1. Data Orchestration: ADF enables you to create and manage data pipelines to move and process data between various data stores, such as Azure Blob Storage, Azure SQL Database, Azure Data Lake Storage, SQL Server, and more.

2. Data Transformation: ADF provides data transformation capabilities, allowing you to transform and manipulate data during the movement process. This can include data cleansing, data formatting, data aggregation, and other data transformations.

3. Data Integration: ADF allows you to integrate with various data sources and destinations, both within Azure and external to Azure, to bring data together in a unified and consistent way.

4. Data Movement: ADF supports moving data in batches or real-time, depending on your requirements. It can efficiently handle large volumes of data and optimize data transfer between data stores.

5. Monitoring and Management: ADF provides monitoring and logging capabilities to track the execution and health of data pipelines. It also allows you to manage and troubleshoot pipelines and activities.

6. Integration with Other Azure Services: Azure Data Factory seamlessly integrates with other Azure services, such as Azure Logic Apps, Azure Functions, Azure Databricks, and more, enabling you to create more complex data workflows and data-driven solutions.

Azure Data Factory employs a graphical user interface (GUI) to design data pipelines, making it easy for users without extensive coding knowledge to create and manage data workflows. Additionally, it supports code-based authoring using Azure Data Factory’s JSON-based language, allowing developers more flexibility and version control over their data pipeline definitions.