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Hi!
Im a beginner in PowerBI.
I need help in creating this view.
Suppose I have this transactional dataset.
What I want to get are the counts of customers with consistent transaction for the past 3 months, 6 months, and even 12 months (relative to the month of reference and category)
Here's the result I would want to achieve:
I think this can be resolved through DAX but let I am open with any suggestions.
Thanks!!
Solved! Go to Solution.
Hi,
Please check the below picture and the attached pbix file.
I tried to create a sample pbix file like below.
Past 3 months consistent customers count: =
VAR _selectedcategory =
VALUES ( Category[Category] )
VAR _pastmonthsnumberselect = 3
VAR _selectedmonthenddate =
MAX ( 'Calendar'[End of Month] )
VAR _startdate =
EOMONTH ( _selectedmonthenddate, - _pastmonthsnumberselect ) + 1
VAR _monthlycalendartable =
SUMMARIZE (
FILTER (
ALL ( 'Calendar' ),
'Calendar'[Date] <= _selectedmonthenddate
&& 'Calendar'[Date] >= _startdate
),
'Calendar'[Month-Year]
)
VAR _newtable =
FILTER (
SUMMARIZE (
ADDCOLUMNS (
FILTER (
SUMMARIZE (
ALL ( Data ),
Category[Category],
Customer[Cust_ID],
'Calendar'[Month-Year]
),
'Calendar'[Month-Year]
IN _monthlycalendartable
&& Category[Category] IN _selectedcategory
),
"@amountsum", CALCULATE ( SUM ( Data[Amount] ) )
),
Customer[Cust_ID],
'Calendar'[Month-Year],
[@amountsum]
),
[@amountsum] <> 0
)
VAR _groupbycustomer =
FILTER (
GROUPBY (
_newtable,
Customer[Cust_ID],
"@monthcount", SUMX ( CURRENTGROUP (), 1 )
),
[@monthcount] >= _pastmonthsnumberselect
)
VAR _result =
COUNTROWS ( _groupbycustomer )
RETURN
_result + 0
Past 6 months consistent customers count: =
VAR _selectedcategory =
VALUES ( Category[Category] )
VAR _pastmonthsnumberselect = 6
VAR _selectedmonthenddate =
MAX ( 'Calendar'[End of Month] )
VAR _startdate =
EOMONTH ( _selectedmonthenddate, - _pastmonthsnumberselect ) + 1
VAR _monthlycalendartable =
SUMMARIZE (
FILTER (
ALL ( 'Calendar' ),
'Calendar'[Date] <= _selectedmonthenddate
&& 'Calendar'[Date] >= _startdate
),
'Calendar'[Month-Year]
)
VAR _newtable =
FILTER (
SUMMARIZE (
ADDCOLUMNS (
FILTER (
SUMMARIZE (
ALL ( Data ),
Category[Category],
Customer[Cust_ID],
'Calendar'[Month-Year]
),
'Calendar'[Month-Year]
IN _monthlycalendartable
&& Category[Category] IN _selectedcategory
),
"@amountsum", CALCULATE ( SUM ( Data[Amount] ) )
),
Customer[Cust_ID],
'Calendar'[Month-Year],
[@amountsum]
),
[@amountsum] <> 0
)
VAR _groupbycustomer =
FILTER (
GROUPBY (
_newtable,
Customer[Cust_ID],
"@monthcount", SUMX ( CURRENTGROUP (), 1 )
),
[@monthcount] >= _pastmonthsnumberselect
)
VAR _result =
COUNTROWS ( _groupbycustomer )
RETURN
_result + 0
# Detension =
VAR __n = MAX( SPAN[Consecutive] )
VAR __p = DATESINPERIOD( DATES[Date], MAX( DATES[Date] ), - __n, MONTH )
RETURN
COUNTROWS(
FILTER(
VALUES( DATA[Cust_ID] ),
CALCULATE( DISTINCTCOUNT( DATES[Yr-Mn] ), CALCULATETABLE( DATA, __p ) ) = __n
)
) + 0
| Thanks to the great efforts by MS engineers to simplify syntax of DAX! Most beginners are SUCCESSFULLY MISLED to think that they could easily master DAX; but it turns out that the intricacy of the most frequently used RANKX() is still way beyond their comprehension! |
DAX is simple, but NOT EASY! |
Hi,
Please check the below picture and the attached pbix file.
I tried to create a sample pbix file like below.
Past 3 months consistent customers count: =
VAR _selectedcategory =
VALUES ( Category[Category] )
VAR _pastmonthsnumberselect = 3
VAR _selectedmonthenddate =
MAX ( 'Calendar'[End of Month] )
VAR _startdate =
EOMONTH ( _selectedmonthenddate, - _pastmonthsnumberselect ) + 1
VAR _monthlycalendartable =
SUMMARIZE (
FILTER (
ALL ( 'Calendar' ),
'Calendar'[Date] <= _selectedmonthenddate
&& 'Calendar'[Date] >= _startdate
),
'Calendar'[Month-Year]
)
VAR _newtable =
FILTER (
SUMMARIZE (
ADDCOLUMNS (
FILTER (
SUMMARIZE (
ALL ( Data ),
Category[Category],
Customer[Cust_ID],
'Calendar'[Month-Year]
),
'Calendar'[Month-Year]
IN _monthlycalendartable
&& Category[Category] IN _selectedcategory
),
"@amountsum", CALCULATE ( SUM ( Data[Amount] ) )
),
Customer[Cust_ID],
'Calendar'[Month-Year],
[@amountsum]
),
[@amountsum] <> 0
)
VAR _groupbycustomer =
FILTER (
GROUPBY (
_newtable,
Customer[Cust_ID],
"@monthcount", SUMX ( CURRENTGROUP (), 1 )
),
[@monthcount] >= _pastmonthsnumberselect
)
VAR _result =
COUNTROWS ( _groupbycustomer )
RETURN
_result + 0
Past 6 months consistent customers count: =
VAR _selectedcategory =
VALUES ( Category[Category] )
VAR _pastmonthsnumberselect = 6
VAR _selectedmonthenddate =
MAX ( 'Calendar'[End of Month] )
VAR _startdate =
EOMONTH ( _selectedmonthenddate, - _pastmonthsnumberselect ) + 1
VAR _monthlycalendartable =
SUMMARIZE (
FILTER (
ALL ( 'Calendar' ),
'Calendar'[Date] <= _selectedmonthenddate
&& 'Calendar'[Date] >= _startdate
),
'Calendar'[Month-Year]
)
VAR _newtable =
FILTER (
SUMMARIZE (
ADDCOLUMNS (
FILTER (
SUMMARIZE (
ALL ( Data ),
Category[Category],
Customer[Cust_ID],
'Calendar'[Month-Year]
),
'Calendar'[Month-Year]
IN _monthlycalendartable
&& Category[Category] IN _selectedcategory
),
"@amountsum", CALCULATE ( SUM ( Data[Amount] ) )
),
Customer[Cust_ID],
'Calendar'[Month-Year],
[@amountsum]
),
[@amountsum] <> 0
)
VAR _groupbycustomer =
FILTER (
GROUPBY (
_newtable,
Customer[Cust_ID],
"@monthcount", SUMX ( CURRENTGROUP (), 1 )
),
[@monthcount] >= _pastmonthsnumberselect
)
VAR _result =
COUNTROWS ( _groupbycustomer )
RETURN
_result + 0
@JLMJ , Have date table, and have month year in your table/sales table
Sales Month = format([Date], "YYYYMM")
Rolling 3= CALCULATE(distinctcount(Sales[Sales Month]),DATESINPERIOD('Date'[Date ],MAX('Date'[Date ]),-3,MONTH))
Continue in the last three months
countx(filter(Values(Sales[Customer]) , [Rolling 3]=3) , [Customer])
Same way change rolling to 6, 12 to get the number
To get the best of the time intelligence function. Make sure you have a date calendar and it has been marked as the date in model view. Also, join it with the date column of your fact/s. Refer :radacad sqlbi My Video Series Appreciate your Kudos.
Why Time Intelligence Fails - Powerbi 5 Savior Steps for TI :https://youtu.be/OBf0rjpp5Hw
https://amitchandak.medium.com/power-bi-5-key-points-to-make-time-intelligence-successful-bd52912a5b...
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