Semantic Model unable to load from Mirrored Database

[PWTRyanWhite]

Hi,

I'm running into an issue with creating a semantic model from an Azure SQL Mirrored Database. Everytime I try and look at the data as a preview in Fabric, I keep getting this error.

Cannot load model

Couldn't load the model schema associated with this report. Make sure you have a connection to the server, and try again.

Please check the technical details for more information. If you contact support, please provide these details.

Any thoughts?

[rosha_rosha · Accepted solution]

Option 1: Create Semantic Model from the Lakehouse (not SQL endpoint)
Instead of using the SQL endpoint, try this:

Go to your Lakehouse in Fabric.

Use “New Semantic Model” directly from the Lakehouse table view (not the SQL endpoint).

Select the tables you want and click “Create”.

This method uses Fabric-native metadata and avoids schema errors from the mirrored SQL endpoint.

Option 2: Use Dataflow Gen2 to Load into a Warehouse or Clean View
Use a Dataflow Gen2 to read from the Lakehouse.

Store the clean data into a Fabric Warehouse.

Build your semantic model from the Warehouse, which has full SQL support and reliable metadata handling.

[v-saisrao-msft]

Hi @PWTRyanWhite,
I wanted to check if you had the opportunity to review the information provided by @rosha_rosha. Please feel free to contact us if you have any further questions. If the response has addressed your query, please accept it as a solution and give a 'Kudos' so other members can easily find it.
Thank you.

[v-saisrao-msft]

Hi @PWTRyanWhite,

May I ask if you have resolved this issue? If so, please mark the helpful reply and accept it as the solution. This will be helpful for other community members who have similar problems to solve it faster.

Thank you.

[v-saisrao-msft]

Hi @PWTRyanWhite,

We haven’t heard back from you regarding your issue. If it has been resolved, please mark the helpful response as the solution and give a ‘Kudos’ to assist others. If you still need support, let us know.

Thank you.