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Hi Experts,
I have a below requirement. I need help to find the solution:
Granularity: The grain of data is hour.
I have a requirement to get
1. Column Grand total ( in attached image ) each hour level.
2. Find the maximum grand total of each hour in day.
3. Find the maximum grand total in the month.
4. How can drill to detail level. ( Drill from max value on which date and time in the month)
Expected Result:-
Here, let say maximum of value of the day on 1st-Jan-20 is 55886(grand total), recorded on 11:00 PM,
and Maximum value of the month is recorded on 24-Jan-20 on 6:00 PM.
Source data
| Date | Time | Org | Sales |
| 1-Jan-20 | 1:00:00 | ORG5 | 19000 |
| 1-Jan-20 | 1:00:00 | ORG2 | 10000 |
| 1-Jan-20 | 1:00:00 | ORG1 | 5112 |
| 1-Jan-20 | 1:00:00 | ORG3 | 900 |
| 1-Jan-20 | 1:00:00 | ORG4 | 500 |
| 1-Jan-20 | 2:00:00 | ORG5 | 19001 |
| 1-Jan-20 | 2:00:00 | ORG2 | 9501 |
| 1-Jan-20 | 2:00:00 | ORG1 | 5109 |
| 1-Jan-20 | 2:00:00 | ORG4 | 500 |
| 1-Jan-20 | 3:00:00 | ORG5 | 19002 |
| 1-Jan-20 | 3:00:00 | ORG2 | 10002 |
| 1-Jan-20 | 3:00:00 | ORG1 | 5102 |
| 1-Jan-20 | 3:00:00 | ORG3 | 2700 |
| 1-Jan-20 | 3:00:00 | ORG4 | 500 |
| 1-Jan-20 | 4:00:00 | ORG5 | 19003 |
| 1-Jan-20 | 4:00:00 | ORG2 | 8903 |
| 1-Jan-20 | 4:00:00 | ORG1 | 5107 |
| 1-Jan-20 | 4:00:00 | ORG3 | 3600 |
| 1-Jan-20 | 4:00:00 | ORG4 | 500 |
| 1-Jan-20 | 5:00:00 | ORG5 | 19004 |
| 1-Jan-20 | 5:00:00 | ORG2 | 11004 |
| 1-Jan-20 | 5:00:00 | ORG1 | 5100 |
| 1-Jan-20 | 5:00:00 | ORG3 | 4500 |
| 1-Jan-20 | 5:00:00 | ORG4 | 500 |
| 1-Jan-20 | 6:00:00 | ORG5 | 19005 |
| 1-Jan-20 | 6:00:00 | ORG2 | 10505 |
| 1-Jan-20 | 6:00:00 | ORG3 | 5400 |
| 1-Jan-20 | 6:00:00 | ORG1 | 5093 |
| 1-Jan-20 | 6:00:00 | ORG4 | 500 |
| 1-Jan-20 | 7:00:00 | ORG5 | 19006 |
| 1-Jan-20 | 7:00:00 | ORG2 | 13006 |
| 1-Jan-20 | 7:00:00 | ORG3 | 6300 |
| 1-Jan-20 | 7:00:00 | ORG1 | 5154 |
| 1-Jan-20 | 7:00:00 | ORG4 | 500 |
| 1-Jan-20 | 8:00:00 | ORG5 | 19007 |
| 1-Jan-20 | 8:00:00 | ORG2 | 14007 |
| 1-Jan-20 | 8:00:00 | ORG3 | 7200 |
| 1-Jan-20 | 8:00:00 | ORG1 | 5173 |
| 1-Jan-20 | 8:00:00 | ORG4 | 500 |
| 1-Jan-20 | 9:00:00 | ORG5 | 19008 |
| 1-Jan-20 | 9:00:00 | ORG2 | 10008 |
| 1-Jan-20 | 9:00:00 | ORG3 | 8100 |
| 1-Jan-20 | 9:00:00 | ORG1 | 5124 |
| 1-Jan-20 | 9:00:00 | ORG4 | 500 |
| 1-Jan-20 | 10:00:00 | ORG5 | 19009 |
| 1-Jan-20 | 10:00:00 | ORG2 | 9509 |
| 1-Jan-20 | 10:00:00 | ORG3 | 9000 |
| 1-Jan-20 | 10:00:00 | ORG1 | 5127 |
| 1-Jan-20 | 10:00:00 | ORG4 | 500 |
| 1-Jan-20 | 11:00:00 | ORG5 | 19010 |
| 1-Jan-20 | 11:00:00 | ORG2 | 10010 |
| 1-Jan-20 | 11:00:00 | ORG3 | 9900 |
| 1-Jan-20 | 11:00:00 | ORG1 | 5116 |
| 1-Jan-20 | 11:00:00 | ORG4 | 500 |
| 1-Jan-20 | 12:00:00 | ORG5 | 19011 |
| 1-Jan-20 | 12:00:00 | ORG3 | 10800 |
| 1-Jan-20 | 12:00:00 | ORG2 | 8911 |
| 1-Jan-20 | 12:00:00 | ORG1 | 5119 |
| 1-Jan-20 | 12:00:00 | ORG4 | 500 |
| 1-Jan-20 | 13:00:00 | ORG5 | 19012 |
| 1-Jan-20 | 13:00:00 | ORG3 | 11700 |
| 1-Jan-20 | 13:00:00 | ORG2 | 11012 |
| 1-Jan-20 | 13:00:00 | ORG1 | 5130 |
| 1-Jan-20 | 13:00:00 | ORG4 | 500 |
| 1-Jan-20 | 14:00:00 | ORG5 | 19013 |
| 1-Jan-20 | 14:00:00 | ORG3 | 12600 |
| 1-Jan-20 | 14:00:00 | ORG2 | 10513 |
| 1-Jan-20 | 14:00:00 | ORG1 | 5131 |
| 1-Jan-20 | 14:00:00 | ORG4 | 500 |
| 1-Jan-20 | 15:00:00 | ORG5 | 19014 |
| 1-Jan-20 | 15:00:00 | ORG3 | 13500 |
| 1-Jan-20 | 15:00:00 | ORG2 | 13014 |
| 1-Jan-20 | 15:00:00 | ORG1 | 5142 |
| 1-Jan-20 | 15:00:00 | ORG4 | 500 |
| 1-Jan-20 | 16:00:00 | ORG5 | 19015 |
| 1-Jan-20 | 16:00:00 | ORG3 | 14400 |
| 1-Jan-20 | 16:00:00 | ORG2 | 14015 |
| 1-Jan-20 | 16:00:00 | ORG1 | 5145 |
| 1-Jan-20 | 16:00:00 | ORG4 | 500 |
| 1-Jan-20 | 17:00:00 | ORG5 | 19016 |
| 1-Jan-20 | 17:00:00 | ORG3 | 15300 |
| 1-Jan-20 | 17:00:00 | ORG2 | 14016 |
| 1-Jan-20 | 17:00:00 | ORG1 | 5164 |
| 1-Jan-20 | 17:00:00 | ORG4 | 500 |
| 1-Jan-20 | 18:00:00 | ORG5 | 19017 |
| 1-Jan-20 | 18:00:00 | ORG3 | 16200 |
| 1-Jan-20 | 18:00:00 | ORG2 | 10017 |
| 1-Jan-20 | 18:00:00 | ORG1 | 5183 |
| 1-Jan-20 | 18:00:00 | ORG4 | 500 |
| 1-Jan-20 | 19:00:00 | ORG5 | 19018 |
| 1-Jan-20 | 19:00:00 | ORG3 | 17100 |
| 1-Jan-20 | 19:00:00 | ORG2 | 9518 |
| 1-Jan-20 | 19:00:00 | ORG1 | 5166 |
| 1-Jan-20 | 19:00:00 | ORG4 | 500 |
| 1-Jan-20 | 20:00:00 | ORG5 | 19019 |
| 1-Jan-20 | 20:00:00 | ORG3 | 18000 |
| 1-Jan-20 | 20:00:00 | ORG2 | 10019 |
| 1-Jan-20 | 20:00:00 | ORG1 | 5183 |
| 1-Jan-20 | 20:00:00 | ORG4 | 500 |
| 1-Jan-20 | 21:00:00 | ORG5 | 19020 |
| 1-Jan-20 | 21:00:00 | ORG3 | 18900 |
| 1-Jan-20 | 21:00:00 | ORG2 | 8920 |
| 1-Jan-20 | 21:00:00 | ORG1 | 5126 |
| 1-Jan-20 | 21:00:00 | ORG4 | 500 |
| 1-Jan-20 | 22:00:00 | ORG3 | 19800 |
| 1-Jan-20 | 22:00:00 | ORG5 | 19021 |
| 1-Jan-20 | 22:00:00 | ORG2 | 11021 |
| 1-Jan-20 | 22:00:00 | ORG1 | 5143 |
| 1-Jan-20 | 22:00:00 | ORG4 | 500 |
| 1-Jan-20 | 23:00:00 | ORG3 | 20700 |
| 1-Jan-20 | 23:00:00 | ORG5 | 19022 |
| 1-Jan-20 | 23:00:00 | ORG2 | 10522 |
| 1-Jan-20 | 23:00:00 | ORG1 | 5142 |
| 1-Jan-20 | 23:00:00 | ORG4 | 500 |
| 2-Jan-20 | 0:00:00 | ORG3 | 21600 |
| 2-Jan-20 | 0:00:00 | ORG5 | 19023 |
| 2-Jan-20 | 0:00:00 | ORG2 | 13023 |
| 2-Jan-20 | 0:00:00 | ORG1 | 5125 |
| 2-Jan-20 | 0:00:00 | ORG4 | 500 |
| 2-Jan-20 | 1:00:00 | ORG3 | 22399.99 |
| 2-Jan-20 | 1:00:00 | ORG5 | 19024 |
| 2-Jan-20 | 1:00:00 | ORG2 | 14024 |
| 2-Jan-20 | 1:00:00 | ORG1 | 5136 |
| 2-Jan-20 | 1:00:00 | ORG4 | 500 |
| 2-Jan-20 | 2:00:00 | ORG3 | 23299.99 |
| 2-Jan-20 | 2:00:00 | ORG5 | 19025 |
| 2-Jan-20 | 2:00:00 | ORG2 | 10025 |
| 2-Jan-20 | 2:00:00 | ORG1 | 5133 |
| 2-Jan-20 | 2:00:00 | ORG4 | 500 |
| 2-Jan-20 | 3:00:00 | ORG3 | 24199.99 |
| 2-Jan-20 | 3:00:00 | ORG5 | 19026 |
| 2-Jan-20 | 3:00:00 | ORG2 | 9526 |
| 2-Jan-20 | 3:00:00 | ORG1 | 5126 |
| 2-Jan-20 | 3:00:00 | ORG4 | 500 |
| 2-Jan-20 | 4:00:00 | ORG3 | 25099.99 |
| 2-Jan-20 | 4:00:00 | ORG5 | 19027 |
| 2-Jan-20 | 4:00:00 | ORG2 | 10027 |
| 2-Jan-20 | 4:00:00 | ORG1 | 5131 |
| 2-Jan-20 | 4:00:00 | ORG4 | 500 |
| 2-Jan-20 | 5:00:00 | ORG3 | 25999.99 |
| 2-Jan-20 | 5:00:00 | ORG5 | 19028 |
| 2-Jan-20 | 5:00:00 | ORG2 | 8928 |
| 2-Jan-20 | 5:00:00 | ORG1 | 5124 |
| 2-Jan-20 | 5:00:00 | ORG4 | 500 |
| 2-Jan-20 | 6:00:00 | ORG3 | 26899.99 |
| 2-Jan-20 | 6:00:00 | ORG5 | 19029 |
| 2-Jan-20 | 6:00:00 | ORG2 | 11029 |
| 2-Jan-20 | 6:00:00 | ORG1 | 5117 |
| 2-Jan-20 | 6:00:00 | ORG4 | 500 |
| 2-Jan-20 | 7:00:00 | ORG3 | 27799.99 |
| 2-Jan-20 | 7:00:00 | ORG5 | 19030 |
| 2-Jan-20 | 7:00:00 | ORG2 | 10530 |
| 2-Jan-20 | 7:00:00 | ORG1 | 5178 |
| 2-Jan-20 | 7:00:00 | ORG4 | 500 |
| 2-Jan-20 | 8:00:00 | ORG3 | 28699.99 |
| 2-Jan-20 | 8:00:00 | ORG5 | 19031 |
| 2-Jan-20 | 8:00:00 | ORG2 | 13031 |
| 2-Jan-20 | 8:00:00 | ORG1 | 5197 |
| 2-Jan-20 | 8:00:00 | ORG4 | 500 |
| 2-Jan-20 | 9:00:00 | ORG3 | 29599.99 |
| 2-Jan-20 | 9:00:00 | ORG5 | 19032 |
| 2-Jan-20 | 9:00:00 | ORG2 | 14032 |
| 2-Jan-20 | 9:00:00 | ORG1 | 5148 |
| 2-Jan-20 | 9:00:00 | ORG4 | 500 |
| 2-Jan-20 | 10:00:00 | ORG3 | 30499.99 |
| 2-Jan-20 | 10:00:00 | ORG5 | 19033 |
| 2-Jan-20 | 10:00:00 | ORG2 | 10033 |
| 2-Jan-20 | 10:00:00 | ORG1 | 5151 |
| 2-Jan-20 | 10:00:00 | ORG4 | 500 |
| 2-Jan-20 | 11:00:00 | ORG3 | 31399.99 |
| 2-Jan-20 | 11:00:00 | ORG5 | 19034 |
| 2-Jan-20 | 11:00:00 | ORG2 | 9534 |
| 2-Jan-20 | 11:00:00 | ORG1 | 5140 |
| 2-Jan-20 | 11:00:00 | ORG4 | 500 |
| 2-Jan-20 | 12:00:00 | ORG3 | 32299.99 |
| 2-Jan-20 | 12:00:00 | ORG5 | 19035 |
| 2-Jan-20 | 12:00:00 | ORG2 | 10035 |
| 2-Jan-20 | 12:00:00 | ORG1 | 5143 |
| 2-Jan-20 | 12:00:00 | ORG4 | 500 |
| 2-Jan-20 | 13:00:00 | ORG3 | 33199.99 |
| 2-Jan-20 | 13:00:00 | ORG5 | 19036 |
| 2-Jan-20 | 13:00:00 | ORG2 | 8936 |
| 2-Jan-20 | 13:00:00 | ORG1 | 5154 |
| 2-Jan-20 | 13:00:00 | ORG4 | 500 |
| 2-Jan-20 | 14:00:00 | ORG3 | 34099.99 |
| 2-Jan-20 | 14:00:00 | ORG5 | 19037 |
| 2-Jan-20 | 14:00:00 | ORG2 | 11037 |
| 2-Jan-20 | 14:00:00 | ORG1 | 5155 |
| 2-Jan-20 | 14:00:00 | ORG4 | 500 |
| 2-Jan-20 | 15:00:00 | ORG3 | 34999.99 |
| 2-Jan-20 | 15:00:00 | ORG5 | 19038 |
| 2-Jan-20 | 15:00:00 | ORG2 | 10538 |
| 2-Jan-20 | 15:00:00 | ORG1 | 5166 |
| 2-Jan-20 | 15:00:00 | ORG4 | 500 |
| 2-Jan-20 | 16:00:00 | ORG3 | 35899.99 |
| 2-Jan-20 | 16:00:00 | ORG5 | 19039 |
| 2-Jan-20 | 16:00:00 | ORG2 | 13039 |
| 2-Jan-20 | 16:00:00 | ORG1 | 5169 |
| 2-Jan-20 | 16:00:00 | ORG4 | 500 |
| 2-Jan-20 | 17:00:00 | ORG3 | 36799.99 |
| 2-Jan-20 | 17:00:00 | ORG5 | 19040 |
| 2-Jan-20 | 17:00:00 | ORG2 | 14040 |
| 2-Jan-20 | 17:00:00 | ORG1 | 5188 |
| 2-Jan-20 | 17:00:00 | ORG4 | 500 |
| 2-Jan-20 | 18:00:00 | ORG3 | 37699.99 |
| 2-Jan-20 | 18:00:00 | ORG5 | 19041 |
| 2-Jan-20 | 18:00:00 | ORG2 | 14041 |
| 2-Jan-20 | 18:00:00 | ORG1 | 5207 |
| 2-Jan-20 | 18:00:00 | ORG4 | 500 |
| 2-Jan-20 | 19:00:00 | ORG3 | 38599.99 |
| 2-Jan-20 | 19:00:00 | ORG5 | 19042 |
| 2-Jan-20 | 19:00:00 | ORG2 | 10042 |
| 2-Jan-20 | 19:00:00 | ORG1 | 5190 |
| 2-Jan-20 | 19:00:00 | ORG4 | 500 |
| 2-Jan-20 | 20:00:00 | ORG3 | 39499.99 |
| 2-Jan-20 | 20:00:00 | ORG5 | 19043 |
| 2-Jan-20 | 20:00:00 | ORG2 | 9543 |
| 2-Jan-20 | 20:00:00 | ORG1 | 5207 |
| 2-Jan-20 | 20:00:00 | ORG4 | 500 |
| 2-Jan-20 | 21:00:00 | ORG3 | 40399.99 |
Hi @sonuojha1 ,
I'm sorry I am not very clear on how the detailed date and time filtered based on which Org’s maximum Sale from the screenshots you gave.
Since the maximum Sale of each Org is at a different time point, for my test ,the Matrix visualization looks like this:
If the Matrix row is date+time,the drill down could not be applied, maybe you could use drill through for Sales instead.
Is the result what you want? If you have any questions, please upload more detailed data samples and expected output.
Please do mask sensitive data before uploading.
Best Regards,
Eyelyn Qin
@Anonymous Thanks for Reply Eyelyn.
I am sorry , but this is not the expected result. As I mentioned, Max of grand total of all organization.
You are taking maximum value of columns, however you have to first sum the all columns value in a row and then find the maximum.
Regards,
Sonu
@sonuojha1 This looks like a measure aggregation problem. See my blog article about that here: https://community.powerbi.com/t5/Community-Blog/Design-Pattern-Groups-and-Super-Groups/ba-p/138149
The pattern is:
MinScoreMeasure = MINX ( SUMMARIZE ( Table, Table[Group] , "Measure",[YourMeasure] ), [Measure])
MaxScoreMeasure = MAXX ( SUMMARIZE ( Table, Table[Group] , "Measure",[YourMeasure] ), [Measure])
AvgScoreMeasure = AVERAGEX ( SUMMARIZE ( Table, Table[Group] , "Measure",[YourMeasure] ), [Measure])
etc.
I think you can structure data little bit first, do the unpivoting/multirow, so you will have three columns
Date with time
Attribute(org1,org2 etc)
Value
Now you have multirow/vertical data, so you can create a measure like MAXX, try this and hope this makes sense.
@mhossainThanks for reply, Yes, I have already restructured it. I tried, but not achieved expected result.
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