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What is Azure Data Factory (ADF)?

Updated: 3/25/2024
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Azure Data Factory (ADF) is a cloud-based data integration service provided by Microsoft Azure. It enables you to create, schedule, and orchestrate data workflows to move, transform, and process data across various sources and destinations. ADF allows you to build data pipelines to ingest data from disparate sources, transform it, and then load it into data lakes, data warehouses, or other storage systems for analytics and reporting purposes.

Key features of Azure Data Factory include:

  1. **Data Movement**: ADF supports data movement between various on-premises and cloud-based data sources such as Azure Blob Storage, Azure SQL Database, Azure Data Lake Storage, Azure Synapse Analytics (formerly known as Azure SQL Data Warehouse), and many others.

  2. **Data Transformation**: ADF provides data transformation capabilities using mapping data flows, allowing you to perform data wrangling, cleansing, enrichment, and aggregation operations within the data pipelines.

  3. **Orchestration**: You can orchestrate complex data workflows by defining dependencies between activities, scheduling pipeline executions, and monitoring pipeline runs.

  4. **Integration with Azure Services**: ADF integrates seamlessly with other Azure services such as Azure Databricks, Azure Machine Learning, Azure Functions, and more, enabling you to leverage the capabilities of these services within your data pipelines.

  5. **Monitoring and Management**: ADF offers monitoring dashboards and diagnostic logs to track pipeline executions, monitor performance, and troubleshoot issues.

  6. **Security and Compliance**: It provides robust security features such as data encryption, role-based access control (RBAC), and compliance certifications to ensure data privacy and regulatory compliance.

Overall, Azure Data Factory simplifies the process of building and managing data pipelines for organizations, allowing them to efficiently ingest, transform, and process data at scale in the cloud.

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