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Hi,
I have a matrix as follows which shows the sales of top 15 products and the past one month (March 2020) and past 3 months (Jan-Mar) values in percentages. I would like to average the values greater than 100% by checking the individual values under the top 15 header. So in the photo below all values above 100% (which are blue) would be added and divided by 13 (all blue values except red) in case of March Sales % and same idea for Jan-Mar Sales %. I tried some formulas but it gives me the wrong results in Sales Growing Products (139% and 129.6%, see below). How can I go about solving this problem?
All the values are composed of measures like March Sales %, Jan-Mar Sales % etc. The measures used are:
Hi everyone,
I have a requirement similar to the one mentioned above. The data is of 4 Fiscal years I should be publishing a forecast based on the previous years' data. Attaching the sample data for your better understanding.
I have a matrix table built in Power Bi Matrix visual based on certain filters applied like Fiscal Year, Category etc.
Rows:
Category (Flowers,Fruits etc)
Sub Category (Rose,Tulips,Apple etc)
Column:
Week Number in a quarter (1,2,3...14)
Values:
Sales Revenue.
This matrix is built for Fy18,Fy19,Fy20. I should build the same table for FY 21 by calculating the average of the previous 3 yrs of data. I'm wondering how to do the same, earlier in Excel it was quite simple task. Since the average of the data is relative to both rows& Columns am confused on how to proceed.
FY18 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | |
Flowers | Rose | $12M | $12M | $12M | $12M | $12M | $12M | $12M | $12M | $12M | $12M | $12M | $12M | $12M | $12M |
Lilly | $13M | $13M | $13M | $13M | $13M | $13M | $13M | $13M | $13M | $13M | $13M | $13M | $13M | $13M | |
Daisy | $14M | $14M | $14M | $14M | $14M | $14M | $14M | $14M | $14M | $14M | $14M | $14M | $14M | $14M | |
Tulip | $15M | $15M | $15M | $15M | $15M | $15M | $15M | $15M | $15M | $15M | $15M | $15M | $15M | $15M | |
Fruits | Mango | $22M | $22M | $22M | $22M | $22M | $22M | $22M | $22M | $22M | $22M | $22M | $22M | $22M | $22M |
Apple | $27M | $27M | $27M | $27M | $27M | $27M | $27M | $27M | $27M | $27M | $27M | $27M | $27M | $27M | |
Orange | $39M | $39M | $39M | $39M | $39M | $39M | $39M | $39M | $39M | $39M | $39M | $39M | $39M | $39M | |
Kiwi | $44M | $44M | $44M | $44M | $44M | $44M | $44M | $44M | $44M | $44M | $44M | $44M | $44M | $44M |
you might consider creating pbix file that will contain some sample data (remove the confidential info), upload the pbix to onedrive for business and share the link to the file. Please do not forget to describe the expected results based on this sample data.
Hi @v-diye-msft ,
Thanks for the reply. I know that I might not have explained the problem with much clarity. As suggested, I have created a sample pbix file so that you can take a look to better understand the problem.
Link to sample pbix: https://1drv.ms/u/s!AjhtAEoJ85hKoxfCHQ8fZa4yDYSr?e=XmV8L7
I have also explained the problem and the expected solution a bit more in the sample file accordingly.
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