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Anonymous
Not applicable

how to added hierarchy to values in matrix visual

Hi, here is my sample data:

data_quarterdata_monthsalessales_Asales_Bcostcost_Acost_Bcost_Cmarginmargin_Amargin_Bmargin_Cmargin_%
Q1 2022.OCT   141,561  164,003  109,044  635,947  414,608     74,985  146,354  551,997  109,829  331,168  111,000389.94%
Q1 2022.NOV   181,679  224,267  150,175  832,144  556,121  113,022  163,001  699,471  158,824  434,847  105,800385.00%
Q1 2022.DEC   102,562  126,920     86,276  474,110  315,758     65,232     93,120  394,064     87,300  245,651     61,113384.22%
Q1 2023.Q1      79,117     97,347     63,899  358,034  240,363     47,790     69,881  305,406     71,524  189,196     44,687386.02%
Q2 2023.JAN 90.490.183.4          27983.498.197.2          312102.3102.3107.0344.61%
Q2 2023.FEB      14,822     10,856     12,174     35,308     12,174     14,159       8,975     28,234       9,060       9,060     10,114190.48%
Q2 2023.MAR      47,377     48,592     46,547  141,519     46,547     51,164     43,808  129,397     42,312     42,312     44,773273.12%
Q2 2023.Q2   119,339  117,654     96,907  314,987     96,907  109,274  108,806  320,194  102,826  102,826  114,543268.31%
Q3 2023.APR   181,538  177,101  155,627  491,814  155,627  174,598  161,589  477,825  154,198  154,198  169,430263.21%
Q3 2023.MAY   102,562  126,920     86,276  474,110  315,758     65,232     93,120  394,064     87,300  245,651     61,113384.22%
Q3 2023.JUN      79,117     97,347     63,899  358,034  240,363     47,790     69,881  305,406     71,524  189,196     44,687386.02%
Q3 2023.Q3 90.490.183.4          27983.498.197.2          312102.3102.3107.0344.61%
Q4 2023.JUL      14,822     10,856     12,174     35,308     12,174     14,159       8,975     28,234       9,060       9,060     10,114190.48%
Q4 2023.AUG      47,377     48,592     46,547  141,519     46,547     51,164     43,808  129,397     42,312     42,312     44,773273.12%
Q4 2023.SEP   119,339  117,654     96,907  314,987     96,907  109,274  108,806  320,194  102,826  102,826  114,543268.31%
Q4 2023.Q4   181,538  177,101  155,627  491,814  155,627  174,598  161,589  477,825  154,198  154,198  169,430263.21%

I want to create a matrix to show values in rows and these values should displayed in hierarchy, and put the date_quarter and date_month dimensions in columns.

here is what it displayed after simply drap the columns and values and I switched values to rows:

olive100101_0-1683251484498.pngolive100101_1-1683251516751.png

 

one problem is that I cannot display the values in a hierarchical relationship, here is the expected result:

olive100101_0-1683256148073.png

do you have any solutions? Thank you

 

1 ACCEPTED SOLUTION

In order to analyze the table effectively, it should be tall and open.
The PBI engine cannot work with pivoted tables in a flexible manner
It must be done at the source of the data or in the PQ.
In this case, Dax manipulations will be cumbersome and ineffective.
If this post helps, then please consider Accepting it as the solution to help the other members find it more quickly.

View solution in original post

3 REPLIES 3
Ritaf1983
Super User
Super User

Hi @Anonymous 
To achieve your goal and to analyze your data you need firstly unpivot your table.
Please Follow nex steps :
In PQ

Select 2 first columns and unpivot the others

Ritaf1983_0-1683254131045.png

in the next step Filter your subtotals:

Ritaf1983_1-1683254230332.png

In this stage, you have your measures an dates.
Now let's have a "measure group" column.
You can achieve it easily with "column from example"

Ritaf1983_2-1683254591203.png

than close and apply

Ritaf1983_3-1683254640409.png

Result:

Ritaf1983_4-1683254738298.png

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

Anonymous
Not applicable

Thank you. actually the real data is more complicated because these are divide calculations so that it is not convenient to transform via PQ, do you have alternative DAX soultions? Thank you.

In order to analyze the table effectively, it should be tall and open.
The PBI engine cannot work with pivoted tables in a flexible manner
It must be done at the source of the data or in the PQ.
In this case, Dax manipulations will be cumbersome and ineffective.
If this post helps, then please consider Accepting it as the solution to help the other members find it more quickly.

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