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I'm wanting to do a calculation to create a column or calculated measure using 2 values on differing rows. My data is a flat file (excel) and the table shown below contains a hierachy that I've created. I'm wanting to forcast numbers by using the retention (calculated measure) from the previous block and mulitplying that my current enrolled. Block 1 forecast will always be 0 and the hierarchy levels above block will be a sum of the forecasted block 1 and 2. See example below, the green box indicates what I want to mulitple by.
Any help greatly appreciated and from my own digging around indexing seems the only option though getts messy with hierarchy.
Solved! Go to Solution.
Hi @Anonymous ,
Based on your picture, I think it is the part of your data I will just focus on the forecast result ignoring the sum value of other two fields [Retention] and [Enrolled].
Also, since the [Retention] is a measure, I have created a simple sum measure to imitate it in my sample file:
Retention = SUM('Table'[value])
To get the previous row value in this case to calculate the forecast value, you can create this measure:
Forecast =
VAR tab =
SUMMARIZE (
'Table',
'Table'[Department],
'Table'[Class],
'Table'[Block],
'Table'[Enrolled],
"prows",
VAR _pre =
CALCULATE (
MAXX ( 'Table', [Retention] ),
FILTER (
ALL ( 'Table' ),
'Table'[Department] IN DISTINCT ( 'Table'[Department] )
&& 'Table'[Class] IN DISTINCT ( 'Table'[Class] )
&& 'Table'[Block]
= CALCULATE (
MAX ( 'Table'[Block] ),
FILTER (
ALL ( 'Table' ),
'Table'[Department] IN DISTINCT ( 'Table'[Department] )
&& 'Table'[Class] IN DISTINCT ( 'Table'[Class] )
&& 'Table'[Block] < MAX ( 'Table'[Block] )
)
)
)
)
RETURN
IF ( ISBLANK ( _pre ), 0, _pre )
)
RETURN
SUMX ( tab, [prows] * [Enrolled] )
Attached my sample file in the below, hopes to help you.
Best Regards,
Community Support Team _ Yingjie Li
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi @Anonymous ,
Based on your picture, I think it is the part of your data I will just focus on the forecast result ignoring the sum value of other two fields [Retention] and [Enrolled].
Also, since the [Retention] is a measure, I have created a simple sum measure to imitate it in my sample file:
Retention = SUM('Table'[value])
To get the previous row value in this case to calculate the forecast value, you can create this measure:
Forecast =
VAR tab =
SUMMARIZE (
'Table',
'Table'[Department],
'Table'[Class],
'Table'[Block],
'Table'[Enrolled],
"prows",
VAR _pre =
CALCULATE (
MAXX ( 'Table', [Retention] ),
FILTER (
ALL ( 'Table' ),
'Table'[Department] IN DISTINCT ( 'Table'[Department] )
&& 'Table'[Class] IN DISTINCT ( 'Table'[Class] )
&& 'Table'[Block]
= CALCULATE (
MAX ( 'Table'[Block] ),
FILTER (
ALL ( 'Table' ),
'Table'[Department] IN DISTINCT ( 'Table'[Department] )
&& 'Table'[Class] IN DISTINCT ( 'Table'[Class] )
&& 'Table'[Block] < MAX ( 'Table'[Block] )
)
)
)
)
RETURN
IF ( ISBLANK ( _pre ), 0, _pre )
)
RETURN
SUMX ( tab, [prows] * [Enrolled] )
Attached my sample file in the below, hopes to help you.
Best Regards,
Community Support Team _ Yingjie Li
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
@Anonymous , Can you share sample data and sample output in table format? Or a sample pbix after removing sensitive data.
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