Forum Discussion
Calculate measure in source or in DAX Query
This is a general question that I'm trying to get a clear answer to. If you could provide any documentation that exist on this topic it would be super appreciated.
Is it more performant to calculate a measure like Net Profit (Profit - Cost) in the source data as a column in the fact table or within a DAX Measure = [Profit] - [Cost].
By the source data, I mean: the sales fact table would have three value columns; profit, cost, net profit. In this instance, the net profit calculation would be done in the upstream data source (SQL). In general, I've understood that it's typically better to use a measure than to create a calculated column but this scenario doesn't use the Power BI calculate column.
In the other scenario, my fact table would have 2 value columns profit and cost. In this instance, I would create a measure in DAX that calculates Net Profit.
4 Replies
Hi thedatahiker
In my view, and many have their own, it should depend on several key factors, among others:
- How the data is structured
- Level of detail the data is available (e.g. transactional or summarised)
- Your / your client's requirement for the report (e.g. once-off or repeatability, etc)
I will always try to use measures where possible when creating financial / accounting indicators. They are often cleaner and easier to work with as you start to piggyback from one measure to the next.
Best of luck with it all!
Theo 🙂
I personally prefer to assemble my solutions in SQL views. This is mostly because I'm more familiar and comfortable with SQL than I am with DAX. Also, PBI/DAX has "funny" behaviour and options that I'm still not quite used to. I generally see PBI/DAX to be the "quick & dirty", and SQL to be the reliable solution for the long haul, especially if you intend to re-use your views across multiple reports. It spares you from having to rewrite columns/measures every time. 0.02
Hi, thedatahiker ï¼›
My preference is SQL, DAX Measure then DAX calculated column.
1.it can provide better compression if it's a SQL column/expression over a DAX column.
2.SQL is easier to manage change than lots of DAX columns.3.you can add as a DAX measure then it's not going store any data and calculated when needed.
4.However measure cannot be used for slicers.
Best Regards,
Community Support Team_ Yalan Wu
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.This is closer to the answer I'm hoping to get. You mention that putting the column in the SQL expression can provide better compression and also that by using a DAX measure the value won't be stored in any data and calculated only when needed. Since the DAX measure wouldn't require any storage wouldn't that be a more performant solution? Especially when the fact table can reach into 10s of millions of rows?
