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PedroReis
Advocate II
Advocate II

Filter table rows where Col 1 = Col 2 by DAX

Objective: Filter the table with only Rows in which C1_Name = C2_Name

Don't want to see rows that do not have any record associated in the factual, like NOT USED = NOT USED

Limitation: Cannot add calculated columns, only use DAX. This is because you only have access to the model in Direct Query mode.

Any idea on how to solve this in a good way?

 

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1 ACCEPTED SOLUTION
parry2k
Super User
Super User

@PedroReis you can add below red code next to calculation of your flag matching measure  

 

Flag Matching Currencies =

<your existing if condition> 
*
DIVIDE( [Total Transaction Value], [Total Transaction Value] )





Did I answer your question? Mark my post as a solution.

Proud to be a Super User! Appreciate your Kudos 🙂
Feel free to email me with any of your BI needs.





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5 REPLIES 5
parry2k
Super User
Super User

@PedroReis you can add below red code next to calculation of your flag matching measure  

 

Flag Matching Currencies =

<your existing if condition> 
*
DIVIDE( [Total Transaction Value], [Total Transaction Value] )





Did I answer your question? Mark my post as a solution.

Proud to be a Super User! Appreciate your Kudos 🙂
Feel free to email me with any of your BI needs.





Thanks for the suggestion 

@PedroReisdid you tried what I proposed? You can choose any aggregation function like MAX/MIN or SELECTEDVALUE






Did I answer your question? Mark my post as a solution.

Proud to be a Super User! Appreciate your Kudos 🙂
Feel free to email me with any of your BI needs.





I did, and multiple variations work the same way. Thanks for sharing Parry!

Anonymous
Not applicable

@PedroReis -

As @parry2k said, you could use various Aggregate functions. Measures require an aggregation, because they're calculated within a Filter context, and not in the context of a single table row.

 

In your case, each Visual row filters each of your columns to a single value. Therefore, MIN, MAX, LASTNONBLANK, SELECTEDVALUE all return the same thing. 

 

Cheers!

Nathan

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