New Dataflow Gen2 data destinations and experience improvements
A new set of enhancements to Dataflow Gen2 in Microsoft Fabric significantly expands data integration and collaboration capabilities—enabling broader connectivity and streamlined workflows across teams. These updates are designed to meet the evolving needs of data professionals by offering more flexible destinations, schema support, and tighter integration with enterprise-grade platforms.
Expanding Where Your Data Can Go
One of the most impactful changes is the addition of new data destinations. With Lakehouse Files, Snowflake and ADLS Gen2 (Preview), and SharePoint (Generally Available), users can choose the most appropriate landing zone for their data.
SharePoint (Generally Available) now offers a seamless way to publish structured data into collaborative environments. This opens up low-code scenarios where business users can interact with data through familiar interfaces, automate workflows, and build reports without needing deep technical expertise.
Snowflake (Sneak Peek) Dataflow Gen2 will support soon writing to Snowflake, allowing organizations to operationalize data pipelines across Fabric and Snowflake environments. This unlocks cross-platform scenarios where Fabric and Snowflake is used together for data preparation, orchestration, and serving results for your Power BI report. Expect the Snowflake destination shows up soon as a new destination you can now write to!
ADLS Gen2 (Preview) brings scalable, secure data lake integration to Dataflow Gen2. Valuable for organizations managing large volumes of structured and unstructured data. It supports centralized ingestion pipelines and staging areas for transformation, while aligning with Azure’s governance and access control frameworks.
Lakehouse Files (Preview) introduces the ability to write directly to CSV files into your Lakehouse for further procession. A game-changer for teams working with Spark, Python, or other open-source tools. It enables raw data access for machine learning workflows.
For Lakehouse files we integrated a smart way to switch between files and tables, simply use the existing Lakehouse connector and switch to new file mode right away when you are browsing your workspaces.
Database Schema Support
A key improvement in this release is the ability to define and manage schemas within databases, specifically for Lakehouse Tables, Fabric Warehouse, and Fabric SQL Databases. Giving users the ability to create structured schemas within their databases to better organize and manage their data assets.
This feature allows teams to group related tables, enforce naming conventions, and apply governance policies more effectively. It supports modular design, improves discoverability, and simplifies permission management by enabling schema-level access controls.
For example, a product team might create separate schemas for operational data, reference data, and analytics outputs each with its own structure and access rules. This level of organization is essential for scaling data solutions across departments and ensuring consistency in enterprise environments.
To leverage this new feature, make sure you enable ‘Navigate using full hierarchy’ setting when you setup your connection. When this is enabled, you will automatically be able to select the schema as your destination for your table.
Unlocking New Scenarios
Lakehouse-first data science workflows: Teams can now land feature sets directly into Lakehouse Files, enabling Spark-based model training and experimentation without the need of maintaining and optimizing for the delta lake format.
Hybrid Lakehouse and warehouse architectures: With ADLS Gen2 support, organizations can ingest data into Fabric while maintaining compatibility with existing Azure data lakes, supporting phased migrations and hybrid analytics strategies.
Collaborative reporting and automation: SharePoint integration allows Fabric data to drive business processes, approvals, and reporting workflows in Microsoft 365, bridging the gap between data engineering and business operations.
Enterprise-grade modeling: Schema support enables structured, governed database design within Fabric, supporting semantic modeling for Power BI, schema-level access control, and standardized data architecture across teams.
Looking Ahead
These improvements reflect our commitment to making Microsoft Fabric the most versatile and enterprise-ready data integration platform. We’re continuing to invest in capabilities that simplify data movement, enhance modeling, and empower users across technical and business roles.
We encourage you to explore these new features and share your feedback. If you’re interested in deeper integration scenarios or want to see how these updates can support your team’s workflows, we’d be happy to help.
To learn more about these features, refer to the Dataflow Gen2 data destinations and managed settings documentation.
