Forum Discussion
Refresh Progress of a Semantic Model - Dynamically
How are we able to dynamically execute and monitor the refresh progress of a Semantic Model? Is the Monitoring Hub sufficient? it seems to me Monitoring Hub is only for historical analysis and alerts.
I recently got my DP 700 and Semantic Link is the the answer if you're looking for that.
5 Replies
Hi tan_thiamhuat
you can also use Semantic Link to refresh and monitor the refresh activity. See this: https://learn.microsoft.com/en-us/python/api/semantic-link-sempy/sempy.fabric?view=semantic-link-python#sempy-fabric-refresh-dataset
Also check this to see how to:
https://data-marc.com/2024/05/28/dynamically-refreshing-historical-partitions-in-power-bi-incremental-refresh-semantic-models-using-fabric-semantic-link/https://www.advancinganalytics.co.uk/blog/semantic-model-refresh-in-fabric
Hope that helps!
BestOnur
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Hi tan_thiamhuat ,
Thanks for reaching out to the Microsoft fabric community forum.
Monitoring Hub is mainly for historical tracking and alerting. If you need to dynamically trigger and monitor a semantic model refresh, you can use the Semantic Model Refresh activity in Fabric Data Factory. It allows you to run the refresh from a pipeline and monitor the status through the pipeline run.
Please go through the below document:
Semantic model refresh activity in Data Factory for Microsoft Fabric - Microsoft Fabric | Microsoft…
If I misunderstand your needs or you still have problems on it, please feel free to let us know.
Best Regards,
Community Support Teamthanks for the reply. I was doing the DP-700 exam, and there is this question above, so I am wondering which is the correct option:
a) Monitoring Hub
b) Semantic Link in a Notebook
for a) on Monitoring Hub, which I think it cannot dynamically execute and monitor the refresh progress of a Semantic Model, but is more for historical analysis and alerts. Am I correct? So the correct answer should be Semantic Link in a Notebook.
