Forum Discussion
Poor Measure Performance and Confusion
Wilson_ thanks again but not luck. Note that ALLEXCEPT requires Table and Column as parameters so you cannot include colums from two different tables. I tried adding two ALLEXCEPT (one for each table/column) but that did not work either.
Your second option also does not work as MIN only accepts a column reference as an argument at ALL generates a table.
vgeldbr,
Sure, should be easy enough fix on the second to get around the issue. Something like:
MINX (
ALL ( 'CTE YTD Excel Report (ServiceNow)'[Usage Month] ),
'CTE YTD Excel Report (ServiceNow)'[Usage Month]
)
Keep in mind, I'm just typing syntax without an editor so feel free to modify if I've made any simple syntax errors. 🙂
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Wilson_ This still produces the result above (ie. wrong with the user showns for each and every one of the 2.3m engagement codes).
vgeldbr,
First of all, I got so annoyed with all the errors in my DAX that I produced my own small sample dataset so I could get my measure correct at least. I was able to but in looking at your question again, I noticed something I glossed over earlier that may be a much more productive path forward on your issue.
Why does your dimension table have 24x more records than your fact table? The inverse seems much more standard. I'm not sure what the data source on your engagement codes is but can you filter out all the codes that aren't in your fact table upstream (either in the data source itself or in Power Query in your Power BI semantic model)?
Wilson_ , the dimension table is a list of financial codes. Each code has many attributes that are required in the report (e.g. status, description, owner). I will need these. I'm focused though just on the immediate problem is just using the engagement code (which is the key for the relationship) causes the performance to grind to a crawl.