values.

Now differentiating them on the basis of common metrics. In descriptive statistics is the mean, median, mode and standard deviation and range. In inferential statistics, this hypothesis testing confidential intervals regression analysis and statistic, the frequency counts, frequency tables, histograms, bars and charts. In kurtosis, kurtosis value, high kurtosis is equal to mode extreme values and low kurtosis is equal to fewer extremes.

Now differentiating on the basis of complexity. Complexity in descriptive statistics is simple and straightforward. Summarizes the observed data and in inferential statistics, it is more complex and in statistics, it is simple counting and displaying off occurrences. Kurtosis, it is request statistical analysis to determine the distribution's scale denotes.

Now finally, differentiating them on the basis of visualization. Descriptive statistics is the box plots, pie charts and summary tables. Inferential statistics, it is confidence intervals regression lines, p values and more. And in statistics, it is barred charts, histograms, frequency tables and Kurtosis, it is histograms, distribution plots to visualize outliers.

So here is the question for you guys. I hope everyone will comment your answers in the chat section and let's see how many of you understood the topic. So the question is, which of the following is not a measure of central tendency and the options are mean, median, mode and standard deviation. But distributing the quies and I hope to see your answers in the comment section.

We will reply to whoever provides the correct answer and the wrong answers will be corrected for sure. I will provide you one minute to write your answers in the comment section. Welcome to SimpliNan. In this video, we are focusing on chat GPT and its groundbreaking role in data analytics.

In a world where data is the new world, understanding and analyzing this worth of information is crucial. But as the volume of data grows exponentially, traditional analysis methods are being pushed to their limits. Entire chat GPT, a revolutionary AI developed by OpenAI that is transforming how we approach data analytics. But what makes chat GPT stand out in the crowded field of data analytics tools?

How can it not only streamline complex processes but also uncover insights that were previously hidden in plain sight? Stay tuned as we under the capabilities of chat GPT share real world applications and show you how it's been used by analysis and businesses alike to make smarter, data-driven decisions. And whether you are a data scientist, a business professional or just a tech enthusiast, curious about the future of AI in data analytics. This video is for you.

So let's dive in and discover how chat GPT is not just revolutionizing data analytics but also how we understand and interact with the vast universe of data. And don't forget to hit that like button, subscribe and ring the bell to stay updated on all our future explorations into the fascinating world of technology. Now let's get started and then look the potential of chat GPT for data analytics together. So guys, an excel data analyst always looks for ways to improve their efficiency and gain deeper insights from the data.

That's where chat GPT comes in handy. So chat GPT is an AI powered language model that can assist you in various tasks including excel based data analysis and for that data analysis, let's dive into some demos to see how it works. So guys, as you can see, this is the chat GPT 4 and you could see this has the support of Dalai browsing and analysis and user's limits may apply like we have the version that has some user's limits. And for the data, I have downloaded the data from the kegger.

I will provide you the link in the description if you want to download the same data you can and I have that in my downloads. So this is the data that we'll be using. So the first thing we'll be doing is data cleaning and preparation. So firstly, let's explore data cleaning and preparation.

Before diving into analysis, it's essential to ensure that data is clean and ready for processing. So for that, we will write a prompt in chat GPT and ask him to clean the data. Chat GPT has the feature to insert the files provide the excel file to the chat GPT and we'll ask him that can you help me identify and remove duplicates in this excel spreadsheet. So let's ask him, can you help me identify and remove duplicates?

duplicates from this excel spreadsheet, from the provided excel spreadsheet. So you could see that Chat GPT has started generating the response and he is telling us that he can definitely help us with that and he is analyzing that. So you could see that Chat GPT has provided us the response. So let's first go to our spreadsheet.

So this is the spreadsheet. Oden number, quantity ordered price of each quantity and order lines. So you could see that first Chat GPT has encountered an error and that is with the character encoding miss patch. And then he has loaded the spreadsheet successfully with the second attempt and you could see that he has provided like the smaller or the prefer version of the spreadsheet that is the dataset consists of sales data with columns such as order number, quantity order, price each order line, sales, order date status.

So he is asking us could you specify how you would like to identify duplicates? For example, it should be consider a arrow or duplicate if all its values match and in the row exactly or are there specifically columns we should focus on to determine duplicates. So we should or here we will be focusing on the column section. So here we want to identify column section.

So he is asking which columns they should identify duplicates. So we want the duplicates in order number. So the Chat GPT has started analyzing the spreadsheet. So you could see that Chat GPT has purchased the response that they have identified a total of 2800 seven rows in the spreadsheet that have duplicates based on the order number column.

So this indicates that multiple rows share the same order number suggesting they might be different items for transactions within the same order. So we would like to proceed by removing these duplicates while keeping either the first or last segments of each order number or do you have another approach in mind for handling these duplicates. So we four identifying the duplicates. What we will do is we will first get rid of the extra spaces.

So we will ask Chat GPT that first find the extra spaces in the spreadsheet and help us remove them. So you could see that it has started analyzing it. So he is asking us that would you like to proceed with any further cleaning or data manipulation? Yes, we want to proceed further with data cleaning only and now we will treat all the blank cells if there are any.

Now treat all the blank cells if there are any. So the spreadsheet contains blank cells in the following columns with their respective counts of blank entries that is address 9 to as 2521 blank cells in the state. So depending on preference of the requirements of the data analysis we can treat these blank cells in similar ways. So just filling them with a taste holder value that is not provided using a specific value that makes sense for data that is example a default state of territory.

But potentially leaving them as if blanks carry meaningful information if the context of your data. So what we will do? We will provide a placeholder, provide a placeholder instead that is node provided or node applicable. So you would see in the spreadsheet has responded that it has replaced the blank cells in the columns that is address line 2 state postal code and territory with the placeholder node provided.

So you could see there's a verification sample showing the updates. So this is how you could clean the data and now with charge jpg you can be identified and eliminate duplicates in your excel spreadsheet using built-in functions and formulas saving your time and effort. So that would be done by the charge jpg and you can download the excel file from the charge jpg only after that you can just ask him that quite mean the output or the result at spreadsheet. So if we talk about data analysis and visualization let's delve into that.

So excel offers powerful tools for analyzing and visualizing data and charge jpg can help to make the most of them. So for this also we'll write a prompt to the charge jpg and we'll write for example we'll write please create a pivot table and a corresponding chart to analyze sales performance by region. So let's see like this prompt what output does charge jpg showed us. So let's ask him please create a pivot table and a corresponding chart analyze sales performance by region.

So you could see that charge jpg has started analyzing the data and the spreadsheet and you could see that the pivot table below shows the sales performance by region or the territory. So this table indicates that the EMEA region has the highest sales performance followed by regions where the territory was not provided then APEC and finally Japan. So now let's create a chart to visually represent this sales performance by region. You could see that it has provided a chart that is a bar chart illustrating the sales performance by territory.

So you would see the guys that it has provided us the analysis and charge jpg can guide you through the process of creating pivot tables charts and other visualizations in excel. Annabling you to gain valuable insights from your data with ease. So let's move to advanced analysis and automation. So lastly we'll explore advanced analysis and automation.

So excel capabilities extend beyond basic functions and charge jpg can help you leverage its cool potential and put this also will write a prompt to the charge jpg that can you assist in building a forecasting model to predict future sales based on historical data present in the spreadsheet. So let's see what charge jpg respond was. So let's ask him can you assist me in building a forecasting model to predict future sales based on historical data. So let's see what charge jpg respond was.

So you could see that building a forecasting model to predict future sales based on historical data in more several steps. So for this you have to prepare the data select a model train the model evaluate the model and make predictions. So let's start by preparing the data we'll aggregate sales by order date to create a time series of total daily sales then we'll choose a model based on data's characteristics. So we will run the permission to charge jpg to proceed with the steps.

So we started analyzing the data. So you could see that that the data has been prepared into a time series of total daily sales and before choosing a forecasting model it's helpful to visualize the sales time series to understand its characteristics such as trend and seasonality. So charge jpg has floated a daily sales data and then he has given the visual trends and the possible seasonal patterns. In the next steps would include testing for stationarity model selection and parameter during model training and then forecasting.

So you could follow all these steps with the help of charge jpg and could create a forecasting model. If you want we can move to the next step. So you could provide a prompt to the charge jpg that move to proceed with next step. So step by step charge jpg will provide you for casting model or it will help you create a forecasting model.

As you can see it has started analyzing it to the augmented Diki Fula that is ADF test gives up a p value of approximately 0.0033. Since this p value is less than the common significance level of 0.05 we can reject the null hypothesis that the time series has a unit root meaning the time series is stationary. So you could see that he is asking us shall we proceed with the Sarima model parameter selection? Yes here is the model parameter selection.

So you could select any based on the trends and the bars are sploted by the charge jpg. So you could see guys that the charge jpg has analyzed the spreadsheet and provided the response that the grid search for the optimal Sarima parameters based on the lower a Cali information criterion such as the best fit model uses the parameter 0 1 1 and for Arima and 0 1 1 12 that is for the seasonal component. So you could see that it has provided the model and the parameters. Now he is asking us shall we move on to forecasting future sales with this model?

Yes proceed with that. So you could see that with charge jpg's assistance you can build complex forecasting models in Excel allowing you to make informed decisions and plan for the future effectively. So charge jpg is a valuable tool for Excel users and data analysis. Offering assistance in data cleaning analysis visualization and automation and by integrating chat jpg in your Excel workflows you can enhance your productivity and uncover new insights from your data.

So you can try at jpg for Excel data analytics today and take your excel skills to the new level and you will see that there's an error in analyzing and he has encountered an error while trying to plot the forecast with its confidence intervals. So this type of error can occur due to data type issues particularly when handling data and I say is in forecast and despite the sick up the forecasting process using the serial model those completed and be able to generate forecast for the next 12 months. Unfortunately due to the plotting issue you couldn't visually displayed. So we'll ask him can you try once again?

So you could see that this time charge jpg has provided us the forecast for the next 12 months. That is the forecast have been successfully plotted along with the historical daily data. So here we have our forecast model and with the chat jpg assistance we can move with other analysis. Hey everyone welcome to Simply Launch YouTube channel.

Today we will learn about data transformation and probably that. That said if these are the type of videos you'd like to watch then hit that like and subscribe buttons and the bell icon to get notified. So what exactly you will buy data transformation and power BI. So data transformation can be a little similar to data to you.

So before any kind of data analytics you might be receiving the raw data from a website source as equal database or an Excel file or multiple sources. Once after you receive the data whether it is batch mode data or streaming data you are supposed to clean. You might have to clean up the discrepancies like the blank rows or the blank cells or any irregularities in data such as wrong data type right such discrepancies from the data should be eliminated in the first stage of data analytics. So that's exactly where data cleaning and data transformation comes into the picture.

So you have various tools for data cleaning and data transformation like Excel is equal but if you are a power BI user then goodness be you. Power query in power BI can assist you in terms of data transformations. So in this tutorial we will be discussing the fundamental the most important day to day data transformations which a data analyst takes care of and the process of data analysis is what we are going to discuss today. So let's quickly switch to power BI but before that let's have overview of what kind of data you are exactly dealing with today.

So we are dealing with super store data and that's in Excel format. So this is our super store data set and we have four tabs here the first one is for the step where we have customer ID, order ID, date, shape date, shape mode and customer name and in the second tab we have store status set which has the details about the customer from where he or she is the state city, post code and which category they purchase and order, sales, discount, corporate, everything. And here we have some information about any of the orders which were returned and some people over here. So these are the four tabs that we are dealing with today.

Now that we have an overview on the data that we are dealing with let's quickly now switch to power BI. So now we are on the power BI window. We can just discuss changes. There you go.

Let's quickly import the data from a download system. This is the state that you want to deal with today. Now it might take a little while to connect to that particular data set and load the data onto power BI just a couple of minutes. Since the data set is a little too heavy it's about 10,000 rows.

So let's wait. Shouldn't take long. There you go. The data got successfully loaded.

So you have the option of loading what kind of data you want. You have four tabs as we just discussed. You can load the order, stab and you can load the store, stab and in case if you want the return stab you can also load that and if you want all of those just load all of those. Now I just want the two tabs orders and stores.

Now here I can just directly load to get started working on this but in case I don't want any kind of discrepancies in case if I have a doubt that this data might not be cleaned I shall go with data transformation. So ideally you should go with data transformation check your data first before any kind of analytical processes. So let's go with that transform data and shortly we should be having the power query window open on our discrop screens. So there you go.

You can see the complete data set has been successfully loaded. Both these stores and orders data sets. Now let's quickly check the data from our data set. So here you can see we have orders date.

But I can see 4 to 682 and 4 to 5WD. This is not in the form of date. So this is the simple step that we discussed changing the round data type. So you can just click on the lower arrow button over here and we can right-click and here you have an option to change the type correct.

So it is considering it as a whole number which is wrong. So you can change it to date. It is current. So now we are trying to change the order date from a data type of whole number to date in the data type.

So there is some error if you click on error or if you just now we can come to it. Power BI should be able to show you what error was it. In just in case if it's not working okay we are unable to parse the one provided. So you can just remove that and try it in a different way.

Change type to date and time zone date. I think this should be helpful. Or if it's not working here let's quickly check what could be here. And now let's try to refresh the data.

It is taking a little while. We also have another information that we deal with. We have the first row as the row headers. So we should particularly layering power BI that we also have a row header we have.

Sticking a little while to refresh. Meanwhile let's quickly check into the store status and here we have customer names. So let's try to apply second type of data transformation which will be like let's say split column. We have the complete name of the customer.

Let's try to split it into first name and second name. So by the limiter and we can give multiple options over here. Left most of the limiter let's say a person has three parts of his name. First name, middle name and second name or the last name.

So but we just wanted to split it into first and second name. So we would go with the first left most limiter and split the data set. That's okay and it should help us to split the data. That's name and second name and that we can also name the column separately as first and second name instead of custom meaning.

It's taking a little while than the ideal time but it's completely alright since considering the 10,000 rows of store status and 10,000 rows of orders data. It is alright another problem. Now let's try to take a look at the order status. It has successfully changed it.

No it is still showing as an error. Here knows from here it's to moving and complete. It's quickly refreshable instead of row and check if it can help us. So there you go after refreshing the first order date is changed to date.

So what we missed is when you change the tag supposed to add a step. So what exactly am I by that? Now we are trying to change the second one as well. So just wait for a while and it will give us a choice if we want to add new step or not.

That's when we select the option yes please add a new step. So what do I mean by steps? So applied steps you can see something over here right? So every alteration, every change or every modification that you're doing every transformation you have including onto a data will be recorded as a macro.

So that can be implemented if you are loading a similar dataset. For the next patch let's say this is 2022 data and if you are trying to analyze the 2023 data and every column is similar and you can just follow these applied steps and the same implementation will be automated. You don't have to spend time and doing the same process once again. There you go.

So this time it has recorded this step and it automatically has taken a new step over here, change step one, change step two. If you don't want the step to be added you can just select the red x mark over here it will remove it and similarly when you go back to the stores to the set here you have the first name and second names let's successfully and now let's say you want to have unique customer data right and that's scenario you can just even remove duplicates from this particular column just remove duplicates and you'll just have unique data. It's possible that one customer might have come here to buy the same product you know by the same product on different days or one customer might have done a repeated purchase. So it's possible but again if in case if you just wanted to know if there is a way to eliminate duplicate entries then do that.

So for now let's not delete the customer IDs here because one customer might have visited the same store multiple times might have purchased a different product or might have made the same order with multiple products right so there is a possibility for that let's not disturb the dataset. So I just wanted you to know if there is a way to eliminate the duplicates from the dataset yes it is now let's also check another possibility of data transformation. So let's say you want it to add and you call them and identify or include some mathematical operations for now. Let's say I have sales quantity just can't unprofit but I don't know what's the rate right so here the sale is for two sixty one dollars and quantities to but I don't know what's the rate of one for you so I can include that you can just select the last column or where you want and you call them just go to the add you column here and here you can just choose the custom column should be somewhere here yeah this is the custom column and now if you click on the custom column you can rename the custom column to rate of product and here you can choose the mathematical operations to be applied on the column so sales column insert or double click divided by quantity okay now it should give you the rate of each product individual product it is taking some sizable time which that takes a long so they're going to have the rate of product and now let's say if you want to combine multiple datasets for example here I have stores dataset but my stores dataset doesn't have any data related to all this and orders does not have any data related to customers now I want to combine these two is there a way yes you can do that now let's get back to stores and here go to home option and here you have something called merge queries so now the store dataset has been selected in the first dataset here just select the drop down and select the second data type of your orders so here you can see stores with the current one which is the first place now select based on which primary key you want to combine both so I want to go with custom variety because both of my datasets do have customer IDs so I'll go with customer ID and both datasets will be combined at the end at the last column probably I will show me a new table not a new I'm calling it will give me a table combined with all the columns in one column you just have to expand the column and select which columns from the second dataset you want to do the new order dataset so let's do that practically so here you can see I just have tables if I select the expand column option right here you can see I have a lot of columns here so just deselect everything I do have row ID I do have a custom right how what I need is order ID order date ship date shipment mode and customer name I do have it so that's all I need so just press on okay and I should have them included in my new dataset altogether it might take a little while so there you go we have the new orders ID or date ship date and ship mode added to our dataset now just click on close and apply and here dataset is already for data analysis supply changes but it is taking a little time so at the end you just have to click on the apply changes and your data will be ready for analysis so that's exactly how you can perform data transformation in power BI desktop version so there you go the reselting got successfully loaded all over here and you can just drag and drop them onto the visualization spot and you can work on your date today we will learn how to use power BI with AI for that let's consider a small problem statement or in other words a simple use case so here it goes a business change data analyst use power BI to generate sales performance dashboards across multiple stores due to manual data cleaning report structuring and repetitive that's calculations the process takes several days delaying the important decision and let's struggle with errors and inconsistencies due to high data complexity by integrating power BI's AI features like smart narrative and AI insights the automate trend identification and anomaly detection now analyst quickly generate visualizations by simply typing questions reducing manual effort AI assisted data modeling ensures cleaner datasets and accurate relationships enhancing effeasing in scene as a result report generation time drops by 50% dashboards are more insightful as stakeholders receive actionable insights faster that's it if these are the type of videos you'd like to watch then hit that like and subscribe buttons and the bell icon to get notified now as discussed in the use case let's imagine a similar performance analysis dashboard now what exactly is AI in power BI so AI and business intelligence are two technological spears that when combined offer powerful tools that of transforming raw data into actionable insights and making data accessible to everyone similarly AI features in power BI can analyze user behavior to customize reports and dashboards to meet individual needs raw data now let's imagine this suppose there is a significant growth in business and you wanted to identify the reason behind it and replicate the same idea across old categories or maybe revolt the team which is responsible for them or let's say there is a significant drop in business and you wanted to understand the reasons behind it and pinpoint onto one which is responsible so that you can resolve and improve the overall business growth and pull out some revenue right now if you are doing it manually using excel datasets or even if you're doing it with Power BI datasets you might end up creating a lot of power query stacks expressions and also if you're working on excel then you end up creating a lot of pivot tables and it might be a manual task and will consume a lot of time right or in case if you're in help with AI then the matter of days could turn into the matter of minutes and you will have the exact data our information you're looking at and you can resolve it in a matter of minutes or hours maybe after a business decision has been made now let's go through a practical demonstration on Power BI for this so before that let's have a quick look on the dataset that we will be using today so this particular one which is the auto sales data for 2024 is the one we will be using today we hold the columns order ID and delivery date state dealership pin co-region and the names of the products and the fuel type leads revenue profit and cost company everything right so this is the cleaned data that we have today for our data analysis now we will be identifying the key areas that lead to the quadrant quarter growth or if you drill down a little bit more then we can also identify the month on month growth or in case if there is a drop in month on month or drop in quarter on quarter we can also identify what is the reason behind it where is the loss coming from which car product or which dealership or what might be the reason is it about the season or the customer or the dealership we can drill down a lot of information from it right so this is the overall idea of how to utilize AI in Power BI now let's quickly switch to Power BI now we are on Microsoft Power BI and we have already loaded the data which is here this is the preview of the data that we are going to work on now let's go back to the report view and pull out a visualization now I'll be trying to proceed with the bar graph now let's pull some data so I'll go with the audit date and drag and drop it to the x axis now let's go with the orders and that will be in our y axis here you go now if you drill down a little bit this year will be turned into quarter of the year now if you kind of drill down again now you have month on month now let's try to do some modifications to the status set or the data visualization and add some improvements go to the view tab here go to the customized current theme and go to text and now here you can increase the font size maybe 18 to have a better visual and after that if you go to the format icon here you can also add a data labels if you want what is the total number of sales that we made now we have a perfectly functional chart here let's eliminate this now let's begin with the AI for identifying the drop trends or the growth trends now here you can see the month of August in 2024 has given us the highest sales which is 2618 orders and you can see there is a quite a good growth here now if you wanted to find out what is the reason behind this growth then just click that bar and right click or double click and go to the option called analyze so this is similar to the x-ells what if analysis but with a little change now here you can see that power BI will automatically give you load of charts individualizations like this one here which is a water wall model and this will indicate you what was the reason of the growth and here you can see we have received 11 orders from anthropodation this is a statewide analysis and also you have decrease so there is a decrease in miserable and a few more regions like a nut pan everything so this is something behind the reason for growth or growth and here you can see the product wise analysis where we have some growth from cars like 8 series well-pired on others that you have some dealership data as well so there is a good orders that is received by prime auto elite auto and a few others and there's a drop in Asian dealerships etc and here you have the state is on delivery so this is also good and now let's say now you wanted to identify what's the reason for drop now what you can do is you can just click on the month which showed you the maximum loss or the least orders received and you can go to that so the least orders is practically from March and here you can see there is a certain drop from August let's say you wanted to come back with these two months and then what you can do is you can just save procedure you can just analyze and now explain the decrease now you have the reasons behind the decrease here so we have a couple of cars which are not receiving the demand of sales and after that you can also see state wise drop in orders and after that you can also see the type of car which has stopped receiving orders you can see sedan class has drastically stopped receiving orders that's the reason behind it and after that most of the orders are in transit so you can filter out the in transit once because this will be delivered to the customer so the overall you know sales will be or the overall orders number will be increased once this transit becomes to deliver right and here you have delivered as well right so it might be a drop in delivery numbers as well and compared to the previous month the number of orders delivered will be low or if you had to talk about the in transit I think this is about the in transit one as well so previous month had a lot of cars in transit and this month compared to that number it is a bit low so that's that can be the reason and after you drill down a little bit more you have region wise analysis now this is also another way to find out the drop analysis and let's say you wanted to compare two different months of a quarter right so here you have quarter one the highest performing month of quarter one happens to be the February one no the January one and you wanted to compare that with the highest performing month of quarter three which is August in that case you can just hold control and select the first month from first quarter which is the highest performing one and you can compare month on month I'm going to the analyze button explain the reason between the increase here now you have the entire report now let's say you have a brilliant looking chart over here and you wanted to present that to your stakeholders now all you can do is you can just select this particular chart and select the option which says plus we should automatically get added to your dashboard which is somewhere here and you can set it in the way you want now you almost have a semi functional or mini dashboard for you which explains you the decrease or the gain and orders and also the month on month performance so you have a fully functional report in front of you which is explaining the comparison between the highest two performing ones so this is how you can make use of AI in Power BI for data analytics today we will learn how to build a star schema using the data modeling process in Power BI Power BI data modeling is crucial for effectively analyzing and visualizing complex datasets when data resides in multiple tables or sources it can create challenges such as inconsistent relationships redundant data and slower query performance data modeling results this by uniting disparate datasets into coherent structure enabling efficient data retrieval and streamlined analysis a well designed model often employs the star schema which is a relational database structure that organizes data into a central factory table surrounded by dimension tables the factory will contain numerical metrics like sales or profits while dimension tables hold descriptive attributes like product categories or custom names this task can simplify squaring and enhances performance by minimizing redundancy and maintaining clear relationships between old datasets this structure is particularly advantageous for reporting and business intelligence as it ensures faster processing and more intuitive navigation per users by implementing a robust data model Power BI users can overcome fragmented data and unlock actionable insights with means that said if these are the type of videos you'd like to watch then hit that like and subscribe buttons and the bell icon to get notified now we will understand what exactly is a star schema in Power BI so in other terms people also prefer to call this as a snowflake schema in Power BI because the shape of the schema represents a star shape or a snowflake so basically there will be one fat table which stores the major part of the dataset and there will be some sub tables or these subordinate tables which store the relevant data to that particular fat table so the fat table maintains many to one relationship with these dimension tables right so basically it will be interconnected with each and every table in the particular schema and you can extract information in the day you'll like this might be a little confusing theoretically but let me navigate you through the session through a practical demonstration let's actually create a dataset using generative AI and moving ahead we will extract or we will pull the same data onto the Power BI platform and then let's look at the star schema practically now let's go to the charge AP or any of the generative AI platforms to create the dataset that we are looking at so this will be my prompt for creating a star schema so we will be trying to generate five different date tables with 2000 rows each so we will be creating one fat table which is the sales data followed by that we have four dimension tables which are customer data product data orders data and shipping data so this is the problem that we will be using today now let's select the entire prompt copy that and get back to charge gpd and here you'll just paste that prompt and then hit the go I've already created one such data table it would take a little time to generate the dataset while a charge gpd is working on creating it let's look at the data that I only have in my inventory this is the data that we have in inventory so as for the inventory the sales data which happens to be our fat table has order ID price discount cost to company let me expand this profit and rigged right and then the fat table is then connected to the dimension tables which is about the customer information customer data customer names states etc and the product details to which category or which product is being bought by the customer and then we have the orders data and shipping data right so shipping data includes the type of shipment more chosen by the customer and also the order date and the ship date let's save this now let's have a look at the the generative AI prompt that we just wrote so there you go so charge gpd has successfully created the dataset and here the link is you can just click on this link and you'll get the downloaded dataset which looks something similar to this one right now how exactly stars schema or snooge leaks schema works now let's say I have this audit details here the sales data here I have order 001 234 and 5 let's say I wanted to track this particular order with boadee 005 so I want to find out the customer who bought that now I can get connected with customer data having the order key order number as the key in between which is common in between both the tables and based on that I can extract the customer details the customer name the customer city the customer state country and region and now let's say I wanted also to extract the product details of what the customer 005 has been buying or on the order number 005 is it right now if I trace down the audit details further I can identify the product ID product name and product category along with the subcategory of the product name which happens to be tables right and now if I drill down a little more bit then I have these many number of trafficking leads and orders received to buy 13 quantities of that particular item called table and they preferred you know kind of same-day delivery so this is how these star schema works all tables are interlinked to each other now let's quickly switch the power BI platform and try to extract or pull the same dataset onto the power BI platform and then let's wait for power BI to generate us schema there you go now we are on the power BI platform and now the data that we are working with is in the form of Excel so let's prefer the Excel workbook as our source now this is the data the demo data that we just created you can just open it and the data will be called for you onto the platform it might take a little while let's wait so here we have the data ready and we have five tables according to the discussion one fact table and remaining else are the dimension table so the customer data orders data product data shipping data are the dimension tables and the fact table is sales data you know and then you can just load or transform as far as I'm concerned my data is clean and I don't have to proceed with the transformation but just in case if you want to perform some data and you can go ahead with transformation of data and if you have to look at an exclusive tutorial on the data transformation using Power Query then we have linked it in the description box below and we can have a clean reference to it so far so good I'll continue with loading the data since I'm confident with my dataset just load it and it might take a couple of moments the data is slowly loading let's give it some time there you go the data has been successfully loaded and here you have the view of your dataset so here we have leads or write the quantity etc product details and the sales details all of them that you need it and if you proceed with this particular table view you can see the tabular version of the dataset and here lies the most important part of today's discussion the model view and if you go here the power BI platform has already created the relationships between your datasets and if you just rearrange a couple of those them as you can literally make a stop act note of it and also if you look at this particular position here you can see that we can establish some new relationships or you can try to edit some existing relationships with the managed relationships option now you just have to drag and drop a few of these tables over here so that you can exactly maintain a start type of pattern there you go so that's how you can generally create a start type schema or also known as the snowflake type of schema and power BI today we will learn how to use power automate in windows power automate will help you to automate the mundane tasks like rolling out reports emails presentations and many more for that let's consider a small product statement or in other words a simple use case so here it goes let's assume that you are a business unit head working with the top brass of your organization your routine might include a lot of tasks like setting up roosters scheduling scrum meetings writing down emails common data entries and a lot more these might not sound much of a task but definitely consume sizable amount of your work in hours the time that you prefer to be more inclined to utilize for resource planning and setting up road strategies for business development if only there was a way to automate all these processes without having to hire another resource yes that can be done with help of one of the most recent Microsoft Office tools called the power automate with power automate the time for all these tasks will be dropped by 50 person and you have a lot of time for productive utilities to build better business strategies that's it if these are the type of videos you'd like to watch and hit that like and subscribe buttons and the bell icon to get notified now the first question what exactly is power automate so power automate is a cloud-based service that automates repetitive tasks across apps and services is designated to help users optimize business processes and focus on more strategic tasks now it is not just confined to Microsoft products it can also be get attached to Google or any other applications as well if you want to roll out some emails via Gmail or if you download some files and so it onto Google Drive power automate will always support it now let's proceed to take a know of you of how to use this Microsoft tool so some of the mundane tasks like sending out an email scheduling some roosters or meetings or some points of the meeting it'll always be a lengthy task that consumes a lot of your time now for a sample task like sending out daily emails we will try to automate this task now we have logged into the Microsoft 365 so here you can have some apps over here and you can check out the app for power automate now we can just go to all apps and here you can just scroll down and here you can see the option that says power automate there are other ways as well you can just you know search for the power automate app and find it out in apps here or now you can just find it here you can just log into the power automate app so power automate already has some templates for it right so you can just navigate to templates and there are many uses of automate so if you want to do with some email attachments or if you want to trigger a power BI data driven alert or if you want to you know set up something in your Microsoft Office or you want to put a notification or if you want to download all the attachments from your email directly to your Google Drive and connect your you know x or twitter you can do that so there are multiple people who have already used Microsoft power automate and they've already delivered some templates for the ready for use purposes and if you want to go with some topics you can also go with this or if you're working with remote work kind of style and you wanted some applications or some automation things you are looking for you can also look at the templates which are remote work related you can just go through all these templates and you know go ahead with that apart from that if you're looking for some data collection type of automation you can also do that and if you're looking for an email automation it goes to that and if you already have created some flow who you can just go through this and find the flows that you have worked on so I've got one flow already ready here I've set up an email that you can be sending out to your reporties or you can send out this email to your fellow developers or fellow Achilles and if you have some improvements you can also do that so there are a lot of things so as we discuss before we will go with the automation of sending out daily reminders so I'll just type down get daily reminders and I get this type of automation here where you'll just send out an email reminder to the outlook.com email which will be which can be about an email to check the numbers check the reports and hand it over to your fellow team members right so it may be about a scrum meeting or roast meeting or setup so I'll go with this one and here you have the recurrence and office 365 outlook so this is my email and I'll just continue and here is the flow so here you can just click and you can give out an interval maybe if you want to give it every day or if you want to give it weekly or by week you can set it up so I'm going to go with every day and here you can set up any press-cry or if you have any type of times in that you want to select you can go ahead with that so I'll go ahead with anything here I'll go with Alaska maybe and you can also provide some time and it's not a mandatory one and apart from that you have some hours you want to select maybe I'll go with 10 a in the morning and also I want another setup at 6 p in which might be the log out time and yeah this is the one and apart from that just go back to the flow once again and here you have to set up few parameters so let me give out an email here as well the recipient email you can add multiple but I'll go with one so I'll add one email recipient address here that's the one and apart from that subject could be about the scrum call with report updates of with numbers number updates can give anything according to the business needs and you have a reminder and I think I'll add the same subject here there you go and you can also provide the importance so I'll go with high importance one so that the recipient will understand so far you have set up the flow I think it's fine so you have no more notifications here this says the flow is completely fine now you want my to save this flow and once the flow is saved you can proceed and test it click on this it's saved and you can you if you want to try and test it you can also do it just test it and it can happen in both ways automatically or manually I'll now go with the manual one so that I can just cross verify if this is happening or not at the current time right we set a time in 10 even the morning and 6 p.m.

in the evening right so it only happens twice but now if you want to run it at this particular instance you can also do that by just testing it I've tested it and I have sent out the yeah it finds good and now if I select run flow then it will run the flow now it has already done no success it's successful no problems here and done and you can now just you know kind of log into your outmail outlook a email then check the email right just a second by logging to my inbox there you go now we have this particular email that we sent right now you have a reminder scrum call with the numbers of date and you can just reply or forward it so this is how you can just automate the emails with your power automate and you can just send out email reminders to your fellow developers or teammates on a regular routine and that's how you automate a lot of simple things as your daily thoughts and I've already created two here and if you go to templates you have a lot of other templates here most of it or if you're looking for a dedicated one like data collection email calendar mobile etc they've also found them there and if you're still in confusion maybe you can just type down and find the templates which are in match with your requirements two most popular job roles in the field of information technology that is business analyst versus data analyst business analyst is a professional who bridges the gap between the IT and the business teams in an organization they use data analytics and modern technologies to assess processes and deliver data driven solutions they understand and solve a business problem and validate business requirements a business analyst generates reports for executives and stakeholders they're part of the business operation and work closely with the technology team to improve the quality of the services being delivered they also assist in the integration and testing of new solutions now let's talk about the job description of a data analyst with the rapid increase in data generation today the term data analyst has found its prominence a data analyst collects processes and performs analysis of large data sets every business generates data in several formats this data can mean the form of customer information and feedback log files transaction data marketing research and so on it is the duty of a data analyst to transform these business data into valuable insights some of the problems it can be addressed are how to improve a business how to provide good customer experience what would be the ideal price for a new product how to reduce transportation costs and so on data analyst deal with data handling data modeling and reporting with this brief understanding of the job description for a business analyst and a data analyst let's now shift our focus towards the various responsibilities of a business analyst a business analyst identifies the business goals understands the problems faced by an organization and comes up with a cost effective solution to tackle issues they thoroughly understand the requirements from the clients and assign the right resources be as communicate and work closely with the development team to design the solution for a problem they ensure that the development team doesn't spend their time understanding the stakeholders requirements and often give iterative feedback on the solution being developed they check and validate if the project is running fine with the help of user acceptance testing they also verify if the solution being worked on is in line with the requirements and ensure that the final product satisfies the user expectations b.a.s.s is the functional and not functional requirements a business analyst documents the project findings and results they present the project conclusions through the stakeholders and clients along with delivering maintenance reports and building visualizations to make decisions now let's take a look at the responsibilities of a data analyst first and foremost a data analyst must identify and understand the organization's goal and requirements this helps to plan and streamline the analysis process data analyst collect data from various heterogeneous sources they assist available resources comprehend the business problem and gather the right data for analysis they work closely with different team members like programmers business analyst and data scientists data filtering and data rambling are vital jobs of a data analyst the data collected is often noisy and it contains missing values hence it is crucial to clean the collected data and remove invalid values to make it ready for analysis they use a variety of analytical statistical and business intelligence tools to spot trends and patterns in complex data sets discover hidden insights and prepare summary reports for the leadership team they also use programming languages for data mining and data manipulation now it's time for us to understand the difference between a business analyst and a data analyst based on the skill set they possess first let's look at the skills that can help you become a b a business analyst should have a graduation degree in any relevant field such as business accounting information systems human resources or engineering you can apply for entry level business analyst positions or with professional experience excel is a powerful analytics and reporting tool for working with data b a is used excel to perform various calculations data analysis plan an editorial calendar and calculate customer discounts to derive meaningful insights and take decisions b a is used SQL to retrieve manipulate and analyze data stored in relational databases critical thinking skills are important to understand customers business needs it allows them to distinguish between requirements that add value to the business and those that should be given a lower priority b a should find different ways to address each challenge data visualization is a key skill for b a is to build interactive dashboards and reports to convey the outcomes of a project knowledge of tabloo per bi and click view is required to make different types of reports depending on the business requirements business analyst should have a good hands on programming experience to solve complex tasks and perform faster analysis of data hence knowledge of programming languages such as r and python is a prerequisite finally they should have good presentation skills they should also be confident about their findings and conclusions and communicated in front of the stakeholders and clients let's now understand the skills that a data analyst should possess you must have a bachelor's degree in any relevant field or be a graduate in statistics economics or science you're eligible to become a data analyst being a fresher or as an experienced professional you should have domain knowledge in the field you are working in once again knowledge of excel is another basic requirement for a data analyst data analyst often work with structured data so they should be proficient in writing SQL queries using data manipulation and data definition commands they should know how to create stored procedures another crucial skill for a data analyst is to have hands-on experience with programming languages such as python or sass and javascript you can analyze and visualize large data sets and create predictive models for making business decisions data analyst create data visualizations using libraries such as map lotlib c bond gg plot and plotly this helps them to perform exploratory data analysis knowledge of tablu and power bi are is required to create different business reports with the help of graphs and charts data analyst should have knowledge of machine learning algorithms to build sophisticated models and make future predictions so they should know about linear regression logistic regression support vector machines came in clustering and other supervised and unsupervised learning algorithms finally data analyst should also possess good communication and presentation skills now let's discuss a salary structure for both of these job roles according to pay scale a business analyst in the united states earns an average salary of 69 thousand dollars while in intia you can earn nearly six lakh rupees per random now talking about the salary for data analyst according to pay scale in the us a data analyst earns an average salary of 60 thousand seven hundred and ten dollars per annum and in india you can earn around four lakhs twenty four thousand rupees per annum let's now move on and look at the different companies hiring for business analyst roles here we have oracle the search engine giant google the american mnc cognizant and e-commerce company amazon in addition to that we have earnest in young technology giant IBM Dell and Cisco hiring business analysts talking about the companies hiring for data and lists we have twitter google the social media leader facebook and amazon we also have the american oil company shell the electric vehicle company tesla apple and the american credit reporting agency equifax now choosing the right field that is to become a business analyst or a data analyst could be a challenging task the key points that you have to keep in mind before making a decision is first review your background and see what qualifications you have check what skills you possess and the domain knowledge you have then gauge your interest to see what suits you best and finally consider your long-term goals and see the job roles that will help you grow in your career in the long run now let me tell you how simply learn can help you grow your career as a business analyst and a data analyst simply learn offers a postgraduate program in business analysis that is in collaboration with perju university the endorsed education provider is iiba some of the skills that will be covered in this course are strategy analysis while framing solution evaluation dashboarding data visualization agile scram methodology scram artifacts statistical analysis excel and sequel database some of the tools covered in this course are Microsoft excel tablu power bi gira post crescequil plan box and others some of the key features of this business analysis program are you will receive perju post graduate program certification master classes from perju faculty you can enroll in simply learns job assist where you will get iam jobs pro membership for six months and obtain 35 iiba pdcd use and 25 pmi pd use you will get 170 plus hours of blended learning along with capstone projects in three domains to become a data analyst you can enroll in the postgraduate program in data analytics offered by simply learn this program is in collaboration with perju university and ibm the skills that will be covered as a part of the course are statistical analysis using excel data analysis in python and are data visualization using tablu and power bi linear and logistic regression modules clustering using k means supervised learning and others the tools that you will learn on numpy pandas scipy scikit learn excel and others some of the key features of this course are you will get perju post graduate program certification industry recognized ibm certificates enrollment and simply learns job assist and master classes from perju faculty you have 180 plus hours of blended learning 14 plus hands on projects on integrated labs and capstone projects in three domains so please go ahead and enroll for these programs if you want to grow your career as a business analyst or a data analyst business analyst interview questions my name is richer curfew with the simply learned team will go with some beginner intermediate and advanced level questions to expect an interview when you're looking at business analytics let's start with the differentiation between a risk and an issue and this should be a very fundamental question dealing with business because in business they want to make money and we really want to understand where the split is on a lot of these things so i always ask yourself where is the bottom dollar on this and what does this mean risk is your potential and an issue is something that's actually happening so risk is a potential problem that can be predicted risk may or may not happen in the future a proactive response plan is formulated and kept ready to mitigate risks so these are things you plan and the issue refers to a risk that is occurring or about to happen there's no response plan in place to solve an issue you can only respond reactively to an issue what are the various tools a business analyst works on this is very company specific and so when you start looking for work you start going in for interviews you just start really asking yourself what are these companies looking for that i'm interested in clearly if you work with ibn you want to have your tools that are central to ibn and the ibn setup same thing with google with you know just across the whole field some of the more basic ones obviously an excel spreadsheet which isn't on this list but your python your sql you should really know your sql because it's going to come up in no matter what format you're in your tabloop your exure your balsamic all these are different platforms there's a lot more out there but you should be aware on which platforms your proficiencies are on and those also that you might not be proficient on but you at least know what they do what their performance is you can answer questions and a lot of companies will pay for you to be certified if their platform isn't on your list what are the various stages of a business project and we look at project initiation project planning project execution project control and monitoring project closure and it's really important to understand any one of these in a little bit more detailed in just knowing the list what is feasibility study a feasibility study is a method of gauging the success rate of proposed business solution it enables business analysts to discover new business opportunities and really a lot of businesses when they're looking at it for a business analyst this is really what they want to know what's the feasibility that is a very central question that comes up in most business plans what's the feasibility of doing something and getting it done what is business model analysis business model analysis is a technique that helps you analyze if a business is financially economically and socially viable or not and know a number of contractors that this is their sole career is to go in and analyze ski resorts in Colorado to find out whether it's going to make it this year or not and what they need to do to fix that so it's a very high-end job niche we really need to know your stuff and understand what it means what do you understand by requirement differentiate between requirements and needs we look at requirements requirement is a targeted solution that is required to achieve the set business objectives business requirements are data used for business processes needs needs are the high level representation of the terms and the result business needs included inifying and comprehending the businesses goals and articulating its strategic direction and you can think of needs are what do we need to succeed requirements are well these are the things we need to put into place this is what's required to achieve a business objective suppose you have been given a list of zip pin codes from different countries using those codes find the city and the state names using Excel and so if you're given a list of zip codes pin codes are various cities from the US in India here's how you can find the city and the country names select all the codes go to the data tab under data types select geography click on the insert data option choosing city from the field list click on the insert data option and select state from the field list really you do need to know your way around excel no matter what other packages you're working with excel is such a base package in business analysis so much people are given that back and forth still it's still kind of a baseline below our sales data that has information on different items sold across various regions and countries what was the total revenue generated for all the items in India you can use the sum if function to find the total revenue generated from India you see here equals sum if and then of course b2 to b100 India L2 to L1,001 and that will give you the sum you can also use a filter option to filter the data only for India and use sub total by pressing alt plus equals nice short hotkey to remember there create a highlight table to visualize a revenue generated from offline and online sales for different items across a region using tabloos now not all companies use tabloos but it is becoming a very highly used tools is so easy to use you drag the region on to columns drag the sales channel and item type fields onto rows select the total revenue column and drag it on to collours and label cards select square as the mark type drag the total revenue filled onto columns drag the total profit column onto rows place item type column onto collours under the size card place a total profit drag the region column into the filters card and select Asia so one of the things about tabloos is it looks real complicated but it's all drag and drop and so you should know your way around about doing some very simple drag and drops for doing your query and summation and below is the resulted plot so let's look at some more questions but let's jump to a little more intermediate level differentiate between software development lifecycle and project lifecycle so we're looking a little bit more hierarchical towards the top of the list software development lifecycle helps with the development of software products it consists of a single software across multiple phases here phases include requirement gathering coding operations maintenance and documentation where the project lifecycle this enables you to develop a new product in the business project lifecycle consists of multiple software and one customer scenario phases here are idea generation screening development testing and analysis how do you perform risk management in your project so again we're doing with intermediate not just how to pull tables across we start analyzing things and the risk management is a technique wherein risks are identified avoided reduced assessed and mitigated having the appropriate risk management plan decreases losses and optimizes decision making to enhance the organization's performance how does risk mitigation differ from risk avoidance risk mitigation risk mitigation is a plan to be executed when a risk occurs when a risk occurs there might be a business impact and the cost incurred is high risk avoidance whereas risk avoidance is carried out to avoid the risk from occurring meanwhile the business impact here is zero and the cost is fully eliminated and you can think about a brick and mortar store and they have shoplifting you want to mitigate as you want to avoid as much shoplifting as you can but you can only frisk people at the door and have security so much before you start losing customers and so when you mitigate it you're going to have to pay for your lost merchandise or you void it you have your security cameras and people watching to stop people from stealing things risk in this case can mean loss of money spent badly spent on equipment certifications there's all kinds of areas where you want to mitigate and avoid risk what are project deliverables project deliverables represent a collection of measurable services and goods that are to be delivered to the end user in the project completion stage this is so important we start talking about any of our when you sign a contract any of our online contracts cloud computing all of that make sure you're very clear what the deliverables are who owns it who is the responsibility of the service and the security around it those are all very important questions to know differentiate between the agile and waterfall model two of our biggest or most basic models used the agile model which is slowly taken over especially in software the agile model is adaptable to requirement changes and has an incremental approach in the agile model testing can be performed in every phase with the waterfall model the waterfall model is referred as a structured software development methodology changes and requirements are difficult to implement meanwhile in the waterfall model testing is performed only in the final phase and you can look at this as a lot of the software today has to be ready to change quickly when the waterfall setup you're not looking for fast changes you're looking for a very solid it's going to work no matter what kind of view this is something that we can build it doesn't have to make major changes but it better work correctly describe the different analytical techniques like Moscow and SWAT Moscow analysis it is a prioritization technique that highlights a requirement significance question like is it a must have or should have could the demand be made better what a specific idea be useful in the future are asked here in the SWAT analysis it discovers the strengths and weaknesses of a firm and evaluates them as opportunities and threats SWAT analysis consists of strengths weaknesses opportunities and threats and you cannot kind of think of it as like the SWAT team coming in to you know you're worried about threats here so we're talking about policing or in Moscow really what is what can we get out of this you know is is this do we have to have it to succeed is it going to be useful in the future so you're looking more for a general value attached to it list various components of strategy analysis for developing a strategic plan for an organization the vital components are vision objectives mission strategies action plan what is benchmarking benchmarking is a process of evaluating an organization's measures like the quality of policies programs etc against the standard criteria it's so important to have that baseline of what are you measuring against the baseline might not even be a very good one but you can't measure something let's you have something to measure it against it helps with the measuring the performance of the company you can recognize the areas of improvement in a company and analyze how other companies achieve other objectives what is the best approach to work with difficult stakeholders a business analyst interacts with many professionals during his work few of the best approaches to take into consideration while working with difficult stakeholders are before I even jump into this I have a friend who is working with some very high-end individuals who took their private plane and he was supposed to meet him at the low in location when he arrived they had been in a fist fight well on their private plane the stakeholders had so much difficulty with some particular aspect going on so difficulties are going to arise hopefully not at that level but things happen and of course you want to just assume work with anybody but you want to listen patiently to the stakeholders point of view respond to them politely and diplomatically have a one-on-one discussion to make things more precise comprehend their worries and be transparent make sure to continuously engage such difficult stakeholders and I'm going to highlight the last one because if you're working with somebody who's difficult and you just try to ignore them one of the things is that whatever problems are arising they're just going to explode so that is so important not to ignore somebody who's being difficult but the rest of it is stay focused stay focused on what you're trying to accomplish be goal driven this is a great time to be goal driven not driven by emotion or the problems that arise or how the person communicates name the different types of agile methodologies scrum you'll get scrum certified important thing to look into if you haven't learn software development and extreme programming XP feature driven development FDD crystal can ban dynamic systems development method dsdm there is an agile just a ton of different methodologies so knowing at least a few of them inside and out and having a kind of a general idea that the other ones are out there is important to at least know what we're talking about when someone comes up and talks about agile describe the gap analysis gap analysis refers to the analysis of differences between the existing systems functionalities and the targeted system the gap indicates the amount of work required to get the intended result gap analysis is a comparison between the current and proposed functionalities you can see here we put together an action plan to go from the current state to the desired state how do you import text file data into msxl and remember excel is one of those things that has been around forever and even though it's like the bottom barrel of a lot of analysis that we do most of our data starts in an excel spreadsheet or comma separated variable file that you then end up with an excel spreadsheet given below is the employee text file it has information about name agent company and here's how you can import this data into excel go to the data tab click on get data drop down under from file select text CSV select where the text files located in your system and click on import click on low data imported into excel you've been given sales data that has information on the cell of different items across the world below is the data create a pivot table to analyze the profit of all the items in each region now remember pivot table is a table of statistics that summarizes the data of a more extensive table so it takes a full data sheet and we're just going to bring we're going to focus zoom in on something is what the the pivot table means if we want to go ahead and do this we do is we go ahead and select a cell in the table go to insert and click on pivot table in the create pivot table box choose existing worksheet to place your pivot table drag region and item type on to rows drag total profit on to values sort the sum of the total profit column using the sales table find the percentage contribution of cosmetics to the total revenue and total profit create a pivot table by dragging item type onto rows select the revenue and profit column under values right click on the revenue value under show value as select percentage of grand total right click on a profit value under show value as choose percentage of grand total you can see here when we do that we end up with cosmetics made a 14.03 percent contributions to the total revenue and an 18.94 percent contribution to the total profit how do you create a dual axes chart in tabloon drag the order data onto columns and convert it into continuous year drag total revenue on to rows and total profit to the right corner of the view until you see the light green rectangle synchronize the right axes by right clicking on the profit axes under the marks card change some total revenue to bar and some total profit to line and adjust the size and color there lots of fun to play with as you start getting into these using the sales data create a view to show the total unit sold and the profit generated from each item which item sold the police and has least profit so we'll go ahead and load an excel file data in tabloon desktop drag units sold onto columns and item type column under rows place the total profit column under color and choose the desired color palette sort the unit sold axes in descending order you can see here it produces a very quick but figures shows a fruit sold and the least and had the least amount of profit create a map to show the unit sold and the profit generated from different middle east and north africa items drag country onto the detail card place the total profit column on the size drag unit sold under color in the filters card drag the region column and select middle east and north africa barrain had the maximum number of units sold at the same time iran made the full amount of profit create a visualization to analyze a total revenue and the unit sold for close meet and baby food across different regions in 2006 and 2017 drag the unit sold filled on the columns drag the region and item type fields on the rows under the color card place a total revenue column drag item type onto filters and choose close meet and baby food drag the order date column onto filters and select 2016 and 2017 meet had the highest unit sold it made the maximum profit now with any of these tablue it's good if you have your own hands on for this so it that's an important thing to note we kind of zoomed in on tablue again there's a lot of other companies out there using a lot of other packages so if you're not familiar with tablue but you're able to do this in another package that's a good thing so at least you know what we're talking about and you've had that hands on let's go ahead and jump to some advanced level questions what is requirement prioritization name the different techniques used for it requirements prioritization focuses on allocating requirements depending on the business urgencies this is essential for the project to run well requirement prioritization enables various teams to understand what is important and work in sync with the business needs there are several techniques used for requirement prioritization we had Moscow technique we mentioned that earlier the requirements are grouped based on must mandatory should high priority could not necessary but preferred and would suggested for the future ranking method here you give each requirement a distinct numerical value based on its importance of course this is at 100 oh well here's kind of similar to ranking is the $100 method multiple stakeholders get a no-no-sional $100 to distribute among the requirements so the $100 method is pretty similar to what the ranking method is top 10 requirements and this approach from a large set the stakeholders simply pick their top 10 requirements this is very popular there's a lot of help books out there about getting things done they say write everything that you want to accomplish put them on three by five cards and narrow it down to five do those five because once you've conquered those five then you can move on to the next ones name the critical agile metrics that should be considered by a business analyst sprint burn down so the sprint burn down is the chart we use when you're tracking usually since grum is where that usually comes from the scrum setup but it's a chart of the work to be completed and what's still going on you have your work category allocation the velocity the cumulative flow diagram defect removal awareness time coverage defect resolution time explain bpmn bpmn business process model and notation gateway controls the flow of interaction and sequence of processes it is a flow chart technique which models the end-to-end business process step the four essential elements of bpmn are flow objects events activities gateways connecting objects sequence messages associations swim lanes pool or lane artifacts data object group annotation list the elicitation techniques the elicitation process is about gathering requirements from users and stakeholders listed below are a few techniques that are used to collaborate with users or clients interviews do not many times have been on the phone calling competition potential clients to ask questions so one of the elicitation techniques is to ask questions if we're going to call clients to ask questions in a lot of terms also turn into additional sales document analysis focus group prototyping brainstorming my favorite brainstorming all these are important I just kind of highlight a few of them that I tend to get stuck in observations and workshops again workshops are a great sales technique also so as you're doing your business analysis and you're bringing people into a workshop and do observations in the workshop and working specifically with these people they turn into potential business growth I tell you what if you're a shareholder and someone's doing a business analysis and they turn around and generate a $30,000 dollar sell for your company they're in you know you've already earned your you've already earned your pay and you're doing what you like which is business analysis interface analysis questionnaire and survey question your surveys my least favorite but they are the most popular because they're the easiest to pump out list the documents needed by a business analyst initiation document project vision document use cases system requirements specifications document business requirement document requirements traceability matrix functional requirement document use case specifications document gap analyst document describe how you would approach a project here's a basic project approach outline which you can use with respect to different situations identifying the project goal formulating the work plan defining the requirements collaborating with other teams tracking the project documenting the progress and really when you start designing your project approach encompassing all the things listed in here is so important with the shareholders if you it's great if you can identify your project goal that's probably the most important thing because if you don't have a goal you might as well walk away but if you don't have the rest well how are you formulating the work plan defining the requirements collaborating with other teams that is such a big step because we're going from everything being on paper and trying to figure out what you're going to do to actually doing it and then tracking and finally documenting very important for the shareholders and what goes back to the top differentiate and alternate flow and exception flow in a use case diagram from a basic flow basic flow represents the operation of activities is required by the company in a use case alternate flow as the name suggests is an alternate solution used in a system failure case different steps are used to complete the goals of a use cases exception flow refers to the various steps executed in case of errors this does not lead to achieving the required goal of a use case critical aspects of creating analytical reporting analytical reporting is a type of business reporting which provides data analysis information and recommendations it enables people to use data to make decisions to create analytical reporting the following points should be kept in mind comprehend business analysis display your analysis skills think critically and i'm going to throw in here the term from big data map and reduce really when we're doing a business analysis you don't want to give them a massive amount of information you want to reduce it down to something that they can see in a single graph a very simple set of notes and you need to think critically you need to really make it what is it that the shareholders want it's going to make them understand why this is important to the business and what does the business get out of it what is can ban can ban helps agile teams and visually managing work through processes it works as a scheduling system in agile just in time production the can ban methodology is all about real-time communication of capacity and full transparency of work the can ban board describes a current development status and of course when you're working with can ban you got to be very careful about inspiring versus coaching versus micromanaging it really can't end up in a micromanaging setup where you want to you want to watch out for that which you also need to track everything a basic can ban board has three step workflow as the to-do in progress and done however depending on a team size structure and objectives the workflow can be mapped to meet any particular teams unique process state the key differences between BRD and srs BRD business requirements documents is a high-level functional specification of software BRD is a formal document to describe the requirement provided by the client business analysts create this post their interaction with the clients srs system requirements specification is a high-level functional and technical specification of software srs describes the software's functions and non-functional requirements that are needed to be developed whereas srs is created by the systems architects what is perito analysis the perito analysis helps in crucial decision making it helps in prioritizing decisions identifying the most relevant and the least decision concerning the overall goal is also known as the 80-20 rule as per this rule 80 to percent of the project's benefit arises from 20 percent of the work vice versa 80 percent of the case problem can be due to 20 percent of the causes differentiate between the v model and the fish model we talk about the v model is an sdlc model where the execution of processes happens sequentially in a v shape and every stage the same person reviews but other testers will do software testing in the last step v model consumes less time and costs the fish model is similar to the v model but with more multiple verification teams every stage is tested by another team for completeness and correctness the fish model is compared to the very costly and time consuming which makes sense because if you have multiple tests on each stage for multiple teams they have to all be spun up on it and so you're literally more than doubling the work because you also have to track all that given the sales data create a chart to show each region's country that made the highest revenue create a pivot table by dragging the region and country onto rows place the total revenue column under values right click on the country values select the filter options and choose top 10 choose top one is shown above and click on okay and you can see here is the pivot table that you will get using the sales data find all the countries where the total units of fruits sold offline were less than 3,000 you need to use an advanced filter option in Microsoft Excel to solve this problem below is the critical based on the question we have go to the data tab select advanced filter option choose copy to another location give your criteria range and the copy to location with the gun okay here's the final result as we can see below let's create a pivot table to find which countries from each region made the lowest amount profit create a pivot table by dragging the region and the country into rows place the profit column under values right click on any country value select the filter option and choose top 10 choose bottom one and click on okay let's create a filled map to analyze the total revenue and profit generated from beverages in North America using tablue drag country under detail card place the total revenue column under the text drag total profit under collure and the filters card drag the region column and select North America in the filters card drag the item type column and select beverages and you can see from the below map you can see the greenland and the maximum revenue and profit generated from beverages in North America who knew using tablue how will you display the top five and bottom five items based on profit drag the item type filled under rows and total profit onto columns right click on the item type column to create a set give a name to the set and select the top tab to choose the top five items by some total profit create a set for the bottom five items by some total profit select both the sets right click to create a combined set give a name to the set and choose all members in both sets drag the new set on the filters and the total profit onto collure the above graph depicts the cosmetics made the highest profit while fruits made the lowest and really when we're talking about tools like tablue or if you're targeting companies working in R or you're targeting companies working in python you should be able to quickly do these kind of displays in any of those packages that you're focused on tablue is one of the biggest ones out there right now because it is a paid for service but it's also very robust and easy to use and uses less programming on the back end so just a quick side note on there really just leads up if you if this does not look right to you're not able to get through some of these things make sure you are if that's what you're targeting in a company for an interview so that's it I'm going to put on a full course if you have any doubts or question ask them in the comments section below I team of experts will reply you as soon as possible thank you and keep learning with simple learn staying ahead 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