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I have a dataflow in the PBI service that consists of a single SQL query executed against an on-prem SQL Server database. There are no transformations on the result of the query.
I also have a semantic model in the PBI service that imports the contents of the dataflow described above.
Both the dataflow and the semantic model are in the same workspace. The workspace is licensed as a Pro workspace.
I recently updated the SQL query in the dataflow with three new columns. I refreshed the dataflow in the PBI service and verified that the new columns are now present in the dataflow.
However, after refreshing the semantic model in the PBI service, the new columns are not displayed in the corresponding table. In order to get the columns to appear, I have to download the semantic model, refresh it the from the desktop and publish the semantic model back to the service.
This is not an adequate solution. We would like these kinds of changes to propagate automatically via scheduled refreshes.
Is it possible to have these kinds of changes propagate automatically to the semantic model instead of having to manually refresh it from the desktop?
Thanks!
Solved! Go to Solution.
Hi @smalltownbear , GilbertQ, thank you for your prompt reply!
Quote from Microsoft:
Changes in data source table structure, or schema, such as a new, renamed, or removed column can only be applied in Power BI Desktop, and in the Power BI service they can cause the refresh to fail.
Best regards,
Joyce
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi @smalltownbear , GilbertQ, thank you for your prompt reply!
Quote from Microsoft:
Changes in data source table structure, or schema, such as a new, renamed, or removed column can only be applied in Power BI Desktop, and in the Power BI service they can cause the refresh to fail.
Best regards,
Joyce
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
This is by design to ensure that changes to the underlying model that will not break the existing model.
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