Don't miss your chance to take the Fabric Data Engineer (DP-600) exam for FREE! Find out how by attending the DP-600 session on April 23rd (pacific time), live or on-demand.
Learn moreNext up in the FabCon + SQLCon recap series: The roadmap for Microsoft SQL and Maximizing Developer experiences in Fabric. All sessions are available on-demand after the live show. Register now
Hi all,
I have a doubt about the next question. Which is better in terms of performance, Custom Column using PQuery or New Column using DAX?
Thanks to all for you answer.
Solved! Go to Solution.
Yeah, I would say that in your case you should definitely consider moving that to Power Query. General rule is that the further upstream that you can push the calculations, the better the performance downstream.
Well, overall, Power Query is only going to execute the calculation once per a query refreshing, so you will take a small performance hit during query refresh but after that you have a static value. With DAX, the calculation will essentially be done every time it is needed so you will have a performance hit each time.
Ok, thanks so much for your fast answer.
I have a model and i need to split some string values from various columns to use later like slicers. The fact table in the model have more than a million of rows and i'm thinking in transform my new DAX columns in Power Query columns to reduce the performance impact when the user use it.
Do you think i should do it?
Thanks again.
Yeah, I would say that in your case you should definitely consider moving that to Power Query. General rule is that the further upstream that you can push the calculations, the better the performance downstream.
Yes, I thinked the same.
If somebody need it, here you have a link that explain so well my first question:
http://radacad.com/m-or-dax-that-is-the-question
Thanks Greg_Deckler
If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.
A new Power BI DataViz World Championship is coming this June! Don't miss out on submitting your entry.
Share feedback directly with Fabric product managers, participate in targeted research studies and influence the Fabric roadmap.
| User | Count |
|---|---|
| 48 | |
| 45 | |
| 41 | |
| 20 | |
| 17 |
| User | Count |
|---|---|
| 69 | |
| 64 | |
| 32 | |
| 31 | |
| 27 |