When creating Time Intelligence Measures with Energy BI or in Cloth in Semantic Fashions, it may be essential to create a date vary to calculate the outcome for a selected time-frame.
To be exact, virtually the entire Time Intelligence features in Dax create a listing of dates for a date vary.
However typically we should create a customized date vary as a consequence of particular necessities.
DAX presents us two features for this job:
Each features take a Begin Date as a parameter.
However for the Finish Date, the habits is totally different.
Whereas DATESINPERIOD() takes Intervals (Days, Months, Quarters, Years), DATESBETWEEN() takes a specified Date used because the Finish Date.
In distinction, DATEADD() makes use of the present Filter Context to get the Begin Date and to calculate the Finish Date.
However we wish to cross a Begin Date, which might differ from the Date(s) within the present Filter Context.
That is when one of many features talked about above comes into play.
On the finish of this text, I’ll present you a sensible instance utilizing the methods proven right here.
Instruments and state of affairs
Like in lots of different articles, I exploit DAX Studio to jot down DAX Queries and analyze the outcomes.
If you’re not aware of writing DAX queries, learn my piece on how one can study to jot down such queries:
This time, I exploit the Knowledge mannequin just for the Date desk.
I wish to calculate a date vary ranging from Might 5. 2025 and both 25 days or 2 Months into the long run.
To set the beginning date, I exploit this expression:
DEFINE
VAR StartDate = "2025-05-05"
EVALUATE
{ StartDate }That is the lead to DAX Studio:
I outline a Variable and assign the results of the date expression for the next queries.
One other strategy to outline the beginning date is to create a date worth utilizing DATE(2025, 05, 05).
The outcome would be the identical.
The distinction between these two approaches is that the primary returns a string, however the second returns a correct date.
The DAX features used right here can work with each.
Utilizing DATESINPERIOD()
Let’s begin with DATEINPERIOD().
I’ll use this operate to get a date vary string from the Begin Date and 25 days into the long run:
DEFINE
VAR StartDate = "2025-05-05"
EVALUATE
DATESINPERIOD('Date'[Date]
,StartDate
,25
,DAY)The result’s a desk with 25 rows for the times ranging from Might 05, 2025, to Might 29, 2025:
Now, let’s barely change the question to get a listing of all dates from the Begin Date to 2 Months into the long run:
DEFINE
VAR StartDate = "2025-05-05"
EVALUATE
DATESINPERIOD('Date'[Date]
,StartDate
,2
,MONTH)The question returns 61 rows ranging from Max 05, 2025, till July 04, 2025:
I can cross the interval with an arbitrary variety of days (e.g., 14, 28, 30, or 31 days), and the operate mechanically calculates the date vary.
Once I cross unfavourable numbers, the date vary goes to the previous, beginning with the beginning date.
Utilizing DATESBETWEEN()
Now, let’s have a look at DATESBETWEEN().
DATESBETWEEN() takes a Begin- and an Finish-Date as parameters.
This implies I need to calculate the top date earlier than utilizing it.
Once I wish to get a date vary from Might 05 to Might 29, 2025, I need to use the next question:
DEFINE
VAR StartDate = "2025-05-05"
VAR EndDate = "2025-05-25"
EVALUATE
DATESBETWEEN('Date'[Date]
,StartDate
,EndDate)The outcome is identical as with DATESINPERIOD().
Nevertheless, there may be one essential level: The tip date is included within the outcome.
This implies I can write one thing like this to get a date vary over two months from Might 05 to July 05, 2025:
DEFINE
VAR StartDate = "2025-05-05"
VAR EndDate = "2025-07-05"
EVALUATE
DATESBETWEEN('Date'[Date]
,StartDate
,EndDate)The result’s similar to the one utilizing DATESINPERIOD() and month because the interval, however with one row extra:
This offers me extra flexibility to create the date ranges, as I can pre-calculate the top date in keeping with my wants.
Use in Measures – a sensible instance.
I can use these strategies to calculate a operating whole in a Measure.
However we should take care to make use of the 2 features in the correct method
For instance, to calculate the operating whole per 30 days for 25 days.
Have a look at the next code, the place I outline two Measures utilizing the 2 features:
DEFINE
MEASURE 'All Measures'[25DayRollingTotal_A] =
VAR DateRange =
DATESINPERIOD('Date'[Date]
,MIN ( 'Date'[Date] )
,25
,DAY)
RETURN
CALCULATE ( [Sum Online Sales]
, DateRange )
MEASURE 'All Measures'[25DayRollingTotal_B] =
VAR DateRange =
DATESBETWEEN ( 'Date'[Date]
,MIN ( 'Date'[Date] )
,MIN ( 'Date'[Date] ) + 25 )
RETURN
CALCULATE ( [Sum Online Sales]
, DateRange )
EVALUATE
CALCULATETABLE (
SUMMARIZECOLUMNS (
'Date'[Year]
,'Date'[Month]
,"Gross sales", [Sum Online Sales]
,"25DayRollingTotal_A", [25DayRollingTotal_A]
,"25DayRollingTotal_B", [25DayRollingTotal_B]
)
,'Date'[Date] >= DATE(2023, 01, 01) && 'Date'[Date] <= DATE(2023, 12, 31)
)
ORDER BY 'Date'[Month]That is the outcome:
Discover the distinction between the 2 outcomes.
It’s because DATESBETWEEN() consists of the top date within the outcome, whereas DATESINPERIOD() provides the variety of intervals to the beginning date however consists of the beginning date.
Attempt it out with the next question:
DEFINE
VAR StartDate = DATE(2025,05,05)
VAR EndDate = StartDate + 25
EVALUATE
DATESINPERIOD('Date'[Date]
,StartDate
,25
,DAY)
EVALUATE
DATESBETWEEN('Date'[Date]
,StartDate
,EndDate)The primary returns 25 rows (Might 05 – Might 29, 2025) and the second returns 26 rows (Might 05 – Might 30, 2025).
Subsequently, I need to change one of many two Measures to get the identical outcome.
On this case, the calculation definition is: Begin from the primary date and go 25 into the long run.
The corrected logic is that this:
DEFINE
MEASURE 'All Measures'[25DayRollingTotal_A] =
VAR DateRange =
DATESINPERIOD('Date'[Date]
,MIN ( 'Date'[Date] )
,25
,DAY)
RETURN
CALCULATE ( [Sum Online Sales]
, DateRange )
MEASURE 'All Measures'[25DayRollingTotal_B] =
VAR DateRange =
DATESBETWEEN ( 'Date'[Date]
,MIN ( 'Date'[Date] )
,MIN ( 'Date'[Date] ) + 24 ) // 24 as an alternative of 25 days
RETURN
CALCULATE ( [Sum Online Sales]
, DateRange )
EVALUATE
CALCULATETABLE (
SUMMARIZECOLUMNS (
'Date'[Year]
,'Date'[Month]
,"Gross sales", [Sum Online Sales]
,"25DayRollingTotal_A", [25DayRollingTotal_A]
,"25DayRollingTotal_B", [25DayRollingTotal_B]
)
,'Date'[Date] >= DATE(2023, 01, 01) && 'Date'[Date] <= DATE(2023, 12, 31)
)
ORDER BY 'Date'[Month]Now, each measures return the identical outcome:
I examined the efficiency of each features for a similar calculation (Rolling whole over 25 days), and the outcomes had been equal. There was no distinction in efficiency or effectivity between these two.
Even the execution plan is identical.
Which means DATEINPERIOD() is a shortcut operate for DATESBETWEEN().
Conclusion
From a performance standpoint, each of the proven features are virtually equal.
The identical applies from the efficiency standpoint.
They differ in the best way the top date is outlined.
DATESINPERIOD() is predicated on calendar intervals, like days, months, quarters, and years.
This operate is used when the date vary have to be calculated based mostly on the calendar.
However when we’ve a pre-defined finish date or should calculate the date vary between two pre-defined dates, the DATESBETWEEN() operate is the operate to make use of.
For instance, I exploit DATESBETWEEN() when performing Time Intelligence calculations for weeks.
You may learn this piece to study extra about weekly calculations:
As you possibly can learn, I retailer the beginning and finish dates of the week for every row within the knowledge desk.
This manner, I can simply search for every date’s begin and finish dates.
So, after we should choose between these two features, it’s not a matter of performance however of necessities outlined by the stakeholders of the brand new studies or the wanted knowledge evaluation.
Learn this text to discover ways to accumulate and interpret Efficiency knowledge with DAX Studio:
Like in my earlier articles, I exploit the Contoso pattern dataset. You may obtain the ContosoRetailDW Dataset without spending a dime from Microsoft here.
The Contoso Knowledge will be freely used below the MIT License, as described in this document. I modified the dataset to shift the information to up to date dates.
