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Anonymous
Not applicable

Unable to sum measure columns from table even though data type is set to number or decimal

I am having an issue with a view I am importing from Google BigQuery.  It's a flat view where I have columns such as Sales Conversions, Sales Revenue, Sessions, Shares, etc.  These columns are set up correctly in "Transform Data" meaning, their column type is Either Decimal or Whole Number.  when I look at the table in Model view I see the following:  

NEdmonds_0-1617886424197.png

When I go back to the visualization canvas, I see the following, there is no Sum icon: 

NEdmonds_1-1617886469132.png

If I click on one of these items, it throws it into a table, and acts like a dimension.  When I check the column formatting information, it is correct: 

NEdmonds_3-1617886680113.png

 There is no other tables in the model connected to this one via a join.  What am I missing?  Why do these columns come through as attributes instead of values? 

 

 

 

4 REPLIES 4
odumna
Helper I
Helper I

Hi. I have the same issue.

In current file I have a column in table. This column has a whole number type but is it not summarized ((( 

But when I create this query in new desktop file  all is fine.

It is very hard to me to create the new file from scratch.

amitchandak
Super User
Super User

@Anonymous , This is strange. Check you are on the latest version of power bi. Close all power bi files. And open again and check.

If yous still face an issue, can you a sample pbix after removing sensitive data?

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Anonymous
Not applicable

Quick update - I opened a ticket with Microsoft support on this, so they are working on this.  

Anonymous
Not applicable

Hi @amitchandak - I have the latest version of power BI.  I opened/closed same issue.  The issue is ONLY with this particular file though, which doesn't make sense.  If I create a new pbix, connect to the data, it is working as expected.  I have already done a tremendous amount of work through in the file causing issues though, so it would be a shame to have to start completely over.  

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