Microsoft is giving away 50,000 FREE Microsoft Certification exam vouchers!
Enter the sweepstakes now!Prepping for a Fabric certification exam? Join us for a live prep session with exam experts to learn how to pass the exam. Register now.
Hello!
I extract data from SAP each month, generating multiple .xlsx files (one per month). To optimize the size of the database, I decided to convert each of these monthly files into separate .parquet files.
However, when I load these files into Power BI, every time I hit "refresh," it reloads all the files, which demands a significant amount of processing power. Is there a way to configure some files as static and others as dynamic, so only the dynamic files are refreshed?
My initial approach was to create two separate folders—one for static files and one for dynamic files—allowing me to configure different refresh settings for each. However, I have not been able to make this setup work yet.
Solved! Go to Solution.
The only way to avoid a full load is to use incremental refresh with a foldable source. Doesn't seem to be an option in your scenario.
Having the data in Parquet format should already give you the highest possible performance. If you put the Parquet files into a data lake you could also consider using the DirectLake connection (where the data is connected live). Performance will be slightly inferior to import mode.
The only way to avoid a full load is to use incremental refresh with a foldable source. Doesn't seem to be an option in your scenario.
Having the data in Parquet format should already give you the highest possible performance. If you put the Parquet files into a data lake you could also consider using the DirectLake connection (where the data is connected live). Performance will be slightly inferior to import mode.
Check out the May 2025 Power BI update to learn about new features.
Explore and share Fabric Notebooks to boost Power BI insights in the new community notebooks gallery.
User | Count |
---|---|
72 | |
68 | |
67 | |
45 | |
42 |
User | Count |
---|---|
47 | |
38 | |
28 | |
28 | |
27 |