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!Calling all Data Engineers! Fabric Data Engineer (Exam DP-700) live sessions are back! Starting October 16th. Sign up.
Hello everyone,
I hope you are well, I will be really grateful for the person who can help me !
Let's consider the following data :
table : item (sample)
Item_Desc | Date | Quantity | Unit_Cost | Inventory_Value |
01591A | item3 | 05/01/2022 | 1 | 5715 | 5715 |
01591A | item3 | 13/01/2022 | -2 | 5715 | -11430 |
01591A | item3 | 02/02/2022 | 3 | 5715 | 17145 |
01591A | item3 | 03/02/2022 | -2 | 11430 | -11430 |
01591A | item3 | 08/02/2022 | -2 | 5715 | -11430 |
01591A | item3 | 10/02/2022 | 4 | 11430 | 22860 |
01591A | item3 | 16/02/2022 | -1 | 11430 | -5715 |
01591A | item3 | 22/02/2022 | 2 | 11430 | 11430 |
01591A | item3 | 23/02/2022 | -2 | 5715 | -11430 |
01591A | item3 | 02/03/2022 | 3 | 5715 | 17145 |
01464D | item1 | 04/03/2022 | 0 | 632,5 | 0 |
01464D | item1 | 08/03/2022 | -2 | 1265 | -1265 |
01591A | item3 | 08/03/2022 | 3 | 5715 | 17145 |
01591A | item3 | 16/03/2022 | 3 | 5715 | 17145 |
02161A | item4 | 18/03/2022 | 59 | 135,2397 | 7979 |
02161A | item4 | 22/03/2022 | -2 | 270,4794 | -270 |
02161A | item4 | 23/03/2022 | -2 | 270,4794 | -270 |
02161A | item4 | 24/03/2022 | -2 | 135,2397 | -270 |
02161A | item4 | 28/03/2022 | -3 | 135,2397 | -406 |
01591A | item3 | 30/03/2022 | 3 | 5715 | 17145 |
02161A | item4 | 01/04/2022 | -2 | 135,2397 | -270 |
01591A | item3 | 04/04/2022 | 3 | 5715 | 17145 |
021612A | item4 | 05/04/2022 | -2 | 135,2397 | -270 |
02221B | item5 | 05/04/2022 | 29 | 220,9791 | 6408 |
01464D | item1 | 06/04/2022 | -2 | 1265 | -1265 |
02161A | item4 | 06/04/2022 | -2 | 135,2397 | -270 |
02221B | item5 | 06/04/2022 | 29 | 220,9791 | 6408 |
01464D | item1 | 07/04/2022 | 41 | 1265 | 25933 |
01591A | item3 | 07/04/2022 | -2 | 5715 | -11430 |
02161A | item4 | 07/04/2022 | -5 | 135,2397 | -676 |
02161A | item4 | 11/04/2022 | -4 | 135,2397 | -541 |
01591A | item3 | 12/04/2022 | 3 | 5715 | 17145 |
02161A | item4 | 12/04/2022 | -2 | 135,2397 | -270 |
02161A | item4 | 14/04/2022 | -3 | 135,2397 | -406 |
02221B | item5 | 14/04/2022 | -2 | 220,9791 | -442 |
02221B | item5 | 15/04/2022 | -2 | 441,9582 | -442 |
02161A | item4 | 19/04/2022 | -2 | 135,2397 | -270 |
02221B | item5 | 20/04/2022 | -2 | 220,9791 | -442 |
02161A | item4 | 22/04/2022 | -2 | 135,2397 | -270 |
01464D | item1 | 26/04/2022 | -2 | 1265 | -1265 |
02161A | item4 | 26/04/2022 | -5 | 270,4794 | -676 |
02161A | item4 | 27/04/2022 | -2 | 270,4794 | -270 |
02161A | item4 | 28/04/2022 | 99 | 135,2397 | 13389 |
022219B | item5 | 28/04/2022 | -2 | 441,9582 | -442 |
01591A | item3 | 29/04/2022 | -2 | 11430 | -11430 |
... | ... | ... | ... | ... |
schema associated
The dynamic index is obtained by the following measure :
What I want is to compute for each row the cumulated "Inventory_Value" based on the measure "dynamic_index" .
Results expected
This will enable me to know dynamically (by switching between YearMonth) which items represent 80% of the total "Inventory_Value".
Thank you
Solved! Go to Solution.
You don't need the dynamic index for that. All you need to do is accumulate all values that are bigger or equal to the current value.
Cumul =
var a = sum('Item'[Inventory_Value])
var b = CALCULATETABLE(SUMMARIZE('Item','Item'[Item_Desc],"s",sum('Item'[Inventory_Value])),ALLSELECTED())
var c = filter(b,[s]>=a)
return sumx(c,[s])
and you can do the percentage the same way
Cumul % =
var a = sum('Item'[Inventory_Value])
var b = CALCULATETABLE(SUMMARIZE('Item','Item'[Item_Desc],"s",sum('Item'[Inventory_Value])),ALLSELECTED())
var c = filter(b,[s]>=a)
return divide(sumx(c,[s]),sumx(b,[s]),0)
You don't need the dynamic index for that. All you need to do is accumulate all values that are bigger or equal to the current value.
Cumul =
var a = sum('Item'[Inventory_Value])
var b = CALCULATETABLE(SUMMARIZE('Item','Item'[Item_Desc],"s",sum('Item'[Inventory_Value])),ALLSELECTED())
var c = filter(b,[s]>=a)
return sumx(c,[s])
and you can do the percentage the same way
Cumul % =
var a = sum('Item'[Inventory_Value])
var b = CALCULATETABLE(SUMMARIZE('Item','Item'[Item_Desc],"s",sum('Item'[Inventory_Value])),ALLSELECTED())
var c = filter(b,[s]>=a)
return divide(sumx(c,[s]),sumx(b,[s]),0)
Oh my god, that's so amazing! This code is so elegant and helps me solve the dynamic Pareto problem on the sub-category!!!!
To implement real-time filtering out of the Pareto sub-category on category, you only need to do the following operations.
Cumul % =
var a = sum('Item'[Inventory_Value])
var b = CALCULATETABLE(SUMMARIZE('Item','Item'[Item_Desc],"s",sum('Item'[Inventory_Value]),REMOVEFILTERS('Item'[Sub_Category]))
var c = filter(b,[s]>=a)
return
divide(sumx(c,[s]),sumx(b,[s]),0)
Thank you very much !
It works well for me.
Join the Fabric FabCon Global Hackathon—running virtually through Nov 3. Open to all skill levels. $10,000 in prizes!
Check out the October 2025 Power BI update to learn about new features.
User | Count |
---|---|
10 | |
7 | |
5 | |
4 | |
3 |
User | Count |
---|---|
12 | |
11 | |
10 | |
9 | |
8 |