External data sharing enhancements out now
It’s been almost a year since we announced the external data sharing in preview at Fabric Conference 2024, and later that year it was made generally available at Ignite 2024. We’ve listened to customer feedback and have continued to improve the functionality of external data sharing. Many new feature enhancements have been delivered since the beginning of the year – this post elaborates on those features.
External data sharing enables Fabric users to seamlessly share data across tenant boundaries while maintaining a single logical copy. This is invaluable for businesses that collaborate with suppliers, customers, partners, or consultants, as it allows for efficient and secure data sharing without duplicating data. The shared data remains read-only for the consumer, ensuring data integrity and consistency.
Creating external data shares is straightforward. Navigate to the item you wish to share—be it a Lakehouse, Mirrored database, or KQL Database—in your workspace or OneLake catalog. From the context menu, select ‘External data share’. Choose the folder or table to share, enter the recipient’s email address, and send the invite. The recipient can then accept the share and access the data within their own tenant, allowing for effortless and effective collaboration.
Multiple table support
We have enhanced the External data sharing capability to now support multiple tables and folders. External data sharing was originally released with the capability to share a single folder or table. We heard your feedback requesting support for multiple tables and added support for sharing multiple tables together in a single share.
Lakehouse schema support
It is also possible to share an entire Lakehouse schema in a single share. Sharing a Lakehouse schema shares all the tables in the schema, and any changes to the schema are immediately reflected in the consumer’s Lakehouse. Data providers can add or remove tables from the schema, and these changes will immediately be available for the consumer without any action required on their part. This contrasts with the multiple table feature mentioned above, where the data provider can select a subset of tables from a Lakehouse or Lakehouse schema, but the external share that is created does not update automatically if the provider later adds or removes tables from the schema.
Consume shared data via SQL analytics endpoints and Semantic models
In the previous releases of external data shares, data could only be consumed by Spark workloads such as Notebooks or Spark jobs. Externally shared tables can now be consumed via Lakehouse SQL Analytics Endpoint and Semantic models. This means that data can be shared from a provider and consumed in-place via SQL queries or in a Power BI report built on top of the consumer’s Lakehouse.
Share data from KQL and SQL databases
Data can now be externally shared from KQL and SQL databases. This is in addition to the already supported Lakehouse and Mirrored Database item types. 
Service principal support in external data sharing API
The external data sharing APIs now support service principals for admin and user operations. Customers who want to automate the creation or management of shares can now do this with a service principal or managed identity.
More improvements coming soon
We aren’t stopping with what we’ve just delivered, there are more features we’ll be rolling out soon.
- Data warehouse support: It will soon be possible to externally share schemas or tables from a data warehouse.
- Shortcut sharing: Long one of the most requested features, we’re happy to say that data providers will soon be able to share OneLake shortcuts using external data sharing. This means that data residing outside of Fabric in S3, ADLS Gen2, or any other supported shortcut location will be externally shareable using external data sharing.
- Consumer APIs: Consumer activities, including viewing share details and accepting shares, will soon be available via API.
For more information check out the official external data sharing documentation.
To further discuss the external data sharing and the challenges it can solve for your organization, please reach out to us at Fabric data sharing feedback, submit your feature ideas on Fabric Ideas and join the conversation on the Fabric Community.
