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Azure Data Factory (ADF) is a cloud-based data integration service that allows you to create, schedule, and manage data pipelines for ingesting, preparing, transforming, and orchestrating data across various sources and destinations. It provides a visual interface for building data workflows and supports a wide range of data integration scenarios.

Key features of Azure Data Factory include:

Data Integration: ADF supports data integration from various sources such as Azure Blob Storage, Azure SQL Database, Azure Synapse Analytics, SQL Server, Oracle, Salesforce, and many others. It allows you to ingest both structured and unstructured data.

Data Transformation: ADF provides data transformation capabilities through mapping data flows, which enable you to visually design data transformation logic using a drag-and-drop interface. It supports various transformation operations such as join, aggregate, derive column, and more.

Data Movement: ADF enables data movement between different data stores efficiently and reliably. It supports batch data movement as well as real-time data movement using change data capture (CDC) mechanisms.

Orchestration: ADF allows you to orchestrate complex data workflows by chaining together multiple activities such as copy data, transform data, execute stored procedure, and more. You can schedule workflows to run at specific times or trigger them based on events.

Monitoring and Management: ADF provides monitoring and management capabilities to track the performance and health of your data pipelines. You can monitor pipeline runs, view execution logs, and troubleshoot issues using built-in monitoring tools and dashboards.

Integration with Other Azure Services: ADF seamlessly integrates with other Azure services such as Azure Data Lake Storage, Azure Synapse Analytics, Azure SQL Database, Azure Databricks, Azure Key Vault, and more, allowing you to leverage the full power of the Azure ecosystem for your data integration needs.