Join us at FabCon Atlanta from March 16 - 20, 2026, for the ultimate Fabric, Power BI, AI and SQL community-led event. Save $200 with code FABCOMM.
Register now!Get Fabric Certified for FREE during Fabric Data Days. Don't miss your chance! Request now
Hi guys,
I've 3 tables: A,B,C
A
B
C
Result:
the first colum (may 2023) is simple, the others are the problem.
I need to see the difference (1000€ - 370€ = 630€) in the row "liquid assets" of next month (june 2023)
The difference of june (= 430 €) --> liquid assets of july 2023
The difference of july (= 430€) --> liquid assets of august
....the same for the next months
Have you idea to do this?
Thank you 🙂
Solved! Go to Solution.
Create a Calculated Column for Differences: Create a new calculated column in your data table to calculate the differences between consecutive months. You can use a formula like this:
Difference =
CALCULATE(
SUM(A[Amount]) - SUM(B[Amount]),
FILTER(
ALL('Date'[Month]),
'Date'[Month] = EARLIER('Date'[Month]) + 1
)
)
Adjust this formula based on your actual column names and structure.
Create a Running Total Measure: Now, create a measure for the running total. This measure should accumulate the differences for each month. Here's an example:
RunningTotal =
CALCULATE(
SUM('YourTable'[Difference]),
FILTER(
ALL('Date'[Month]),
'Date'[Month] <= MAX('Date'[Month])
)
)
Again, adjust the table and column names accordingly.
Visualize the Data: Finally, use a line chart or any suitable visualization to display the running total over time. Put the Date field on the x-axis and the RunningTotal measure on the y-axis.
These steps should help you create a Power BI report that shows the running total of differences in "liquid assets" over time. Adjust the formulas based on your actual data model and requirements.
Create a Calculated Column for Differences: Create a new calculated column in your data table to calculate the differences between consecutive months. You can use a formula like this:
Difference =
CALCULATE(
SUM(A[Amount]) - SUM(B[Amount]),
FILTER(
ALL('Date'[Month]),
'Date'[Month] = EARLIER('Date'[Month]) + 1
)
)
Adjust this formula based on your actual column names and structure.
Create a Running Total Measure: Now, create a measure for the running total. This measure should accumulate the differences for each month. Here's an example:
RunningTotal =
CALCULATE(
SUM('YourTable'[Difference]),
FILTER(
ALL('Date'[Month]),
'Date'[Month] <= MAX('Date'[Month])
)
)
Again, adjust the table and column names accordingly.
Visualize the Data: Finally, use a line chart or any suitable visualization to display the running total over time. Put the Date field on the x-axis and the RunningTotal measure on the y-axis.
These steps should help you create a Power BI report that shows the running total of differences in "liquid assets" over time. Adjust the formulas based on your actual data model and requirements.
Check out the November 2025 Power BI update to learn about new features.
Advance your Data & AI career with 50 days of live learning, contests, hands-on challenges, study groups & certifications and more!
| User | Count |
|---|---|
| 9 | |
| 7 | |
| 6 | |
| 6 | |
| 5 |
| User | Count |
|---|---|
| 24 | |
| 21 | |
| 18 | |
| 14 | |
| 14 |