Custom Rollup in SSAS - ssas

I have created in SSAS a cube that represents “the value of counters measured from network element in a period of time” so the structure of the cube will be as follow:
Dimensions:
- Time
- Counter
- Network Element (a parent-child dimension)
Fact :
- Value: which represent the numeric value measured of the counter
For some counters, I must do the rollup of the value by calculating the average.
I’m using SQL Server 2012 Enterprise Edition, I tried to create a column in the dimension Counter to hold the MDX expression of the custom rollup so the expression to perform the average rollup by the dimension Network element (NE) for the counter [433] will be:
Avg([NE].[NE Parent SK].CURRENTMEMBER.CHILDREN, ([Measures].[Value],[Counter].[Counter SK].&[433]))
[Measures].[Value]: is the fact.
When I browse the cube this counter is disappeared which mean it has the NULL value.
I tried to use calculated member [Average] which is calculated as follow:
[Measures].[Value]/[Measures].[Value Count]
[Measures].[Value Count] is a default measure caculated by SSAS.
Then I put in custom rollup column this MDX expression:
[Measures].[Average]
When I browse the cube this counter is disappeared which mean it has the NULL value.
My second problem is : how can I perform two different rollup calculation with each dimension (in my case: time & Network Element)

Related

Is there any ways to dynamic cumulative measure in MDX?

All of the measure that I want to cumulative has the same formula. So, is there any way to use the thing like function or any thing in calculate measure to resolve this issue?
There are two ways to achieve your aim:
1- the first solution is based on using the business intelligence wizard to add time intelligence to your solution.
The time intelligence enhancement is a cube enhancement that adds time calculations (or time views) to a selected hierarchy. This enhancement supports the following categories of calculations:
List item
Period to date.
Period over period growth.
Moving averages.
Parallel period comparisons.
The wizard will let you chose the calculations and measures you want to apply.
Visit : https://learn.microsoft.com/en-us/analysis-services/multidimensional-models/define-time-intelligence-calculations-using-the-business-intelligence-wizard
Visit : http://www.ssas-info.com/analysis-services-articles/62-design/2465-ssas-time-intelligence-wizard
2- Use a dimension table to calculate your calculations, this solution is more complicated, but very powerful and one of the best practices.
The first step is to create a new physical dimension, with real
members for each of the calculations we're going to need. We don't
actually need to create a table in our data warehouse for this
purpose, we can do this with an SQL view like this
CREATE VIEW DateTool AS SELECT ID_Calc = 1, Calc = 'Real Value' UNION ALL SELECT ID_Calc = 2, Calc = 'Year To Date'
Next, we need to add this view to our DSV and create a dimension based
on it. The dimension must have one hierarchy and this hierarchy must
have its IsAggregatable property set to False. The DefaultMember
property of this hierarchy should then be set to the Real Value
member. Giving this dimension a name can be quite difficult, as it
should be something that helps the users understand what it does –
here we've called it Date Tool. It needs no relationship to any
measure group at all to work.
Our next task is to overwrite the value returned by each member so
that they return the calculations we want. We can do this using a
simple SCOPE statement in the MDX Script of the cube:
this code let you create the YEAR-TO-DATE aggregation for all your measures.
SCOPE ([Date Tool].[Calculation].[Year To Date]); THIS = AGGREGATE ( YTD ([Date Order].[Calendar].CurrentMember), [Date Tool].[Calculation].[Real Value]); END SCOPE;
Visit:https://subscription.packtpub.com/book/big_data_and_business_intelligence/9781849689908/6/ch06lvl1sec35/calculation-dimensions

Sum-up and then calculate vs. calculate and then sum-up (SSAS-MDX)

I have a cube in SSAS multidimensional mode.
I have created a calculating measure in visual studio called "Total Cost". The formula is:
[Measures].[Unit Cost]*[Measures].[Qty]
It is in the lowest level of granularity (i.e. - the transnational level information has these fields).
The formula works well, as long as I present the data in this same level of granularity (for example, when I create a pivot and the rows are transaction IDs - like the source file)
However, when I present it in an aggregate format (for example - by customer) - then instead of making the calculation and then sum it up, it sum up and then calculate.
Here is what I expected:
Expected results vs. What I get
My understanding, that this is regardless a (correct/incorrect) hierarchy structure. In other words, I expected this calculation to work even without defining any hierarchy between the transaction ID level and the customer level.
I'd appreciate your help!
In your SSAS project ->datasource view, you need to add a named calculation. This would be "[Unit Cost]*[Qty]". Now add this named calculation as a Measure in your Cube. This do the job. This problem was already addressed in the following link.
https://stackoverflow.com/questions/53554284/how-to-multiply-two-measures-prior-to-aggregation/53558733#53558733

How the aggregation and calculated members work as combined to produce output in SSAS Cube

I am creating a POC on the SSAS. Ultimate goal is to be able to perform any kind of the calculation either ad hoc calculation or pre calculated with good performance. Existing solutions is based on the SQL server but due to the performance issues with huge data facing issues.
I need some insight upon how the Cube works to give faster outputs. I have created date dimensions with hierarchy Year-> Semester-> Quarter -> Month -> Week -> Date. Several other dimensions are linked with the date dimension. My cube has almost 10 to 15 dimension which have several role playing dimensions.There are almost two to three dates in every fact table.
How the Cube aggregates the data based on the dimensions linked to the facts?
Does it internally creates all the combination of the dimension values and saves the fact aggregate data internally?
Here i have attached an MDX script which hase YTD,MTD,QTD Calculated Measures.[Measures].[Value] measure has to be added based on the function applied on the date dimension. Does SSAS internally sum up the [Measures].[Value] for various hierarchy of the date/Other dimension/s? What exactly SSAS does to provide the final value fast?
Our system has large number of the fields whose calculation depends on the value selected by the end user to the number has to be calculated at run time by aggregating some other measures. Does SSAS is fast to provide the Calcualted Member output by using the internally aggregated values generated during the cube processing?
With Member [Measures].[YTDValue] as ([Measures].[Value],
OpeningPeriod([Rundate].[Calendar].[Date],[Rundate].[Calendar].CurrentMember.Parent.Parent.Parent.Parent.Parent))
Member [Measures].[QTDValue]
as ([Measures].[Value],OpeningPeriod([Rundate].[Calendar].[Date],[Rundate].[Calendar].CurrentMember.Parent.Parent.Parent))
Member [Measures].[MTDValue]
as ([Measures].[Value],OpeningPeriod([Rundate].[Calendar].[Date],[Rundate].[Calendar].CurrentMember.Parent.Parent))
SELECT
{
[Measures].[YTDValue],
[Measures].[QTDValue],
[Measures].[MTDValue],
} on 0,
{
[Rundate].[Calendar].[Date].Members
} ON 1
FROM
(
select
{
[Rundate].[Calendar].[Date].&[2015-01-09T00:00:00]
} on 0
from [Cube_Sample]
)

SSAS Max calculation in cube

I have a dimension list of Product Codes and a measure called ACV in my cube. I need to be able to calculate the maximum ACV value for each product code.
I have got as far as the calculation below but that returns the sum of ACV for all products.
MAX([Products].[Product Code].[Product Code].Members, [Measures].[ACV])
I'd be grateful for input on how to resolve my problem.
Thanks!
If you want the maximum evaluated semiadditively by the grain of your model designed in the data source view, you should add a new measure (based on the same source field as the ACV measure) to your cube add set its AggregationFunction property to Max. More on aggregation functions in SSAS.

Access system tables in calculation

Is there a way to access system tables in a SSAS cube calcuation?
For example the following query can be executed on a SSAS cube to return a last processed date:
SELECT LAST_DATA_UPDATE FROM $System.MDSCHEMA_CUBES WHERE CUBE_NAME = 'Cube'
How would one access this information in a calculation?
Background: We were using ASSP before (a third party sproc) to get the last cube processed date. Recently, this sproc threw an exception on one of our cubes and caused SSAS to go down. Using the above line of MDX did not have this behavior. I would rather not have our cube depend on third party code so I am looking for a way to access LAST_DATA_UPDATE in a calc for a specific cube name.
I usually include a detached Dimension in my cubes e.g. ".Cube Information" which includes attributes like this. Other useful attributes could expose the currency of the data e.g. when did the last underlying ETL process complete, or the release/build of your cube.
I feed this "Cube Information" dimension from a SQL view which returns a single row with whatever data is needed - you could use your SELECT statement. It also needs to return a Key column with a fixed value e.g. 1.
By "detached" I mean the "Cube Information" dimension has no entries in the Cube Dimension Relationship tab.
In the cube Calculation script, I assign the DEFAULT_MEMBER property for that dimension to the fixed Key value from the SSAS view.
Any client tool can then access those Dimension attributes.