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holeinone10
Frequent Visitor

Time Intelligence Creating Daily Data Model from Monthly Data

What is the best way to convert monthly projections to compare against daily results?   The source is beginning of month, average daily rate, total days running, and total monthly production.  I already have a calendar table by date with BOM, EOM, days, etc.

4 REPLIES 4
v-juanli-msft
Community Support
Community Support

Hi @holeinone10 

Could you show some example data?

 "month, average daily rate, total days running, and total monthly production"

What are these fields ? columns or measures?

In the same table or not?

 

Best Regards
Maggie

The data table represents production for various plants by month and by product line which I want to reitterate as a daily average to reflect actual daily rate vs. forecast for the final output in the second table using measures.

 

LOCATIONPRODUCT LINEMONTHRUN
DAYS
DAILY PRODUCTON RATEPRODUCTION
woodburychocolate05/01/20193122,581700,000
woodburychocolate06/01/20193030,000900,000
woodburychocolate07/01/20193119,355600,000
woodburychocolate08/01/20193122,581700,000
woodburychocolate09/01/20193030,000900,000

 

  est by monthactual by date avg sold by month  
dateproduction
capacity
production
forecated
production
actual
%capcontractedshipped
actual
ending inventory
06/09/2019         32,000         30,000 94%        26,667                  46,437
06/08/2019         32,000         30,000 94%        26,667                  43,104
06/07/2019         32,000         30,000 94%        26,667                  39,771
06/06/2019         32,000         30,000 94%        26,667                  36,437
06/05/2019         32,000         30,000 94%        26,667                  33,104
06/04/2019         32,000         30,000 94%        26,667                  29,771
06/03/2019         32,000         30,000 94%        26,667                  26,437
06/02/2019         32,000         30,000 94%        26,667                  23,104
06/01/2019         32,000         30,000 94%        26,667                  19,771
05/31/2019         32,000         22,581 71%        23,333                  16,437
05/30/2019         32,000         22,581           25,00078%        23,333     24,000                 17,190
05/29/2019         32,000         22,581           19,00059%        23,333     24,000                 16,190
05/28/2019         32,000         22,581           19,50061%        23,333     24,000                 21,190
05/27/2019         32,000         22,581           19,70062%        23,333     24,000                 25,690
05/26/2019         32,000         22,581           19,99062%        23,333     24,000                 29,990
05/25/2019         32,000         22,581           25,00078%        23,333     23,000                 34,000

Hi @holeinone10 

The second table is what you have in your dataset or what you expect to achieve?

 

Best Regards
Maggie

Hopefully, the result. 

 

The data table represents production for various plants by month and by product line which I want to reitterate as a daily average to reflect actual daily rate vs. forecast for the final output in the second table using measures.

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