Ungroup a Running total

[Anonymous]

Hello everyone.

I have the following data:

FLVR	ITEM_SAP	Fecha Semana	#Semana	Calculo INV final
CHOCOLATE	300033915	10/09/2022	0	547
CHOCOLATE	300033915	17/09/2022	1	177
CHOCOLATE	300033915	24/09/2022	2	-11
CHOCOLATE	300033915	01/10/2022	3	383
CHOCOLATE	300033916	10/09/2022	0	240
CHOCOLATE	300033916	17/09/2022	1	7
CHOCOLATE	300033916	24/09/2022	2	8
CHOCOLATE	300033916	01/10/2022	3	-92
CHOCOLATE	300033918	10/09/2022	0	2101
CHOCOLATE	300033918	17/09/2022	1	222
CHOCOLATE	300033918	24/09/2022	2	-61
CHOCOLATE	300033918	01/10/2022	3	-21

As you can see, there are 3 different codes (ITEM SAP) and each week (from 0 to 3) has a different value for it.

I try to apply a cumulative sum with DAX for each of the codes and I get the following result:

I used the following formula:

INV Final = CALCULATE(SUMX('table',[Calculate INV final]), FILTER(ALL('table'), 'table'[#Week] <= MAX('table'[#Week]))))

This is the desired result. However, I am looking for a second view where the codes are grouped ("ITEM SAP"), summing the value of the 3 codes for each week. As follows:

The goal is that a cumulative sum can also be performed by FLVR. But leaving the same formula, the result is not the desired one.
I also tried with the following formula:
INV Final Flvr = CALCULATE([Calculate INV final], FILTER(ALL('table'), 'table'[#Week] <= MAX('table'[#Week])))).
But I get this result:

Idon't understand where is the error. Please help me to solve this.

Thank you,

Sabrina H.

[v-chenwuz-msft · Accepted solution]

Hi @Anonymous ,

Please try this:

INV final =
CALCULATE (
    SUM ( 'Table'[Calculo INV final] ),
    FILTER (
        ALLEXCEPT ( 'Table', 'Table'[FLVR], 'Table'[ITEM_SAP] ),
        [#Semana] <= MAX ( 'Table'[#Semana] )
    )
)

result:

Pbix in the post you created 

Suma acumulada con una agrupación de datos - Microsoft Power BI Community

Best Regards

Community Support Team _ chenwu zhu

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.