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Hello,
I'm struggling to find the right DAX formula so my Grand Total in the right-most column in my Table visual is correct when compared to the total amount of the row level data. I think what is happening is that my DAX formula for Total Service Penalties Based on Qty Fill Rate % sees the 96.5% and then takes the total amount from the Service Penalty at 1.5% measure. This is incorrect when looking at the individual row values for the Total Service Penalties Based on Qty Fill Rate % column. The total amount I want to see for the Total Service Penalties Based on Qty Fill Rate % column is $ 360,084.89 which would be a summation of the individual row amounts. How would I achieve this result? I've tried leveraging variables and the HASONEVALUE() approach but my total ending up being inflated to approx. $1.01 million even though the individual row amounts were correct.
Solved! Go to Solution.
Please try using this DAX pattern referencing your existing measures to get the correct numbers on both the rows and the total.
NewMeasure = SUMX(VALUES(Table[DC Name]), [YourExistingMeasure])
If this works for you, please mark it as the solution. Kudos are appreciated too. Please let me know if not.
Regards,
Pat
To learn more about Power BI, follow me on Twitter or subscribe on YouTube.
Please try using this DAX pattern referencing your existing measures to get the correct numbers on both the rows and the total.
NewMeasure = SUMX(VALUES(Table[DC Name]), [YourExistingMeasure])
If this works for you, please mark it as the solution. Kudos are appreciated too. Please let me know if not.
Regards,
Pat
To learn more about Power BI, follow me on Twitter or subscribe on YouTube.
@mahoneypat Can you please elaborate on what [DC Name] in your response represents?
DC Name is the name of the Customer's Distribution Center name that orders are shipped to after they've been fulfilled. Leveraging the VALUES() DAX function with [DC Name] tells which level of granularity to perform the calculation at.
Hope this helps.
Giddy up...this worked. Thanks!
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