Explore Azure Databricks

Topics

• Get Started with Azure Databricks
• Identify Azure Databricks Workloads
• Understand Key Concepts
• Data Governance Using Unity Catalog and Microsoft Purview

Labs / Practice

• Explore Azure Databricks

Understand Azure Databricks Architecture

Topics

• Understand Azure Databricks Architecture
• Understand Unity Catalog Managed Storage
• Understand External Storage
• Understand Default Storage (Serverless Compute)

Understand Azure Databricks Integrations

Topics

• Integration with Microsoft Fabric
• Integration with Power BI
• Integration with VS Code
• Integration with Power Platform
• Integration with Copilot Studio
• Integration with Microsoft Purview
• Integration with Microsoft Foundry

Select and Configure Compute in Azure Databricks

Topics

• Choose an Appropriate Compute Type
• Configure Compute Performance
• Configure Compute Features
• Install Libraries for Compute
• Configure Compute Access

Labs / Practice

• Select and Configure Compute in Azure Databricks

Create and Organize Objects in Unity Catalog

Topics

• Apply Naming Conventions
• Create Catalog
• Create Schema
• Create Tables and Views
• Create Volumes
• Implement DDL Operations
• Implement Foreign Catalog
• Configure AI/BI Genie Instructions

Labs / Practice

• Create and Organize Objects in Unity Catalog

Secure Unity Catalog Objects

Topics

• Understand Query Lifecycle
• Implement Access Control Strategies
• Understand Fine-Grained Access Control
• Implement Row Filtering and Column Masking
• Access Azure Key Vault Secrets
• Authenticate Data Access with Service Principals
• Authenticate Resource Access with Managed Identities

Labs / Practice

• Secure Unity Catalog Objects

Govern Unity Catalog Objects

Topics

• Create and Preserve Table Definitions
• Configure ABAC with Tags and Policies
• Apply Data Retention Policies
• Set Up and Manage Data Lineage
• Configure Audit Logging
• Design Secure Delta Sharing Strategy

Labs / Practice

• Govern Unity Catalog Objects

Design and Implement Data Modeling with Azure Databricks

Topics

• Design Ingestion Logic and Data Source Configuration
• Choose a Data Ingestion Tool
• Choose a Data Table Format
• Design and Implement a Data Partitioning Scheme
• Choose a Slowly Changing Dimension (SCD) Type
• Implement a Slowly Changing Dimension (SCD) Type 2
• Design and Implement a Temporal (History) Table to Record Changes over Time
• Choose Granularity on a Column or Table Based on Requirements
• Choose Managed vs. Unmanaged Tables
• Design and Implement a Clustering Strategy

Labs / Practice

• Design and Implement Data Modeling with Azure Databricks

Ingest Data into Unity Catalog

Topics

• Ingest Data with Lakeflow Connect
• Ingest Data with Notebooks
• Ingest Data with SQL Methods
• Ingest Data with CDC Feed
• Ingest Data with Spark Structured Streaming
• Ingest Data with Auto Loader
• Ingest Data with Lakeflow Spark Declarative Pipelines

Labs / Practice

• Ingest Data into Unity Catalog

Cleanse, Transform, and Load Data into Unity Catalog

Topics

• Profile Data
• Choose Column Data Types
• Resolve Duplicates and Nulls
• Transform Data with Filters and Aggregations
• Transform Data with Joins and Set Operators
• Transform Data with Denormalization and Pivots
• Load Data with Merge, Insert, and Append

Labs / Practice

• Cleanse, Transform, and Load Data into Unity Catalog

Implement and Manage Data Quality Constraints with Azure Databricks

Topics

• Implement Validation Checks
• Implement Data Type Checks
• Detect and Manage Schema Drift
• Manage Data Quality with Pipeline Expectations

Labs / Practice

• Implement and Manage Data Quality Constraints with Azure Databricks

Design and Implement Data Pipelines with Azure Databricks

Topics

• Design Order of Operations for a Pipeline
• Choose Notebook vs. Lakeflow Pipelines
• Design Lakeflow Job Logic
• Design Error Handling in Pipelines and Jobs
• Create Pipeline with Notebook
• Create Pipeline with Lakeflow Spark Declarative Pipelines

Labs / Practice

• Design and Implement Data Pipelines with Azure Databricks

Implement Lakeflow Jobs with Azure Databricks

Topics

• Create Job Setup and Configuration
• Configure Job Triggers
• Schedule a Job
• Configure Job Alerts
• Configure Automatic Restarts

Labs / Practice

• Implement Lakeflow Jobs with Azure Databricks

Implement Development Lifecycle Processes in Azure Databricks

Topics

• Apply Git Version Control Best Practices
• Manage Branching and Pull Requests
• Implement Testing Strategy
• Configure and Package DABs
• Deploy Bundle with Databricks CLI

Labs / Practice

• Implement Development Lifecycle Processes in Azure Databricks

Monitor, Troubleshoot, and Optimize Workloads in Azure Databricks

Topics

• Monitor and Manage Cluster Consumption
• Troubleshoot and Repair Lakeflow Jobs
• Troubleshoot Spark Jobs and Notebooks
• Investigate Caching, Skewing, Spilling, and Shuffle
• Implement Log Streaming with Azure Log Analytics

Labs / Practice

• Monitor, Troubleshoot, and Optimize Workloads in Azure Databricks