Table Visual not Matching Calculated Visual

Hi muom,

Checkout below solution - 

First create a measure to count the adults - same as what you have provided.

Then, create a measure Earned Income Status (Maintained or Increased) using above measure - 

Earned Income Status (Maintained or Increased) = 
VAR _count = 
CALCULATE(
    [Count Adults], 
    'PDE_EE-EnrollmentsTbl'[Earned Income.Change Status] IN {"Increased", "Maintained"}
)
RETURN
DIVIDE(_count, [Count Adults], 0)

This measure will use the first measure where you have already calculated total count of adults. Using variable _count you are capturing total adults with status increased and maintained and then dividing _count with total count of adults measure.

Result - 

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Best regards,
Rupasree Achari | BI & Fabric Analytics Engineer 

muom 

Your card measure counts distinct Entry Exit IDs where status is Increased OR Maintained in one pass. Your table's Count Adults measure has no filter on Earned.Change Status at all - it relies purely on row context from the visual. If there are duplicate/multiple enrollment records per Entry Exit ID in 'PDE_EE-EnrollmentsTbl', an ID can land in multiple rows of the table (counted twice) while only being counted once in the OR-based card measure.

Check for duplicate Entry Exit IDs per status in 'PDE_EE-EnrollmentsTbl' - that's almost certainly your mismatch.

Hi,

Please share the download link of the PBI file.

muom  

Oh yeah, this happened to me many times its usually because of a  fan-out. Your card measure counts each Exit once (because of the OR), but your table breaks it out by category, so if an exit has more than one Enrollment record (like it got reassessed and has both an "Increased" row and a "Maintained" row), it gets counted once in EACH row of the table — inflating the sum.

A quick way to check is group your Enrollments table by Entry Exit ID and see if any IDs show up with more than one distinct Change Status. If so, that's your culprit.

And if thats it to fix it pick one Change Status per exit (latest record, usually) before it hits the table,  like a calculated column or a summarized table instead of letting the visual count every related Enrollment row

I think the issue is that the table and the card are not actually calculating the same thing.

In your table, the % measure is only returning the count of adult records in the current row context. Since the table already has Earned Income. Change Status on the rows, each row is already filtered to one status. So that measure is not really calculating a percentage of total adults by itself.

To make the table match the card, you need to divide each row count by the total adult count.

I’d also check whether Entry Exit ID is unique. If it isn’t, COUNT() can overcount, and that can cause the row values not to reconcile with the total. In many cases DISTINCTCOUNT() is the better option.

A cleaner approach would be to create a total adult measure like:
Adult Exits = CALCULATE( DISTINCTCOUNT('Exit Details_UDE'[Entry Exit ID]), AgeCatTbl[Adult-Child] = "Adult" )

Then use a percentage measure for the table like:
Adult Exit % by Status = DIVIDE( CALCULATE( DISTINCTCOUNT('Exit Details_UDE'[Entry Exit ID]), AgeCatTbl[Adult-Child] = "Adult" ),                                          CALCULATE( [Adult Exits], REMOVEFILTERS('PDE_EE-EnrollmentsTbl'[Earned Income.Change Status]) ) )

And for the card:
Earned Income Status % = DIVIDE( CALCULATE( DISTINCTCOUNT('Exit Details_UDE'[Entry Exit ID]), AgeCatTbl[Adult-Child] = "Adult", 'PDE_EE-EnrollmentsTbl'[Earned Income.Change Status] IN { "Increased", "Maintained" } ), [Adult Exits] )

So the mismatch is most likely coming from one or more of these:

1. The table measure is not actually calculating a percentage
2. The table and card are being evaluated under different filter context
3. COUNT() may be double-counting if Entry Exit ID is not unique

If the row totals add up to more than the overall total, I’d definitely check for duplicate Entry Exit IDs or cases where the same ID appears under more than one status.