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Hello.
1 month in on Power BI.
I have two tables, both with numeric columns. Average two columns and multiply the results.
SS = Round(Average('Table1'[ColA]),2) * Round(Average('Table2'[ColB], 2)
Year | ColA | Year | ColB | YEAR | ||
2025 | 100 | 2025 | 2 | 2020 | ||
2025 | 100 | 2025 | 4 | 2021 | ||
2025 | 100 | 2025 | 2 | 2022 | ||
2025 | 100 | 2025 | 2 | 2023 | ||
2024 | 100 | 2025 | 2 | 2024 | ||
2024 | 99 | 2025 | 4 | 2025 | ||
2024 | 100 | 2025 | 2 | 2026 | ||
2024 | 100 | 2025 | 2 | 2027 | ||
2024 | 99 | 2025 | 3 | 2028 | ||
2024 | 100 | 2025 | 4 | |||
2024 | 99 | 2025 | 2 | |||
2024 | 100 | 2025 | 2 | |||
2024 | 100 | 2025 | 2 | |||
2024 | 100 | 2025 | 2 |
Solved! Go to Solution.
hello @mwjansen
i think you need to make another DIM table for Division.
Here i made a Division Dim table from SUMMARIZE as an example (i think you have a list of Division that can be worked as your Dim).
Then, you create a relationship between Division and those two Fact table.
after that, you can do the measure as yours.
Take slicer value from Year dim table and Division dim table.
as the result above, in 2025
Mission Critical has 100 average value in COLA and 2.5 average value in COLB
Operations has 100 average value in COLA and 3 average value in COLB.
Hope this will help.
Thank you.
Hi, @mwjansen
I wish you all the best. Previously Super user have provided a solution to help you solve the problem. Since we haven't heard back from you yet, I'd like to confirm if you've successfully resolved this issue or if you need further help?
If yes, you are welcome to share your workaround and mark it as a solution so that other users can benefit as well. If you find a reply particularly helpful to you, you can also mark it as a solution.
If you still have any questions or need more support, please feel free to let us know. We are more than happy to continue to help you.
Thank you for your patience and look forward to hearing from you.
Best Regards
Jianpeng Li
Thank you Irwan. You are correct, it does work fine. Dumb me forgot where it failed. In the visuals (clustered column chart), the x-axis is 'Division' (found in both Table1 and Table2), and the y-axis is Table1 Average of ColA (and another visual where y-axis is Table2 Average of ColB).
It is here where the calculations are off for each Division.
Division | Year | COLA | Year | DIVISION | COLB | YEAR | ||
Mission Critical | 2025 | 100 | 2025 | Mission Critical | 4 | 2020 | ||
Mission Critical | 2025 | 100 | 2025 | Operations | 2 | 2021 | ||
Operations | 2025 | 100 | 2025 | Commercial/Special Projects | 4 | 2022 | ||
Mission Critical | 2025 | 100 | 2025 | Mission Critical | 2 | 2023 | ||
Mission Critical | 2024 | 100 | 2025 | Mission Critical | 2 | 2024 | ||
Mission Critical | 2024 | 99 | 2025 | Mission Critical | 2 | 2025 | ||
Mission Critical | 2024 | 100 | 2025 | Operations | 4 | 2026 | ||
Mission Critical | 2024 | 100 | 2025 | Mission Critical | 2 | 2027 | ||
Mission Critical | 2024 | 99 | 2025 | Mission Critical | 2 | 2028 | ||
Mission Critical | 2024 | 100 | 2025 | Mission Critical | 3 | |||
Mission Critical | 2024 | 99 | 2025 | Mission Critical | 4 | |||
Mission Critical | 2024 | 100 | 2025 | Mission Critical | 2 | |||
Mission Critical | 2024 | 100 | 2025 | Mission Critical | 2 |
hello @mwjansen
i think you need to make another DIM table for Division.
Here i made a Division Dim table from SUMMARIZE as an example (i think you have a list of Division that can be worked as your Dim).
Then, you create a relationship between Division and those two Fact table.
after that, you can do the measure as yours.
Take slicer value from Year dim table and Division dim table.
as the result above, in 2025
Mission Critical has 100 average value in COLA and 2.5 average value in COLB
Operations has 100 average value in COLA and 3 average value in COLB.
Hope this will help.
Thank you.
hello @mwjansen
i am not sure how the data is off, but i tried your DAX and it looks fine.
Thank you.
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