Power BI is turning 10, and we’re marking the occasion with a special community challenge. Use your creativity to tell a story, uncover trends, or highlight something unexpected.
Get startedJoin us for an expert-led overview of the tools and concepts you'll need to become a Certified Power BI Data Analyst and pass exam PL-300. Register now.
You would need to have a separate query for each table that you want to end up in Power BI. Use the same join conditions and where clause for each query, just change the columns that you select to only give the columns you want in that particular table.
Both methods worked correctly, which one is better from a star schema perspective?
Is that the only possible way? Without the query total size is 150MB but with the separate query it's 200 MB size which is a bit strange . I am guessing even with the increase size from seperate query the performance should be better than having them all in one table?
You would need to have a separate query for each table that you want to end up in Power BI. Use the same join conditions and where clause for each query, just change the columns that you select to only give the columns you want in that particular table.
Both methods worked correctly, which one is better from a star schema perspective?
Is that the only possible way? Without the query total size is 150MB but with the separate query it's 200 MB size which is a bit strange . I am guessing even with the increase size from seperate query the performance should be better than having them all in one table?
Yes, the increase in size shouldn't affect performance enough to offset the benefits of having a proper star schema
This is your chance to engage directly with the engineering team behind Fabric and Power BI. Share your experiences and shape the future.
Check out the June 2025 Power BI update to learn about new features.
User | Count |
---|---|
66 | |
62 | |
52 | |
36 | |
34 |
User | Count |
---|---|
78 | |
66 | |
58 | |
45 | |
43 |