Check your eligibility for this 50% exam voucher offer and join us for free live learning sessions to get prepared for Exam DP-700.
Get StartedDon't miss out! 2025 Microsoft Fabric Community Conference, March 31 - April 2, Las Vegas, Nevada. Use code MSCUST for a $150 discount. Prices go up February 11th. Register now.
I am trying to create a measure (Preferred Return Due to Date) that is a running total of another running total measure (Preferred Return Due Quarterly). I have searched this site and other sites for solutions, but I cannot figure it out. Any help would be appreciated. Please excuse the formatting of this post. I was getting errors when I tried to post code, and I could not figure out how to attach files.
Here are the measures I used:
Here is a screenshot of the matrix visualization:
The Preferred Return Due to Date should be a running total of Preferred Return Due Quarterly.
Hi @paiello1 ,
Please try this way:
I used Power Query to add an indexed column starting at 1 to the data table:
Then I use this DAX to create a new column:
Preferred Return Due to Date =
CALCULATE(
SUM('Table'[Preferred Return Due Quarterly]),
FILTER(
ALL('Table'),
'Table'[Index] <= EARLIER('Table'[Index])
)
)
The results are as follows:
Best Regards,
Dino Tao
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
@v-junyant-msft Unfortunately, that approach does not work. The table you added an index to is not a table. It is a matrix visualization (i.e. the output of the measures I created). So, I cannot add an index to it. Any other thoughts would be welcome as I am still stuck on it.
Could you somehow splice in your expected result on the last screenshot.
@Data-estDog Thank you for considering this issue. Here is the table with the desired results for Preferred Return Due to Date.
QuarterInCalendar | Capital Contributions to Date | Returned Capital to Date | Unreturned Capital to Date | Preferred Return Due Quarterly | Preferred Return Due to Date |
Q1 2013 | |||||
Q2 2013 | 4,200,000 | 4,200,000 | 73,500 | 73,500 | |
Q3 2013 | 4,200,000 | 4,200,000 | 73,500 | 147,000 | |
Q4 2013 | 4,200,000 | 4,200,000 | 73,500 | 220,500 | |
Q1 2014 | 4,200,000 | 4,200,000 | 73,500 | 294,000 | |
Q2 2014 | 4,200,000 | 4,200,000 | 73,500 | 367,500 | |
Q3 2014 | 4,200,000 | 4,200,000 | 73,500 | 441,000 | |
Q4 2014 | 4,200,000 | 4,200,000 | 73,500 | 514,500 | |
Q1 2015 | 4,200,000 | 4,200,000 | 73,500 | 588,000 | |
Q2 2015 | 4,200,000 | 4,200,000 | 73,500 | 661,500 | |
Q3 2015 | 4,200,000 | 4,200,000 | 73,500 | 735,000 | |
Q4 2015 | 4,200,000 | 4,200,000 | 73,500 | 808,500 | |
Q1 2016 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 877,625 |
Q2 2016 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 946,750 |
Q3 2016 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,015,875 |
Q4 2016 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,085,000 |
Q1 2017 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,154,125 |
Q2 2017 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,223,250 |
Q3 2017 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,292,375 |
Q4 2017 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,361,500 |
Q1 2018 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,430,625 |
Q2 2018 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,499,750 |
Q3 2018 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,568,875 |
Q4 2018 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,638,000 |
Q1 2019 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,707,125 |
Q2 2019 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,776,250 |
Q3 2019 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,845,375 |
Q4 2019 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,914,500 |
Q1 2020 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 1,983,625 |
Q2 2020 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 2,052,750 |
Q3 2020 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 2,121,875 |
Q4 2020 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 2,191,000 |
Q1 2021 | 4,200,000 | 250,000 | 3,950,000 | 69,125 | 2,260,125 |
Q2 2021 | 4,300,000 | 250,000 | 4,050,000 | 70,875 | 2,331,000 |
Q3 2021 | 4,300,000 | 250,000 | 4,050,000 | 70,875 | 2,401,875 |
Q4 2021 | 4,300,000 | 250,000 | 4,050,000 | 70,875 | 2,472,750 |
Q1 2022 | 4,400,000 | 250,000 | 4,150,000 | 72,625 | 2,545,375 |
Q2 2022 | 4,400,000 | 250,000 | 4,150,000 | 72,625 | 2,618,000 |
Q3 2022 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 2,692,375 |
Q4 2022 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 2,766,750 |
Q1 2023 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 2,841,125 |
Q2 2023 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 2,915,500 |
Q3 2023 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 2,989,875 |
Q4 2023 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 3,064,250 |
Q1 2024 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 3,138,625 |
Q2 2024 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 3,213,000 |
Q3 2024 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 3,287,375 |
Q4 2024 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 3,361,750 |
Q1 2025 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 3,436,125 |
Q2 2025 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 3,510,500 |
Q3 2025 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 3,584,875 |
Q4 2025 | 4,500,000 | 250,000 | 4,250,000 | 74,375 | 3,659,250 |
March 31 - April 2, 2025, in Las Vegas, Nevada. Use code MSCUST for a $150 discount!
Check out the January 2025 Power BI update to learn about new features in Reporting, Modeling, and Data Connectivity.
User | Count |
---|---|
123 | |
78 | |
49 | |
38 | |
37 |
User | Count |
---|---|
196 | |
80 | |
70 | |
51 | |
42 |