Forum Discussion
Writeback solution in Microsoft Fabric using a Lakehouse table but facing the issue
I am building a writeback solution in Microsoft Fabric using a Lakehouse table but facing the issue.
The goal is to let users (for example, from Power BI) update specific records in a Lakehouse dataset — like changing GoalAmount for a given Manufacturer, Territory, and GoalMonth — directly through a Fabric UDF.
Is this possible? If Yes please help.
Direct writeback to a Lakehouse table from Power BI (or any client app) is not supported natively yet, because Fabric Lakehouse tables are designed for analytical (read) workloads not transactional updates.
However, you can achieve controlled writeback using one of the following supported patterns:
What You Can Do
- Use a Fabric Notebook or Data Pipeline
- Create a notebook or pipeline with an UPDATE / MERGE SQL statement.
- Trigger it from Power BI using a Power Automate button or flow.
- Use a Staging Table
- Send updates to a separate table (via PowerApps or flow).
- Periodically merge those into your main Lakehouse.
- For Real-Time Writeback
- Use Dataverse or SharePoint List >> supports instant updates.
- Then sync that data back to Fabric if needed.
If It Still Doesn’t Work
- Check your user’s Fabric workspace permissions (need Edit + Contributor).
- Ensure the Lakehouse table is Delta format (required for MERGE).
- If Power BI >> Automate >> Fabric call fails, test the notebook manually.
- Last option: store edits in Dataverse/SharePoint and rebuild pipeline logic.
- Use a Fabric Notebook or Data Pipeline
3 Replies
Direct writeback to a Lakehouse table from Power BI (or any client app) is not supported natively yet, because Fabric Lakehouse tables are designed for analytical (read) workloads not transactional updates.
However, you can achieve controlled writeback using one of the following supported patterns:
What You Can Do
- Use a Fabric Notebook or Data Pipeline
- Create a notebook or pipeline with an UPDATE / MERGE SQL statement.
- Trigger it from Power BI using a Power Automate button or flow.
- Use a Staging Table
- Send updates to a separate table (via PowerApps or flow).
- Periodically merge those into your main Lakehouse.
- For Real-Time Writeback
- Use Dataverse or SharePoint List >> supports instant updates.
- Then sync that data back to Fabric if needed.
If It Still Doesn’t Work
- Check your user’s Fabric workspace permissions (need Edit + Contributor).
- Ensure the Lakehouse table is Delta format (required for MERGE).
- If Power BI >> Automate >> Fabric call fails, test the notebook manually.
- Last option: store edits in Dataverse/SharePoint and rebuild pipeline logic.
Hi Shubham_rai955 ,
Thank you rohit1991 for the response provided!
Has your issue been resolved? If the response provided by the community member addressed your query, could you please confirm? It helps us ensure that the solutions provided are effective and beneficial for everyone.
Thank you for your understanding!Hi Shubham_rai955 ,
I wanted to check if you had the opportunity to review the information provided. Please feel free to contact us if you have any further questions.
Thank you.
- Use a Fabric Notebook or Data Pipeline
