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Hi everyone,
While i'm developing a straight table, I found out that the Sum that is being displayed is quite different from the actual data.
Some more information:
Dimension:
- Synthetic Dimension: Valuelist('ExampleA')
- Month Year (MMMYYYY)
Measure:
- if(Valuelist('ExampleA') = 'ExampleA', Sum({< [Year]={"$(=Max(Year))"}, [SearchString]={"*String1*"} >}[Interactions]))
Imagine, the straight table give me 103 for January. However, if i create a pivot table with all those dimensions (Country, SearchString Month Year) and Export it to a excel, the total is still the same as the Sum(103), but the sum of all the values in the rows for January give me 475.
Is this a aggr problem?
Any tip would be highly apreciated!
Thanks for the help!
It might be an aggregation problem; try this:
sum(aggr( Sum({< [Year]={"$(=Max(Year))"}, [SearchString]={"*String1*"} >}[Interactions]), Country, SearchString, MonthYear))
It is the correct answer.
However, let me just add that there is currently a issue when we try tu work with AGGR and Synthetic Dimensions.
Thanks for the help!
I don't think there is. You need to keep in mind that, when calculating totals, the engine needs to work through a data table made of dimensions and measures. If those dimensions do not exist in your data (because you are using a synthetic dimension) then you'll need a way to re-creating that data structure for the engine to work as expected