Lesson 22 – Quick overview on Dataflow Gen2 connectors

Data integration and transformation are essential tasks for any data-driven organization. However, they can also be complex and time-consuming, especially when dealing with data from different sources and formats. That’s why you need Dataflow Gen2 connectors. In this blog post, we will give you a quick overview of Dataflow Gen2 connectors and their key features.

Dataflow Gen2 connectors

Dataflow Gen2 is a set of connectors within Microsoft Azure Data Factory designed to simplify data access and transformation from diverse sources. Integral to the Dataflow Gen2 framework, these connectors play a crucial role in efficiently managing and organizing data within the Microsoft Azure environment, offering streamlined data integration and transformation capabilities

Key features of dataflow gen2 connectors

• Seamless Data Access and Transformation – Dataflow Gen2 connectors enable smooth access and transformation of data from various sources within Microsoft Azure Data Factory.
• Efficient Management – These connectors serve as essential components for managing and organizing data effectively.
• Integration with Data Pipelines – Dataflow Gen2 connectors seamlessly integrate with data pipelines, ensuring a cohesive data processing architecture.
• High-Scale Compute – The connectors support high-scale compute capabilities, accommodating the processing needs of large datasets.
• Monitoring and History Features – Improved monitoring and refresh history features provide users with better visibility into data transformation processes, contributing to enhanced data management.
• Incremental Refresh Support – Supports incremental refresh, refreshing only the changed data since the last update instead of the entire dataflow. This feature enhances performance and efficiency during dataflow refreshes.
• Wide Data Source Support – Supports diverse data sources, including Access Database, Adobe Analytics, Amazon Athena, Azure Analysis Services, Azure Blob Storage, Azure Cosmos DB, Azure Data Lake Storage Gen2, Azure Synapse Analytics, Common Data Service, Dynamics 365, Excel workbook, Google Analytics, Google BigQuery, Google Sheets, and more.
• Flexible Data Destinations – Allows users to specify data destinations like Fabric Lakehouse, Azure Data Explorer, Azure Synapse Analytics, Azure SQL Database, enabling separation of ETL logic and destination storage for optimized data management across various data stores.

Dataflow Gen2 connectors in Microsoft Fabric

The table below provides a comprehensive list of all currently available connectors for Data Factory Dataflow Gen2 within Microsoft Fabric.