Get certified for free when you join Fabric Data Days 2026 and dive into Fabric, Power BI, SQL, AI, and other essential data skills.
Join nowJuly 7 - July 17 | Round 2 of the Power BI Dataviz World Championships. Don't miss your chance! Learn more
Hi there.
I am quite new PowerBi user without experience with DAX and SQL. My issue is linked with PowerBi command Not enought memory during SQL data importing to PowerBi.I executed some community suggestions for instance: remove unnessesary colums; i disable "Allow data preview to download in the background". That hepled partialy; it's mean before i could load 40 mln rows now i can load 103 mln rows before error occur. is it possible (and how to do it) to filter by date, for instance load data from sql to the PowerBi model only from 3 years before now?
This thread shows how to build the SQL into your query - writing it should be pretty straightforward, something like
SELECT * from [YourTable] where [DateYourInterestedIn] >= DATEADD(year, -3, CURRENT_TIMESTAMP);
depending on what your server is runing and how much data you want to pull
Thank you for prompt reply.
I tried your code but, there is a syntax error. Anyway i use column filter properties(date/time filters), but it seem that there is still to many records for PowerBi/available memory to load (i loaded data from 2017-12-29 and when i try 2017-12-01 memory limitation message appear)
Hi @Ryszard,
When you use SQL statement to filter your data, please test using SSMS, then type the accurate SQL statement in the red line box.
Best Regards,
Angelia
This isn't a solution, but I have a related question.
When you use SQL to load rows, does PBI use the indexes in the database associated with those tables?
Are there best practices available to load large datasets in PBI?
Join us in Barcelona for FabCon and SQLCon, the Fabric, Power BI, SQL, and AI community event. Save €200 with code FABCMTY200.
Join Data Days 2026: 60 days of free live/on-demand sessions, challenges, study groups, and certification opportunities.
| User | Count |
|---|---|
| 26 | |
| 24 | |
| 19 | |
| 19 | |
| 15 |
| User | Count |
|---|---|
| 46 | |
| 46 | |
| 43 | |
| 36 | |
| 33 |