Forum Discussion
Delta Lake Refresh Issue
Hi fazithzakirll ,
Since the other three reports are working correctly with the same setup, it seems the issue is specific to this semantic model.
The behavior you mentioned refresh time updating but data remaining unchanged typically indicates that the model is displaying cached data and not retrieving the latest information from the Lakehouse until a full model refresh occurs.
As you’ve confirmed it’s connected directly to the Lakehouse and not the SQL endpoint, here are a few things to check.
1. Compare this model to the others for differences, such as calculated columns, complex measures, or larger tables.
2. Because this model uses a calendar table in Import mode, you might try recreating or temporarily removing it to see if Refresh visuals starts updating the data.
3. If possible, make a small test semantic model using the same tables to see if it updates as expected. If the test model works, the issue is likely within this specific model.
These steps should help determine if it’s a model level issue rather than a Direct Lake problem.
Thank You.
That’s a strange one, especially when your other reports are behaving fine.
It sounds like your "Ops Dashboard" semantic model might be falling back to DirectQuery mode. When this happens, "Refresh visuals" can sometimes behave inconsistently because it's no longer using the high-speed Direct Lake path.
This fallback usually happens for a few specific reasons:
Memory Pressure: If the columns needed for that specific report are too large, the capacity might refuse to load them into memory and switch to DirectQuery instead.
Unsupported Features: Direct Lake has some strict requirements. If your "Ops Dashboard" uses certain features (like complex DAX calculated columns or RLS in a specific way), it might be forcing a fallback.
Lakehouse Schema Changes: If the underlying Delta tables for that specific model were updated in a way that altered the schema, the link can sometimes "glitch" until a full manual refresh is triggered.
I’d suggest using the Performance Analyzer in Power BI Desktop (connected to the service) or looking at the DAX Studio metrics to see the "Direct Lake Readiness" of your tables. Microsoft has a great guide on how to check if your queries are actually using Direct Lake or falling back to DirectQuery: Analyze Direct Lake query processing.
If you find it is falling back, you might need to investigate your dax measures and perhaps use the vertipaq analyzer to see if you have some columns in your tables that are too large to be loaded into memory (eg. high cardinality columns like date/time columns etc.).
Br
Asger