Description:

This advanced course on Microsoft Azure Data Factory takes a deep dive into the various features and functionalities of the platform, providing hands-on labs to help you gain practical experience. Learn how to design data workflows, create data pipelines, and automate data integration processes using Azure Data Factory. Dive into advanced topics such as data transformation, monitoring, and optimization techniques to enhance your data engineering skills.

Key Highlights:

• Advanced Azure Data Factory insights
• Hands-on labs for practical experience
• Data workflow design and automation
• Optimization and monitoring techniques

What you will learn:

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  Section 1: Introduction to Azure Data Factory

• Overview of Azure Data Factory (ADF)
• Understanding ADF components and architecture
• Key features and capabilities of ADF
• Hands-on Lab: Setting up an Azure Data Factory instance

• Section 2: Data Ingestion

• Data ingestion concepts in ADF
• Connecting to various data sources (Azure Blob Storage, Azure SQL Database, etc.)
• Creating datasets and linked services
• Hands-on Lab: Ingesting data from multiple sources into ADF

• Section 3: Data Transformation

• Introduction to data transformation in ADF
• Using Mapping Data Flows for ETL processes
• Transforming and cleaning data using ADF activities
• Hands-on Lab: Implementing data transformations with Mapping Data Flows

• Section 4: Data Orchestration

• Understanding data orchestration and workflow management
• Creating pipelines and activities in ADF
• Monitoring and managing pipeline executions
• Hands-on Lab: Building and scheduling data pipelines

• Section 5: Data Integration and Movement

• Overview of data integration capabilities in ADF
• Using copy activities for data movement
• Working with Azure Synapse Analytics integration
• Hands-on Lab: Integrating data across different platforms with ADF

• Section 6: Monitoring and Management

• Monitoring and logging in Azure Data Factory
• Implementing alerting and notifications
• Best practices for managing ADF pipelines and resources
• Hands-on Lab: Setting up monitoring and alerts for ADF pipelines

• Section 7: Advanced Topics and Use Cases

• Introduction to advanced ADF features (such as parameterization, expressions)
• Data security and compliance considerations in ADF
• Real-world use cases and scenarios
• Hands-on Lab: Implementing parameterization and security features in ADF

• Section 8: Integration with Other Azure Services

• Integration of ADF with Azure Databricks, Azure Machine Learning, etc.
• Leveraging Azure Data Factory for modern data architecture
• Hands-on Lab: Building end-to-end data solutions using ADF and other Azure services

• Section 9: Optimization and Performance Tuning

• Performance optimization techniques for ADF pipelines
• Understanding scalability and resource utilization
• Hands-on Lab: Optimizing and tuning ADF pipelines for efficiency

• Section 10: Capstone Project

• Final project to apply all learned concepts
• Design and implement a comprehensive data solution using Azure Data Factory
• Presentation and review of the project