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Hi eveyone,
I'm following this instruction to connect semantic model from Workspace A using VNET Data Gateway to Workspace B, Workspace has Data Warehouse and it is protected with Private Link (public access disabled): Set Up a Virtual Network Gateway to Access a Lakehouse from Power BI - Microsoft Fabric | Microsoft ... - Access inbound restricted lakehouse data from Power BI by using a virtual network gateway.
I used as recommended Azure SQL connector and DW SQL Analytics end point. Both workspaces and Gateway running on Fabric Capacity F8.
I used web authoring to create semantic model that in Transform (Power Query) view connect to Data Warehouse and I can see the data and apply transformations BUT when I close Transform window and click refresh I get this error:
Any ideas how to fix?
Solved! Go to Solution.
Resolved: issue was in F8, for inbound protection it should F64 + capacity or Trial capacity. Had to return public access, switch to Trial and disable public access again.,
Resolved: issue was in F8, for inbound protection it should F64 + capacity or Trial capacity. Had to return public access, switch to Trial and disable public access again.,
@ssrithar I included msft article in my post referenced microsoft describing set up for inbound access protection case. So according to msft it must work
Hi @EduardD ,
The article is about accessing Lakehouse from PowerBI but in your case you have an added scenario of a data warehouse which results in cross workspace access
Hi @EduardD ,
Private Link in Fabric enforces workspace-level isolation. While Power Query authoring can preview data across workspaces, dataset refresh runs in a service context that blocks cross-workspace access when Private Link is enabled. To support refresh, the semantic model must reside in the same workspace as the Warehouse.
If this post helps, then please appreciate giving a Kudos or accepting as a Solution to help the other members find it more quickly.
If I misunderstand your needs or you still have problems on it, please feel free to let us know. Thanks a lot!
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