This time we’re going bigger than ever. Fabric, Power BI, SQL, AI and more. We're covering it all. You won't want to miss it.
Learn moreLevel up your Power BI skills this month - build one visual each week and tell better stories with data! Get started
Recently I have migrated all the data to a database, and done the ETL directly on the server, and loaded into Power BI only the query with all the transformations. For me this sped up a lot. So I decided to do this in dataflows, and load in the report the dataflows instead of the queries. I did this in the hope of getting even faster updating and loading the data in the report.
However, I am having a lot of problems, sometimes I open the PBIX file it says that the table does not exist, and then I open the dataflow and the table is there, so I have to delete all the tables and load again.
What do you think about using dataflows instead of loading the queries directly into the dataset? Do you think it's really worth it and makes it faster, or doesn't it change much?
What would you do to make loading and updating the report faster?
Please check this video https://www.youtube.com/watch?v=Biz-s-YoKRc&pp=ygUsc2hvdWxkIHdlIHVzZSBkYXRhc2V0IG9yIGRhdGFmbG93IHBvd...
Regards,
Ritesh
Dataflows will always be faster since all the processing and ETL is previously done when they are refreshed. Instead of processing data from multiple sources, Power BI would just refer to the dataflow server. However, if you are working with just 2 single tables, then a dataflow is not worth it. On your case, I would check up the dataflow connector and ensure the dataflow refreshes properly.
Proud to be a Super User!
Check out the April 2026 Power BI update to learn about new features.
Sign up to receive a private message when registration opens and key events begin.
If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.
| User | Count |
|---|---|
| 12 | |
| 11 | |
| 8 | |
| 7 | |
| 7 |
| User | Count |
|---|---|
| 38 | |
| 27 | |
| 25 | |
| 22 | |
| 22 |