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KevinWong
New Member

Question regarding Cumulative sum

Hello PBI experts,

 

I am new to PBI and handling a project that need to use cumulative sum to deliver a dynamic summary recently.

But I am struggled in the DAX, can someone please help or provide some hits for the next step. Thanks.

 

Here below is the data I got and I need to aggragate the table and create a measure - cummulative sum based on the Ordering by each ID.

 

I can reach the result by using the below DAX when filtering each ID but I can't get the proper summarised total result when releasing the filter of the ID. Can someone please help? Thanks.

 

KevinWong_0-1704953347696.png

Total_Cumulative_Value =
SUMX(FILTER(ALLSELECTED(Data), Data[Order] > MAXX(Data, Data[Order])), [Total_Value])

 

KevinWong_0-1704946162033.pngKevinWong_3-1704947137178.png

 

 

And here below is the expected outcome, summarized by the aggregated table

KevinWong_2-1704946367080.png

 

 

1 ACCEPTED SOLUTION
v-shex-msft
Community Support
Community Support

HI @KevinWong,

You can refer to the following measure formula to calculate cumulative value based on current order value and ID group:

 

Total_Cumulative_Value =
VAR currOrder =
    MAX ( Data[Order] )
RETURN
    CALCULATE (
        SUM ( [Total_Value] ),
        FILTER ( ALLSELECTED ( Data ), Data[Order] > currOrder ),
        VALUES ( Data[ID] )
    )

 

Regards,

Xiaoxin Sheng

Community Support Team _ Xiaoxin
If this post helps, please consider accept as solution to help other members find it more quickly.

View solution in original post

1 REPLY 1
v-shex-msft
Community Support
Community Support

HI @KevinWong,

You can refer to the following measure formula to calculate cumulative value based on current order value and ID group:

 

Total_Cumulative_Value =
VAR currOrder =
    MAX ( Data[Order] )
RETURN
    CALCULATE (
        SUM ( [Total_Value] ),
        FILTER ( ALLSELECTED ( Data ), Data[Order] > currOrder ),
        VALUES ( Data[ID] )
    )

 

Regards,

Xiaoxin Sheng

Community Support Team _ Xiaoxin
If this post helps, please consider accept as solution to help other members find it more quickly.

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