Calculate between two fact tables

[chewkarann]

Dear Forum Community, 

First time posting here.  Hope you could help.

I have two fact tables as below:

.

Each "Staff" could be associated to one or *more* "Department" in every month.  Each "Department" has one "Income" every month.  

For each Staff, I need to get the "Total Income" and the "Average Income", across all the "Department" he/she associated to.  Two values required: a) total and average across all the months, b) total and average in each month.  

What is the DAX measure code to get these values?  

Then, in my visual, I will plot graph/table showing the value for each month, using "Calendar[Month]" as my axis/row.  

Kind regards, 

Kar Ann 

[Greg_Deckler · Accepted solution]

@chewkarann Maybe:

Measure Each Month =
  VAR __StaffDept = DISTINCT('Fact Staff'[Department])
  VAR __Table = FILTER('Fact Department', [Department] IN __StaffDept)
  VAR __Total = SUMX(__Table, [Income])
  VAR __Average = AVERAGEX(__Table, [Income])
  VAR __Result = __Total // __Average
RETURN
  __Result


Measure All Months =
  VAR __StaffDept = DISTINCT('Fact Staff'[Department])
  VAR __Table = FILTER(ALL('Fact Department'), [Department] IN __StaffDept)
  VAR __Total = SUMX(__Table, [Income])
  VAR __Average = AVERAGEX(__Table, [Income])
  VAR __Result = __Total // __Average
RETURN
  __Result

[Greg_Deckler · Accepted solution]

@chewkarann Maybe:

Measure Each Month =
  VAR __StaffDept = DISTINCT('Fact Staff'[Department])
  VAR __Table = FILTER('Fact Department', [Department] IN __StaffDept)
  VAR __Total = SUMX(__Table, [Income])
  VAR __Average = AVERAGEX(__Table, [Income])
  VAR __Result = __Total // __Average
RETURN
  __Result


Measure All Months =
  VAR __StaffDept = DISTINCT('Fact Staff'[Department])
  VAR __Table = FILTER(ALL('Fact Department'), [Department] IN __StaffDept)
  VAR __Total = SUMX(__Table, [Income])
  VAR __Average = AVERAGEX(__Table, [Income])
  VAR __Result = __Total // __Average
RETURN
  __Result

[Anonymous · Accepted solution]

Hi @chewkarann,

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Regards,

Xiaoxin Sheng

[chewkarann]

@Greg_Deckler  THANKS so much, Greg!!  And sorry for the late reply.