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Applies to: ✅ SQL analytics endpoint, Warehouse, and Mirrored Database in Microsoft Fabric
You can create new Power BI semantic models based on lakehouse, SQL analytics endpoint, or Warehouse items in Microsoft Fabric.
Note
By November 30, 2025, all Power BI default semantic models are disconnected from their item and become independent semantic models. You can retain them if you still use them for reports or dashboards or delete them safely if they are no longer needed. For more information, see Blog: Decoupling Default Semantic Models for Existing Items in Microsoft Fabric.
- Since September 5, 2025, Power BI default semantic models are no longer created automatically when a warehouse, lakehouse, or mirrored item is created. For more information, see Blog: Sunsetting Default Semantic Models.
- If your item doesn't have a semantic model already, you can create a Power BI semantic model.
Create a new Power BI semantic model in Direct Lake mode
These new Power BI semantic models can be edited in the workspace using Open data model and can be used with other features such as write DAX queries and semantic model row-level security. For more about semantic models and Direct Lake mode, see Power BI semantic models in Microsoft Fabric.
To create a Power BI semantic model using Direct Lake mode, follow these steps:
- In the Fabric portal, create a new semantic model based on the desired item:
- Open the lakehouse and select New Power BI semantic model from the ribbon.
- Alternatively, open the relevant item, such as your warehouse or SQL analytics endpoint, select New semantic model.
- Enter a name for the new semantic model, select a workspace to save it in, and pick the tables to include. Then select Confirm.
- The new Power BI semantic model can be edited in the workspace, where you can add relationships, measures, rename tables and columns, choose how values are displayed in report visuals, and much more. If the model view doesn't show after creation, check the pop-up blocker of your browser.
- To edit the Power BI semantic model later, select Open data model from the semantic model context menu or item details page to edit the semantic model further.
Power BI reports can be created in the workspace by selecting New report from web modeling, or in Power BI Desktop by live connecting to this new semantic model. To learn more on how to connect to semantic models in the Power BI service from Power BI Desktop
Create a new Power BI semantic model in import or DirectQuery storage mode
Having your data in Microsoft Fabric means you can create Power BI semantic models in any storage mode: Direct Lake, import, or DirectQuery. You can create more Power BI semantic models in import or DirectQuery mode using SQL analytics endpoint or Warehouse data.
To create a Power BI semantic model in import or DirectQuery mode, follow these steps:
- Open Power BI Desktop, sign in, and select OneLake.
- Choose the SQL analytics endpoint of the lakehouse or warehouse.
- Select the Connect button dropdown list and choose Connect to SQL endpoint.
- Select import or DirectQuery storage mode and the tables to add to the semantic model.
From there, you can create the Power BI semantic model and report to publish to the workspace when ready.
Create a new, blank Power BI semantic model
The New Power BI semantic model button creates a new blank semantic model.
Script a Power BI semantic model
You can script out a Power BI semantic model from the XMLA endpoint with SQL Server Management Studio (SSMS).
View the Tabular Model Scripting Language (TMSL) schema of the semantic model by scripting it out via the Object Explorer in SSMS. To connect, use the semantic model's connection string, which looks like powerbi://api.powerbi.com/v1.0/myorg/username. You can find the connection string for your semantic model in the Settings, under Server settings. From there, you can generate an XMLA script of the semantic model via SSMS's Script context menu action. For more information, see Dataset connectivity with the XMLA endpoint.
Scripting requires Power BI write permissions on the Power BI semantic model. With read permissions, you can see the data but not the schema of the semantic model.