Don't miss your chance to take exam DP-600 or DP-700 on us!
Request nowLearn from the best! Meet the four finalists headed to the FINALS of the Power BI Dataviz World Championships! Register now
Hi Everyone,
I've been a heavy user of PowerQuery to perform all my ETL before passing it onto PowerBI.
As i'm working with millions of rows of data, PowerQuery can get too slow whenever i edit anything as it will go through step by step.
Thus i'm wondering if R Script would be faster to perform the ETL within PowerBI instead of PowerQuery?
I'm also curious if anyone here uses R Script within PowerBI to clean up their data.
Cheers
Solved! Go to Solution.
@v-ljerr-msft , Thanks for the reply.
Not too sure if you're aware that if we're running huge dataset with lot of ETL, PowerQuery will rerun all the steps whenever you open it thus making it the query extremely slow.
I'm still learning R thus I'm here seeking advice but from what I know, R only execute the required steps and don't rerun the entire query therefore I have the impression that it might be faster as compared to PowerQuery.
Hi @Rookarumba,
Thus i'm wondering if R Script would be faster to perform the ETL within PowerBI instead of PowerQuery?
Based on my research, R is not a fast language. This is not an accident. R was purposely designed to make data analysis and statistics easier for you to do. It was not designed to make life easier for your computer. So I doubt that using R Script would be faster to perform the ETL within PowerBI instead of PowerQuery. ![]()
Regards
@v-ljerr-msft , Thanks for the reply.
Not too sure if you're aware that if we're running huge dataset with lot of ETL, PowerQuery will rerun all the steps whenever you open it thus making it the query extremely slow.
I'm still learning R thus I'm here seeking advice but from what I know, R only execute the required steps and don't rerun the entire query therefore I have the impression that it might be faster as compared to PowerQuery.
Share feedback directly with Fabric product managers, participate in targeted research studies and influence the Fabric roadmap.
Check out the February 2026 Power BI update to learn about new features.
| User | Count |
|---|---|
| 53 | |
| 45 | |
| 38 | |
| 16 | |
| 15 |
| User | Count |
|---|---|
| 83 | |
| 70 | |
| 38 | |
| 28 | |
| 26 |