Master Azure Data Factory for building robust ETL pipelines, transforming data, and integrating seamlessly with Power BI to deliver impactful data solutions.
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Introduction to Data Warehousing and ETL Concepts
Unit 1: Data Warehousing Fundamentals
Unit 2: ETL Demystified
Unit 3: ETL in the Real World
Introduction to Azure Data Factory
Unit 1: ADF Overview and Core Concepts
Unit 2: Integration Runtimes and ADF UI
Unit 3: Resource Management and Navigation
Setting up your Azure Environment for ADF
Unit 1: Azure Setup Fundamentals
Unit 2: Provisioning Azure Data Factory
Unit 3: Security and Access Control
Unit 4: Setting up Azure SQL Database
Connecting to Data Sources: Linked Services
Unit 1: Linked Services Fundamentals
Unit 2: Creating and Configuring Linked Services
Unit 3: Advanced Linked Service Management
Defining Data Structures: Datasets
Unit 1: Dataset Fundamentals
Unit 2: Configuring Dataset Properties
Unit 3: Dynamic Data Access with Parameters
Building Your First Pipeline: Copy Activity
Unit 1: Introduction to Pipelines and Activities
Unit 2: Creating Your First Pipeline with Copy Activity
Unit 3: Executing and Monitoring Your Pipeline
Data Transformation Options in ADF
Unit 1: ADF Transformation Landscape
Unit 2: Deep Dive into Data Flows
Unit 3: Stored Procedures & Azure Functions
Unit 4: Choosing the Right Tool
Introduction to Data Flows
Unit 1: Data Flows: The Basics
Unit 2: Creating and Configuring Data Flows
Unit 3: Exploring Data Flow Transformations
Data Flow Transformations: Basic Operations
Unit 1: Getting Started with Data Flow Transformations
Unit 2: Filtering Data in Data Flows
Unit 3: Projecting Data in Data Flows
Unit 4: Aggregating Data in Data Flows
Unit 5: Putting It All Together
Data Flow Transformations: Joins and Lookups
Unit 1: Introduction to Joins in Data Flows
Unit 2: Advanced Join Types and Lookup Transformations
Unit 3: Advanced Lookup Techniques and Error Handling
Data Flow Transformations: Derived Columns and Expressions
Unit 1: Introduction to Derived Columns
Unit 2: Working with Expressions
Unit 3: Advanced Techniques
Data Flow Transformations: Conditional Split and Sink
Unit 1: Conditional Split Deep Dive
Unit 2: Sink Transformation Essentials
Unit 3: Advanced Sink Configuration
Data Flow Debugging and Monitoring
Unit 1: Data Flow Debugging Fundamentals
Unit 2: Advanced Debugging Techniques
Unit 3: Monitoring and Performance
Using Stored Procedure Activity for Transformations
Unit 1: Introduction to Stored Procedure Activity
Unit 2: Configuring Stored Procedure Activity
Unit 3: Passing Parameters and Handling Output
Unit 4: Advanced Scenarios and Error Handling
Unit 5: Performance and Best Practices
Implementing Data Transformations with Stored Procedures
Unit 1: Stored Procedure Fundamentals for ADF
Unit 2: Data Transformation Techniques in Stored Procedures
Unit 3: Performance Optimization and Error Handling
Using Azure Function Activity for Transformations
Unit 1: Azure Functions Activity Fundamentals
Unit 2: Configuring Azure Function Activity in ADF
Unit 3: Advanced Scenarios and Best Practices
Implementing Data Transformations with Azure Functions
Unit 1: Azure Functions for Data Transformation: Core Concepts
Unit 2: Data Transformation Techniques with Azure Functions
Unit 3: Integrating Azure Functions with ADF and Optimizing Performance
Choosing Between Data Flows, Stored Procedures, and Azure Functions
Unit 1: Understanding Transformation Options
Unit 2: Performance and Scalability
Unit 3: Choosing the Right Tool
Incremental Data Loading: Introduction
Unit 1: Understanding Incremental Loading
Unit 2: Techniques for Incremental Loading
Unit 3: Choosing the Right Technique
Incremental Data Loading: Using Watermark Columns
Unit 1: Watermark Column Fundamentals
Unit 2: Implementing Watermark Loading in ADF
Unit 3: Advanced Watermark Techniques
Incremental Data Loading: Change Data Capture (CDC)
Unit 1: Understanding Change Data Capture (CDC)
Unit 2: Configuring CDC in Azure SQL Database
Unit 3: Implementing CDC with Azure Data Factory
Parameterization and Dynamic Pipelines
Unit 1: Introduction to Parameterization
Unit 2: Parameterizing Datasets and Linked Services
Unit 3: Dynamic Pipelines and Advanced Techniques
Variables and Expressions in ADF
Unit 1: Introduction to Variables in ADF
Unit 2: Working with Expressions in ADF
Unit 3: Advanced Variable and Expression Techniques
Control Flow Activities: ForEach and If Condition
Unit 1: ForEach Activity Deep Dive
Unit 2: If Condition Activity Explained
Unit 3: Advanced Control Flow Scenarios
Error Handling and Logging
Unit 1: Error Handling Fundamentals
Unit 2: Proactive Error Prevention
Unit 3: Reactive Error Handling
Unit 4: Logging and Monitoring
Unit 5: Putting It All Together
Monitoring and Alerting
Unit 1: Introduction to Monitoring and Alerting in ADF
Unit 2: Setting Up Alerts in Azure Data Factory
Unit 3: Azure Monitor Integration
Data Governance and Security: Access Control
Unit 1: Understanding Access Control in ADF
Unit 2: Implementing Access Control
Unit 3: Managed Identities
Data Governance and Security: Data Masking and Encryption
Unit 1: Data Masking Fundamentals
Unit 2: Encryption Fundamentals
Unit 3: Azure Key Vault Integration
Unit 4: Compliance and Best Practices
Performance Optimization: General Strategies
Unit 1: Understanding ADF Performance
Unit 2: Optimizing Data Handling
Unit 3: Integration Runtime and Monitoring
Performance Optimization: Copy Activity
Unit 1: Understanding Copy Activity Performance
Unit 2: Tuning Copy Activity Settings
Unit 3: Parallel Copy and Advanced Techniques
Performance Optimization: Data Flows
Unit 1: Understanding Data Flow Performance
Unit 2: Transformation Optimization Techniques
Unit 3: Advanced Optimization and Partitioning
Cost Optimization: General Strategies
Unit 1: Understanding ADF Cost Drivers
Unit 2: Optimizing Pipeline Design for Cost
Unit 3: Integration Runtime Optimization
Cost Optimization: Integration Runtime
Unit 1: Understanding Integration Runtimes
Unit 2: Azure Auto-Resolve IR
Unit 3: Self-Hosted IR
Unit 4: Scaling and Performance
Unit 5: Cost Optimization Strategies
ADF and Power BI: Data Refresh Strategies
Unit 1: Power BI Refresh Fundamentals
Unit 2: ADF Integration for Power BI Refresh
Unit 3: Incremental Refresh Strategies
ADF and Power BI: DirectQuery Considerations
Unit 1: DirectQuery Fundamentals
Unit 2: Connecting Power BI to ADF Data
Unit 3: Optimizing ADF for DirectQuery
Connecting ADF to Power BI: End-to-End Example
Unit 1: End-to-End Integration Overview
Unit 2: Building the ADF Pipeline
Unit 3: Data Transformation (Stored Procedure)
Unit 4: Power BI Integration and Security
Source Control Integration with Azure DevOps
Unit 1: Introduction to Source Control and Azure DevOps
Unit 2: Setting up Git and Azure DevOps
Unit 3: Integrating ADF with Azure DevOps Git
Unit 4: CI/CD for ADF
CI/CD for ADF: Automated Deployments
Unit 1: Introduction to CI/CD for ADF
Unit 2: Setting up the CI/CD Pipeline
Unit 3: Advanced CI/CD Techniques
Unit 4: Best Practices and Troubleshooting
Testing ADF Pipelines
Unit 1: Introduction to ADF Pipeline Testing
Unit 2: Setting Up Your Testing Environment
Unit 3: Writing Unit Tests for ADF Pipelines
Unit 4: Automating Testing and CI/CD
Unit 5: Advanced Testing Techniques
Data Lineage and Impact Analysis
Unit 1: Understanding Data Lineage
Unit 2: Leveraging ADF's Monitoring Capabilities
Unit 3: Implementing Custom Data Lineage Tracking
Unit 4: Performing Impact Analysis
Advanced Data Flow Techniques
Unit 1: Advanced Data Flow Transformations
Unit 2: Custom Expressions and Functions
Unit 3: Data Quality and Validation
Working with REST APIs in ADF
Unit 1: Introduction to REST API Integration in ADF
Unit 2: Authentication Methods
Unit 3: Parsing JSON Responses
Unit 4: Advanced REST API Integration
Handling Complex Data Types
Unit 1: Working with JSON Data in ADF
Unit 2: Parsing JSON Data with Data Flows
Unit 3: Working with XML Data in ADF
Integrating ADF with Azure Logic Apps
Unit 1: Logic Apps & ADF: The Basics
Unit 2: Triggering ADF Pipelines from Logic Apps
Unit 3: Advanced Logic Apps & ADF Integration
Unit 4: Real-World Scenarios & Best Practices
Real-time Data Ingestion with ADF
Unit 1: Introduction to Real-Time Data Ingestion
Unit 2: Capturing Data with Azure Event Hubs
Unit 3: Building Real-Time Pipelines with ADF
Unit 4: Near Real-Time Analytics and Considerations
Best Practices for ADF Development
Unit 1: Pipeline Design Principles
Unit 2: Coding Standards and Naming Conventions
Unit 3: Documentation and Maintainability
Troubleshooting Common ADF Issues
Unit 1: Introduction to Troubleshooting ADF Pipelines
Unit 2: Using the ADF Monitoring Dashboard
Unit 3: Troubleshooting Common Connectivity Issues
Unit 4: Troubleshooting Data Transformation Issues
Unit 5: Leveraging Documentation and Community
ADF and Data Lake Storage
Unit 1: Introduction to Azure Data Lake Storage Gen2
Unit 2: Connecting ADF to ADLS Gen2
Unit 3: Copying Data to and from ADLS Gen2
Unit 4: Data Flows and ADLS Gen2
Unit 5: Data Lake Patterns with ADF
Unit 6: Performance Optimization and Best Practices
Migrating Existing ETL Processes to ADF
Unit 1: Assessing Your Current ETL Landscape
Unit 2: Planning Your ADF Migration
Unit 3: Implementing and Validating the Migration
Unit 4: Post-Migration Activities
Advanced Security Considerations
Unit 1: Network Security for ADF
Unit 2: Private Endpoints for Secure Data Access
Unit 3: Data Loss Prevention (DLP) Measures
Unit 4: Compliance with Industry Security Standards
Scaling ADF for Large Datasets
Unit 1: Understanding Large Datasets in ADF
Unit 2: Scaling Integration Runtimes
Unit 3: Parallel Processing Techniques
Unit 4: Optimizing Data Partitioning
Unit 5: Monitoring and Tuning
Automating ADF Pipeline Management
Unit 1: Introduction to ADF Automation
Unit 2: Automating with PowerShell
Unit 3: Automating with Azure CLI
Unit 4: Infrastructure as Code (IaC) with ARM Templates
Unit 5: Streamlining ADF Operations
Future Trends in ADF and ETL
Unit 1: The Evolving Landscape of ETL
Unit 2: New Features and Capabilities in ADF
Unit 3: Industry Best Practices and the Future of Data Integration
