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I encountered one challenge on my power BI report design recently, could anyone please advise on it?
My source summary table looks as below, but is with very large size.
ym_id | DIGIT_USER | MOB_USER | … | lndg_tot_bal | bcn_scr | … | customer |
202211 | 0 | 0 | … | 5040830 | 9160 | … | 14 |
202211 | 0 | 0 | … | 3315879 | 7740 | … | 11 |
202211 | 0 | 0 | … | 480094.2 | 662 | … | 1 |
202211 | 0 | 0 | … | 1089981 | 717 | … | 1 |
202211 | 0 | 0 | … | 8083.89 | 862 | … | 1 |
I have generated around 30 new measurements based on those attributes variables, and two examples are as below:
The next step, I create two fields as below to group both Segments Variables andAttributes Variables. The use the two fields to control the final matrix.
Segment fields: This is used to select the segment variable for comparison, such as selecting comparison based on “Digit_User” or “Mob_User”.
Attributes fields: This field includes all 30 different measurements from the corresponded attributes, such as “Average_Beacon_Score” and “Average_Lending_Balance”.
Based on above design, I can get a matrix as below:
Then I get the matrix as below with “Switch values to row” option.
So far, everything looks good. But I am struggled on creating “Level Difference” and “% difference” comparison within and without category comparison. For example, in month of 202212, if I would like to get difference of average beacon score between digital users (653.11) and non-digital user (549.88), I always failed on it. I think this can be done by DAX, but not clear how to apply DAX on fields rather than single column.
Q1: So, could anyone please help to advise if field can be used in the measurement to handle multiple attributes together? Especially how to use field in filter within the measurement?
Q2: May I know if power BI also provide some advance data transpose method? For example, I can transpose the 30 attributes variables (eg. Beacon Score & Lending Balance) by the 33 segments columns (Digit_User, MOB_User and YM_ID).
Any advice will be appreciated!
Thanks a lot!
Wayne
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