Databricks - Zero to Hero| Databricks With Unity Catalog | Databricks Tutorial 2025 | Databricks Training 2025 | Databricks tutorial for beginners
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What you'll learn
This course includes
- 15.3 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 54 lessons • 15.3 hours of video
Databricks - Zero to Hero| Databricks With Unity Catalog | Databricks Tutorial 2025 | Databricks Training 2025 | Databricks tutorial for beginners
54 lessons
• 15.3 hours
Databricks - Zero to Hero| Databricks With Unity Catalog | Databricks Tutorial 2025 | Databricks Training 2025 | Databricks tutorial for beginners
54 lessons
• 15.3 hours
- 01 Databricks Tutorial 2025 | Databricks for Data Engineering | Azure Databricks Training 02:12
- 02 What is Data Lakehouse & Databricks Data Intelligence Platform | Benefits of Databricks Lakehouse 10:05
- 03 Databricks High Level Architecture | Understand Control Plane & Data Plane | Roles in Databricks 08:59
- 04 Setup Databricks on Azure | Create your first Databricks Workspace | How to Databricks free trial 12:24
- 05 Understand Databricks Account Console | User Management in Databricks | Workspace Management 05:03
- 06 Databricks Workspace & Notebooks | Cell Magic commands | Version History | Comments | Variables 12:05
- 07 How Databricks work with Azure | Managed Storage Container | Databricks clusters using Azure VMs 05:51
- 08 What is Unity Catalog and Databricks Governance | What is Metastore | Unity Catalog Object Model🔥 06:53
- 09 Legacy Hive Metastore Catalog in Databricks | What are Managed Table and External Table | DBFS 11:09
- 10 Enable Unity Catalog and Setup Metastore | How to setup Unity Catalog for Databricks Workspace 08:44
- 11 Catalog, External Location & Storage Credentials in Unity Catalog |Catalog with External Location 14:54
- 12 Schemas with External Location in Unity Catalog | Managed Table data Location in Unity Catalog 11:35
- 13 Managed & External Tables in Unity Catalog vs Legacy Hive Metastore | UNDROP Tables in Databricks 10:43
- 14 Delta Tables Deep & Shallow Clones | Temporary & Permanent Views | List Catalog, Schemas & Tables 23:14
- 15 Delta Tables MERGE and UPSERTS | SCD1 in Delta | Soft Delete with Incremental data using Merge 14:10
- 16 Delta Tables Liquid Clustering and Deletion Vectors | Optimize Delta Tables | Delta Clustering 12:53
- 17 Volumes - Managed & External in Databricks | Volumes in Databricks Unity Catalog |Files in Volume 11:59
- 18 DBUTILS command | Databricks Utilities | Create Widgets in Databricks Notebooks |DBUTILS FS usage 12:41
- 19 Orchestrating Notebook Jobs, Schedules using Parameters | Run Notebook from another Notebook 13:51
- 20 Databricks Computes - All Purpose & Job | Access Modes | Cluster Policies | Cluster Permissions 17:14
- 21 Custom Cluster Policy in Databricks | Create Instance Pools | Warm Instance Pool 13:48
- 22 Workflows, Jobs & Tasks | Pass Values within Tasks | If Else Cond | For Each Loop & Re-Run Jobs 25:15
- 23 Databricks COPY INTO command | COPY INTO Metadata | Idempotent Pipeline | Exactly Once processing 14:51
- 24 Auto Loader in Databricks | AutoLoader Schema Evolution Modes | File Detection Mode in AutoLoader 23:04
- 25 Medallion Architecture in Data Lakehouse | Use of Bronze, Silver & Gold Layers 03:09
- 26 DLT aka Delta Live Tables | DLT Part 1 | Streaming Tables & Materialized Views in DLT pipeline 22:41
- 27 DLT Internals & Incremental load | DLT Part 2 | Add or Modify columns| Rename table| Data Lineage 13:33
- 28 DLT Append Flow(Union) & Autoloader | Pass parameter in DLT pipeline |Generate tables dynamically 17:50
- 29 DLT SCD2 & SCD1 table | Apply Changes | CDC | Back loading SCD2 table | Delete/Truncate SCD table 20:10
- 30 DLT Data Quality & Expectations | Monitor DLT pipeline using SQL | Define DQ rule |Observability 17:57
- 31 DLT Truncate Load Source | Workflow File Arrival Triggers | Full Refresh | Schedule DLT pipelines 11:16
- 32 Databricks Secret Management & Secret Scopes | Save secrets in Databricks |Use of Azure Key Vault 14:10
- 33 User Management in Databricks | How to add Users, Service Principal & Groups in Unity Catalog 17:34
- 34 Object Level Security or Permissions in Unity Catalog | Manage Object Privileges in Unity Catalog 20:41
- 35 Functions in Unity Catalog using Databricks SQL | SCALAR and TABLE User Defined Functions 16:28
- 36 Row Level Filters in UC | Filter Sensitive Data in Unity Catalog table using Row Level Security 20:17
- 37 Column Level Masking in UC | Mask Sensitive Column in Unity Catalog table using Column Masking 16:15
- 38 Workspace Catalog Binding in Unity Catalog in Databricks | Limit Catalog Access | Share Catalog 10:39
- 39 Delta Sharing in Databricks | Databricks Express Edition | Share Data outside your Organization 12:38
- 40 Serverless Compute for Notebooks, Jobs, DLT, ML and Warehouses | Architecture of Serverless 13:05
- 41 Data Warehousing using DBSQL | SQL Warehouses on Databricks | SQL Query Performance Tuning 16:18
- 42 Streaming Tables and Materialized Views in DBSQL | Background Working | Schedule data Refresh 21:16
- 43 Lakehouse Federation or Query Federation in Databricks | Query External Database |Foreign Catalog 10:46
- 44 Databricks SQL Alerts | Configure Alert Schedule and Destinations 10:11
- 45 Metric Views in Databricks Unity Catalog | Design Semantic Model | Measures and Attributes 29:32
- 46 AIBI Dashboards & Visualizations | Consumer Access in Databricks | Forecasting Reports 35:48
- 47 AIBI Genie Space in Databricks | Use Natural Language to Query data 17:16
- 48 Databricks GIT Folders | Configure GIT repository with Databricks using Azure DevOps Repo 12:50
- 49 Databricks CLI | Install and Authenticate Databricks CLI | U2M and M2M Authentication 15:36
- 50 Databricks Asset Bundles | Configure Production grade DABs | CICD using DABs (IAC) 49:21
- 51 Setup Azure DevOps Pipeline with Databricks Asset Bundles (DABs) | Complete CICD Process 27:26
- 52 Lakeflow Spark Declarative Pipelines | New Pipeline Code Editor | AUTO CDC |External Target Sinks 35:38
- 53 Lakeflow Connect SQL Server Managed Connector | Ingest Data using Databricks native connectors 47:36
- 54 Zerobus Ingest Lakeflow Standard Connector | Ingest Streaming data directly into Delta Table 33:50
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