Introducing the New Feature in Lakehouse Connector in Fabric Data Factory: Schema Support for Reading and Writing Data
Fabric Lakehouse supports the creation of custom schemas. Schemas allow users to group tables together for better data discovery, access control, and more. This is now a Preview feature in Fabric. Learn more here.
We are excited to announce the latest enhancement in Fabric Data Factory that Lakehouse connector in data pipeline now supports schema. This new feature allows users to seamlessly read schema information from Fabric Lakehouse and write data directly into Lakehouse tables with schema information specified.
What Does This Feature Offer?
The Lakehouse connector now integrates with Lakehouse schema capability, offering both reading and writing functionalities that were previously limited. Users can directly retrieve schema information from the Fabric Lakehouse through data pipeline, ensuring that data structures are fully understood before any operations. Additionally, when writing data to Lakehouse tables, the connector now supports the inclusion of schema information, either writing to an existing schema or to a new schema.
How to Use the New Lakehouse Schema Support
When reading from Fabric Lakehouse table, schema information is now automatically included, offering an up-to-date view of the table structure. Similarly, when writing data, the connector will ensure that schema details are accurately applied, safeguarding the integrity of your tables.
For detailed instructions on how to configure it, please refer to our documentation, or explore the feature directly through Fabric Data Factory’s user interface.
Looking Ahead
At Fabric Data Factory, we are constantly innovating to improve our data integration solutions. The introduction of schema support in the Lakehouse connector is just one of many steps we are taking to empower users with the tools they need to manage data effectively.
