Google Cloud End to End Data Engineering Projects - Apache Flink For Analytics | End to End Data Engineering Project

Master End-to-End Data Engineering: Real-Time Streaming, AI Integrations, and High-Performance Systems! Dive into hands-on projects, expert-guided tutorials, and cutting-edge technologies for a standout career in data engineering.

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25 learners

What you'll learn

Understand and implement real-time streaming with Google Cloud for data engineering projects
Learn how to perform real-time socket streaming using Apache Spark
Master the use of Apache Airflow alongside Spark, Pyspark, Java, and Scala for data engineering
Develop skills to build and optimize high-performance, real-time analytics databases

This course includes

47.5 hours of video
Certificate of completion
Access on mobile and TV

Summary

Keywords

Apache Flink Data Engineering Big Data Real-Time Data Processing Data Transformation Data Analysis Flink Tutorial Flink for Beginners Data Analytics Tutorial Java End to End Data Engineering Projects data engineering tutorials

Full Transcript

In this video you will setup end-to-end data engineering project for Sales Analytics using Apache Flink, a leading framework for big data processing. 🔍 What You'll Learn: ✅ Apache Flink Basics: Get to grips with the fundamentals of Apache Flink, a powerful open-source stream processing framework. ✅ Data Ingestion and Processing: Learn how to ingest and process sales data from CSV files using Flink's DataSet API. ✅ Complex Data Transformations: Understand how to perform joins, aggregations, and sorting on large datasets. ✅ Custom Output Formats: See how to create custom output formats to write processed data back to the file system. 👨‍💻 In This Tutorial: We've developed a real-world example of a Flink application that performs comprehensive sales analysis. The application reads sales and product data, joins these datasets, and computes total sales per category. It then sorts the results and writes them back to a CSV file, showcasing the power and ease of handling big data with Flink. 📝 Key Concepts Covered: 👉 Reading CSV data into Flink 👉 Using POJOs for data representation 👉 Joining datasets on key fields 👉 Aggregating data with map and reduce functions 👉 Sorting data in descending order of sales 👉 Writing custom output formats 💡 Perfect For: 👍🏻 Data Engineers and Analysts looking to enhance their big data processing skills. 👍🏻 Beginners in Apache Flink eager to learn through practical examples. 👍🏻 Anyone interested in understanding how sales data can be analyzed and processed in a big data environment. 🔗 Source Code: Get the full source code of the project here: https://github.com/airscholar/ApacheFlink-SalesAnalytics Medium Article: https://medium.com/@yusuf.ganiyu/apache-flink-for-sales-analytics-end-to-end-data-engineering-db7a737f6f43 📚 Pre-Requisites: Basic understanding of Java programming and familiarity with concepts of big data and data processing. 🎥 Stay Tuned: Subscribe to our channel for more tutorials on Apache Flink and other big data technologies. Hit the bell icon to get notified about our latest updates! 👍 Like, Share, and Comment: Enjoyed this tutorial? Like and share the video with your friends and colleagues. Have questions or suggestions? Drop them in the comments section below! 🔗 Follow Us: Website: datamasterylab.com LinkedIn: https://www.linkedin.com/in/yusuf-ganiyu-b90140107 Twitter: https://twitter.com/datamasterylab My Twitter: https://twitter.com/YusufOGaniyu #ApacheFlink #DataEngineering #SalesAnalytics #BigData #FlinkTutorial #DataProcessing #RealTimeAnalytics