need to understand

hey, 

its a good practice and performance topic here, for little model and simple models you wont see much of a impact but as the tablas, data, complexity growth you can end up with some ugle babies data model, making refresh slow, visuals slow, ineficient, and impact user experience for the reports, also its better for building datasets with several tablas using dates, 

1) basically you turn off the in build date model for each table from the report option

2) configure a dimensianal table for managing dates

3) relantionship between them

this will make making report easier, and over time will keep your model simplier and with better performance

doing this its something the diferrence between a 1GB or 10GB dataset convert it down to 1MB dataset, and isnt exagerating the case !!!

guys in a cube show a greate video about these and overral experience and creating this type of tables:  https://www.youtube.com/channel/UCFp1vaKzpfvoGai0vE5VJ0w 

if this helped give some kudos and mark as solution for others to find.

Hi abc_777 ,

In my sample data, I created the following measures, and they all returned the correct results.

PARALLELPERIOD_BM = 
CALCULATE(
    SUM(BMCalendar[value]),
    PARALLELPERIOD( BMCalendar[Date], -1, MONTH)
)

PARALLELPERIOD_Sale = 
CALCULATE(
    SUM(SaleDate[Sales]),
    PARALLELPERIOD( SaleDate[Date], -1, MONTH )
)

I think we get different results because of different calculation contexts. Could you please share your sample data and models? That can help us find the cause faster. 

Best Regards,
Winniz

Hi abc_777 ,

Does your problem have been solved? If it is solved, please mark a reply which is helpful to you.

If the problem is still not resolved, please provide detailed error information or the expected result you expect. Let me know immediately, looking forward to your reply.

Best Regards,
Winniz