Forum Discussion
Semantic Model Refresh History For Particular Tables
Hi Deagle ,
Power BI doesn't natively track the last transformation time for each individual table in a semantic model.
However, you can manually add a
timestamp during the final transformation step in Power Query. For each table, you can either add a column using DateTime. LocalNow() to mark when the data was loaded, or create a one-row summary table that logs the refresh time. This way, you can display the last transformation timestamp per table directly in your report.
Thanks,
Sai Teja
Hi Deagle,
Just wanted to follow up. If the shared guidance worked for you, that’s wonderful hopefully it also helps others looking for similar answers. If there’s anything else you'd like to explore or clarify, don’t hesitate to reach out.
Thank you.
Unfortunately no
Hi Deagle,
Thank you for getting back to us, and I truly understand your concern about tracking refresh history at the table level within a semantic model.
At present, Microsoft Fabric only records refresh history at the dataset (semantic model) level. There isn’t a built-in feature or API that provides individual table-level refresh timestamps or logs.
That said, you can still achieve similar visibility by creating a custom tracking setup using a Fabric Notebook or Data Factory pipeline. Here is how you can do it:Use Fabric Notebook with the Semantic Link library: You can use the Semantic Link library to connect to your workspace and model programmatically. From there, call the refresh history endpoint to get dataset-level logs, and extract the tables or partitions that were refreshed.
https://learn.microsoft.com/en-us/python/api/semantic-link/overview-semantic-link?view=semantic-link-python&viewFallbackFrom=semantic-link-py
Capture and Log Table Information: When triggering a refresh (via API or Data Factory), record which tables/partitions were included. You can parse the response (which includes refresh time, status, and affected objects) and write that data into a Lakehouse or SQL table for persistent storage. Over time, this builds your own table-level refresh log.
Automate with Scheduling: Schedule the notebook or pipeline to run automatically after every dataset refresh. This ensures your table-level history stays up to date without manual intervention.Refer these links:
1. https://learn.microsoft.com/en-us/rest/api/power-bi/datasets/get-refresh-history?tabs=HTTP
2. https://learn.microsoft.com/en-us/fabric/data-factory/semantic-model-refresh-activityHope that clarifies. Let us know if you have any doubts regarding this. We will be happy to help.
Thank you for using the Microsoft Fabric Community Forum.
Hi Deagle,
Just checking in to see if the issue has been resolved on your end. If the earlier suggestions helped, that’s great to hear! And if you’re still facing challenges, feel free to share more details happy to assist further.Thank you.
Hi Deagle,
Just wanted to follow up. If the shared guidance worked for you, that’s wonderful hopefully it also helps others looking for similar answers. If there’s anything else you'd like to explore or clarify, don’t hesitate to reach out.Thank you.