Power BI is turning 10! Tune in for a special live episode on July 24 with behind-the-scenes stories, product evolution highlights, and a sneak peek at what’s in store for the future.
Save the dateEnhance your career with this limited time 50% discount on Fabric and Power BI exams. Ends August 31st. Request your voucher.
Hi,
I need your help with the following problem. I have two different but similar tables from which I want to subtract two columns (Cost). For confidentiality reasons, I cannot provide the data but I will give a simple example:
Table A (imagine that I have multiple Product Clusters, Products, Years, etc. - this is a simplified view):
Product Cluster | Product | Year | Attribute | Cost |
A | X | 2023 | Sum | 10 |
A | X | 2023 | Cont. | 0 |
A | X | 2024 | Sum | 20 |
A | X | 2024 | Cont. | 0 |
A | X | 2025 | Sum | 30 |
A | X | 2025 | Cont. | 1 |
A | Y | 2023 | Sum | 10 |
A | Y | 2023 | Cont. | 0 |
A | Y | 2024 | Sum | 20 |
A | Y | 2024 | Cont. | 0 |
A | Y | 2025 | Sum | 30 |
A | Y | 2025 | Cont. | 1 |
A | Z | 2023 | Sum | 15 |
... | ||||
B | H | 2023 | Sum | 20 |
B | H | 2024 | Cont. | 0 |
Table B:
Product Cluster | Product | Year | Attribute | Cost |
A | X | 2023 | Sum | 9 |
A | X | 2023 | Cont. | 0 |
A | X | 2024 | Sum | 19 |
A | X | 2024 | Cont. | 0 |
A | X | 2025 | Sum | 35 |
A | X | 2025 | Cont. | 1 |
A | Y | 2023 | Sum | 12 |
A | Y | 2023 | Cont. | 0 |
A | Y | 2024 | Sum | 25 |
A | Y | 2024 | Cont. | 0 |
A | Y | 2025 | Sum | 20 |
A | Y | 2025 | Cont. | 1 |
A | Z | 2023 | Sum | 18 |
... | ||||
B | H | 2023 | Sum | 10 |
B | H | 2024 | Cont. | 0 |
Both come from the same Excel file and tab, with the only difference being the file version (version controlled on SharePoint). Many users can edit this file and I need to provide a quarterly review and capture the Delta.
Note that while transforming my data, I am filtering the data creating a new column to split the Sum from Cont. entries (Add Conditional Column filtering Sum).
What I have done is add an Index column to each table, create a 1-1 relationship and it worked. However, when I took another file version (same structure, same items on the same lines) it messed up the Indexing resulting in a mess.
I understand that the Indexing idea was not perfect as it cannot handle changes in line items - which can happen.
Is there anything else I can try?
Thanks,
George
@kg22 , you need to create common dimensions product, cluster product, attribute, year etc and join with both tables and then use them in visual
Power BI- Power Query: When I asked you to create common tables: https://youtu.be/PqfGW6pl1Sw
Power BI- DAX: When I asked you to create common tables: https://youtu.be/a2CrqCA9geM
https://medium.com/@amitchandak/power-bi-when-i-asked-you-to-create-common-tables-a-quick-dax-soluti...
Thank you for the information. I've created the proposed structure and managed to get the required visuals i.e. the Delta of all costs between the two different tables.
This is done using the following Measure:
Delta (K€) = SUM('Table A'[Cost]) - SUM('Table B'[Cost]).
However, I have added a Table below this visual to present the entries contributing to this result i.e. those having a Delta not equal to "0". While filtering out all such entries, for some reason, I am seeing most of the entries reported with their negative value.
To give an example, if a 2023 item has 10 as Cost in Table A and it is the same in Table B, I would expect the result (Delta) to be 0. However, the outcome is -10.
This is a sample of the expected result:
Product Cluster | Product | Year | Cost (Table A) | Delta |
A | X | 2023 | 10 | 1 |
A | X | 2024 | 20 | 1 |
And what I see (the second shouldn't be appearing assuming the cost is the same in both tables):
Product Cluster | Product | Year | Cost (Table A) | Delta |
A | X | 2023 | 10 | 1 |
C | L | 2026 | 20 | -20 |
However, the calculation should be ok as the visuals agree with the math (cross-checked in Excel).
Any idea why this is happening?
Thank you!
George
Check out the July 2025 Power BI update to learn about new features.
This is your chance to engage directly with the engineering team behind Fabric and Power BI. Share your experiences and shape the future.
User | Count |
---|---|
65 | |
64 | |
56 | |
39 | |
27 |
User | Count |
---|---|
85 | |
59 | |
45 | |
43 | |
38 |