Being an SSAS newbie, I was wondering if it's possible to create a calculated member that references an individual row's value as well as the aggregated value in order to create a percentage?
For example, if I have a fact table with ValueA, I'd like to create a calculate member that essentially performed:
[Measures].[ValueA] (for each row I've sliced the data by) / [Measures].[ValueA] (the total)
Also I'd like to keep the total as the sum of whatever's been filtered in the cube browser. I feel certain this must be possible but I'm clearly missing something.
You can use the Axis function. Her is an example:
WITH MEMBER [Measures].[Percentage] AS
[Measures].[ValueA] / (Axis(1).CurrenMember.Parent, [Measures].[ValueA])
SELECT {[Measures].[ValueA], [Measures].[Percentage]} ON 0,
'what you want' ON 1
FROM your cube
(You may need to add check in the calculated member expression)
Related
I am trying to create a formula in Calculated measure but none is working correctly
Dimension Cell has multiple members including Control and Core. I also have measure called [Measures].[Rate] which is precalculated as percentage
I need to achieve below formula
(([Measures].[Rate] in [Cell].[ABC].&[Control] and [Cell].[ABC].&[Core])
- ([Measures].[Rate] not in [Cell].[ABC].&[Control] and [Cell].[ABC].&[Core]))
/ ([Measures].[Rate] in [Cell].[ABC].&[Control] and [Cell].[ABC].&[Core])
Something like (A+B)/A but I am not able to calculate individual A and B.
Please note [Measures].[Rate] is in percentage format so cannot be summed up
EDIT
Also any idea if the same above has to be done with two slices from different dimension for single measure
eg.
([Measures].[Rate] in [Cell].[ABC].&[Control] and [Cell].[ABC].&[Core] also in [Data].[PQR].&[Yes])
or
SUM (
{ [Cell].[ABC].&[Control] , [Cell].[ABC].&[Core] }
,{[Data].[PQR].&[Yes])}
,[Measures].[A]
)
Is above workable or what will be its syntax
Uhmm maybe something like:
CREATE MEASURE [Measures].[SpecialRate]
AS
AGGREGATE({[Cell].[ABC].&[Control],[Cell].[ABC].&[Core]}, [Measures].[Rate])
- AGGREGATE(EXCEPT([Cell].[ABC].MEMBERS,{[Cell].[ABC].&[Control],[Cell].[ABC].&[Core]}), [Measures].[Rate])
/ AGGREGATE({[Cell].[ABC].&[Control],[Cell].[ABC].&[Core]}, [Measures].[Rate])
,VISIBLE = 1;
The easiest way is to redesign the Cell dimension to include a new rollup column which includes both Control and Core into one rollup.
If that's not feasible and you have to do it in MDX then one way is to create a calculated measure on the dimension and then use it:
CREATE MEMBER CurrentCube.[Cell].[ABC].[All].[Control and Core] as
AGGREGATE({[Cell].[ABC].&[Control], [Cell].[ABC].&[Core]})
,VISIBLE=0;
CREATE MEMBER CurrentCube.[Cell].[ABC].[All].[Not Control and Core] as
AGGREGATE(-{[Cell].[ABC].&[Control], [Cell].[ABC].&[Core]})
,VISIBLE=0;
CREATE MEMBER CurrentCube.[Measures].[My Calc] as
(([Measures].[Rate], Cell].[ABC].[All].[Control and Core])
- ([Measures].[Rate], Cell].[ABC].[All].[Not Control and Core]))
/ ([Measures].[Rate], Cell].[ABC].[All].[Control and Core]);
I have a measure [Measures].[myMeasure] that I would like to create several derivatives of based on the related attribute values.
e.g. if the related [Location].[City].[City].Value = "Austin" then I want the new calculated measure to return the value of [Measures].[myMeasure], otherwise, I want the new calculated measure to return 0.
Also, I need the measure to aggregate correctly meaning sum all of the leaf level values to create a total.
The below works at the leaf level or as long as the current member is set to Austin...
Create Member CurrentCube.[Measures].[NewMeasure] as
iif(
[Location].[City].currentmember = [Location].[City].&[Austin],
[Measures].[myMeasure],
0
);
This has 2 problems.
1 - I don't always have [Location].[City] in context.
2. When multiple cities are selected this return 0.
I'm looking for a solution that would work regardless of whether the related dimension is in context and will roll up by summing the atomic values based on a formula similar to above.
To add more context consider a transaction table with an amount field. I want to convert that amount into measures such as payments, deposits, return, etc... based on the related account.
I don't know the answer but just a couple of general helpers:
1 You should use IS rather than = when comparing to a member
2 You should use null rather than 0 - 0/NULL are effecitvely the same but using 0 will slow things up a lot as the calculation will be fired many more times. (this might help with the second section of your question)
Create Member CurrentCube.[Measures].[NewMeasure] as
iif(
[Location].[City].currentmember IS [Location].[City].&[Austin],
[Measures].[myMeasure],
NULL
);
I'm building a cube in MS BIDS. I need to create a calculated measure that returns the weighted-average of the rank value weighted by the number of searches. I want this value to be calculated at any level, no matter what dimensions have been applied to break-down the data.
I am trying to do something like the following:
I have one measure called [Rank Search Product] which I want to apply at the lowest level possible and then sum all values of it
IIf([Measures].[Searches] IS NOT NULL, [Measures].[Rank] * [Measures].[Searches], NULL)
And then my weighted average measure uses this:
IIf([Measures].[Rank Search Product] IS NOT NULL AND SUM([Measures].[Searches]) <> 0,
SUM([Measures].[Rank Search Product]) / SUM([Measures].[Searches]),
NULL)
I'm totally new to writing MDX queries and so this is all very confusing to me. The calculation should be
([Rank][0]*[Searches][0] + [Rank][1]*[Searches][1] + [Rank][2]*[Searches][2] ...)
/ SUM([searches])
I've also tried to follow what is explained in this link http://sqlblog.com/blogs/mosha/archive/2005/02/13/performance-of-aggregating-data-from-lower-levels-in-mdx.aspx
Currently loading my data into a pivot table in Excel is return #VALUE! for all calculations of my custom measures.
Please halp!
First of all, you would need an intermediate measure, lets say Rank times Searches, in the cube. The most efficient way to implement this would be to calculate it when processing the measure group. You would extend your fact table by a column e. g. in a view or add a named calculation in the data source view. The SQL expression for this column would be something like Searches * Rank. In the cube definition, you would set the aggregation function of this measure to Sum and make it invisible. Then just define your weighted average as
[Measures].[Rank times Searches] / [Measures].[Searches]
or, to avoid irritating results for zero/null values of searches:
IIf([Measures].[Searches] <> 0, [Measures].[Rank times Searches] / [Measures].[Searches], NULL)
Since Analysis Services 2012 SP1, you can abbreviate the latter to
Divide([Measures].[Rank times Searches], [Measures].[Searches], NULL)
Then the MDX engine will apply everything automatically across all dimensions for you.
In the second expression, the <> 0 test includes a <> null test, as in numerical contexts, NULL is evaluated as zero by MDX - in contrast to SQL.
Finally, as I interpret the link you have in your question, you could leave your measure Rank times Searches on SQL/Data Source View level to be anything, maybe just 0 or null, and would then add the following to your calculation script:
({[Measures].[Rank times Searches]}, Leaves()) = [Measures].[Rank] * [Measures].[Searches];
From my point of view, this solution is not as clear as to directly calculate the value as described above. I would also think it could be slower, at least if you use aggregations for some partitions in your cube.
I have a query to pull clickthrough for a funnel, where if a user hit a page it records as "1", else NULL --
SELECT datestamp
,COUNT(visits) as Visits
,count([QE001]) as firstcount
,count([QE002]) as secondcount
,count([QE004]) as thirdcount
,count([QE006]) as finalcount
,user_type
,user_loc
FROM
dbname.dbo.loggingtable
GROUP BY user_type, user_loc
I want to have a column for each ratio, e.g. firstcount/Visits, secondcount/firstcount, etc. as well as a total (finalcount/Visits).
I know this can be done
in an Excel PivotTable by adding a "calculated field"
in SQL by grouping
in PowerPivot by adding a CalculatedColumn, e.g.
=IFERROR(QueryName[finalcount]/QueryName[Visits],0)
BUT I need give the report consumer the option of slicing by just user_type or just user_loc, etc, and excel will tend to ADD the proportions, which won't work b/c
SUM(A/B) != SUM(A)/SUM(B)
Is there a way in DAX/MDX/PowerPivot to add a calculated column/measure, so that it will be calculated as SUM(finalcount)/SUM(Visits), for any user-defined subset of the data (daterange, user type, location, etc.)?
Yes, via calculated measures. calculated columns are for creating values that you want to see on rows/columns/report header...calculated measures are for creating values that you want to see in the values section of a pivot table and can slice/dice by the columns in the model.
The easiest way would be to create 3 calculated "measures" in the calculation area of the powerpivot sheet.
TotalVisits:=SUM(QueryName[visits])
TotalFinalCount:=SUM(QueryName[finalcount])
TotalFinalCount2VisitsRatio:=[TotalFinalCount]/[TotalVisits]
You can then slice the calculated measure [TotalFinalCount2VisitsRatio] by user_type or just user_loc (or whatever) and the value will be calculated correctly. The difference here is that you are explicitly telling the xVelocity engine to SUM-then-DIVIDE. If you create the calculated column, then the engine thinks you want to DIVIDE-then-SUM.
Also, you don't have to break down the measure into 3 separate measures...it's just good practice. If you're interested in learning more, I'd recommend this book...the author is the PowerPivot/DAX guru and the book is very straightforward.
I have created new measure that counts distinct policies (this measure is called FK Policy Distinct Count).
Then I created new calculated member called CountPolicyEndorsesNull which counts all policies from FK Policy Distinct Count using a filter:
(([Policy].[Endorses].&[0],[FK Policy Distinct Count]).
Than I did new calculated member called CountPolicy:
SUM(EXCEPT([Policy].[Policy Status].[Policy Status],[Policy].[Policy Status].&[Void]), [Measures].[CountPolicyEndorsesNull])
Next, I created a new member CountNewBound
SUM(
{
[Submission].[Tran Type].&[New], [Submission].[Tran Type].&[Developed]
},
[Measures].[CountPolicy]
)
And finally, YTDCountNewBound
SUM(YTD([Invoice Date].[Date Hierarchy].CurrentMember), [Measures].[CountNewBound])
Obviously, SUM function doesn't work in this case. Any idea how to make proper YTD count for calculated member?
Distinct count is a special measure which should be managed with a little more care. The rational behind this is that the when evaluating the measure a set of previous values is kept in memory. In order to improve performance, this structure is not passed and it's quickly converted to a scalar value.
Going back to your problem :
Distinct count can be evaluated over a tuple without problem, but you'll get in problems once you try to evaluate over a set of tuples. A possible, but costly and not always possible, is to create a hierarchy of values so you can convert your set in a member of a dimension.
In your case instead of using YTD([Invoice Date].[Date Hierarchy].CurrentMember) function using another hierarchy -> [Invoice Date].[YTD Date Hierarchy].
All this depends on the specific OLAP implementation you're using, but I guess holds true for mainly all OLAP vendors.