Course Outline:
Module 1: Introduction to Azure Data Factory
- Understanding data integration and ETL
- Overview of Azure Data Factory
- Key features and benefits
Module 2: Azure Data Factory Components
- Data pipelines
- Datasets
- Linked services
- Triggers
- Integration Runtimes
Module 3: Data Movement and Copy Activities
- Data movement concepts
- Creating copy pipelines
- Data movement best practices
- Monitoring and managing copy activities
Module 4: Data Transformation with Data Flow
- Introduction to Data Flow
- Data Flow components
- Building data transformation pipelines
- Debugging and testing Data Flows
Module 5: Data Orchestration and Control Flow
- Control Flow concepts
- Building control flow pipelines
- Conditional activities
- Error handling strategies
Module 6: Data Integration with Azure Services
- Integration with Azure SQL Database
- Integration with Azure Data Lake Storage
- Integration with Azure Synapse Analytics
- Integration with other Azure services
Module 7: Security and Data Compliance
- Data encryption and security best practices
- Azure Data Factory Managed Virtual Network
- Data compliance and governance
Module 8: Monitoring and Performance Optimization
- Monitoring pipelines and activities
- Using Azure Monitor and Azure Log Analytics
- Performance optimization techniques
Module 9: Real-world Use Cases and Best Practices
- Industry-specific case studies
- Best practices for large-scale data integration
- Tips for cost optimization
Module 10: Final Project and Certification
- Hands-on project using Azure Data Factory
- Certification exam preparation
- Course completion and certification
Prerequisites:
- Basic knowledge of data concepts
- Familiarity with Microsoft Azure is a plus but not required
Who Should Enroll:
- Data engineers
- Data analysts
- Business intelligence professionals
- Anyone interested in mastering Azure Data Factory