AZURE DATA FACTORY

INDEX:

1.Introduction to Azure Data Factory:

• Overview of Azure Data Factory and its key components.
• Understanding data integration and orchestration concepts.
• Introduction to Azure Data Factory UI and service architecture.

2. Building Data Pipelines in Azure Data Factory:

• Creating data pipelines for ingesting data from various sources (e.g., Azure Blob Storage, Azure SQL Database, on-premises systems).
• Configuring data sets, linked services, and activities in Azure Data Factory.
• Managing and monitoring data pipelines using Azure Data Factory Monitoring.

3. Data Transformation with Azure Data Factory Data Flows:

• Introduction to Azure Data Factory Data Flows for visual data transformation.
• Building data flow activities to cleanse, transform, and enrich data.
• Integrating machine learning and AI capabilities into data transformation processes.

4. Data Movement and Integration:

• Implementing efficient data movement strategies using Azure Data Factory.
• Working with data integration patterns such as batch processing, incremental loading, and change data capture.
• Real-time data integration with Azure Data Factory and event-driven architectures.

5. Advanced Data Integration Techniques:

• Handling complex data types and formats in Azure Data Factory.
• Implementing data partitioning, compression, and encryption.
• Optimizing data pipeline performance and scalability.

6. Integration with Azure Services:

• Integrating Azure Data Factory with Azure Synapse Analytics for advanced analytics and data warehousing.
• Leveraging Azure Databricks for big data processing and analytics.
• Using Azure Data Factory with Azure SQL Database and Azure Data Lake Storage for data storage and processing.

7. Data Governance and Security:

• Implementing data governance policies and practices in Azure Data Factory.
• Securing data pipelines and sensitive data in Azure Data Factory.
• Implementing compliance standards and regulations (e.g., GDPR, HIPAA) in data workflows.

8. Real-world Use Cases and Scenarios:

• Exploring real-world use cases and scenarios for Azure Data Factory in various industries and domains.
• Designing and implementing end-to-end data integration solutions using Azure Data Factory.