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]
)
Related
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
is there a difference between a native cube measure (for example Measure1) and this mdx measure :
Measure2=[Measures].[Measure1] ?
Because when I use these measures together I dont get any results, and when I use them one by one I get what I want.
So the Cube Measures are present at the time of cube processing where the "MDX measures"(correct name is calculations) are determined at the query time. You should try to use the Cube measures where ever possible.
Secondly they can be easily used together.
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
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.
First some background: I have the typical Date dimension (similar to the one in the Adventure Works cube) and an Account dimension. In my fact table I have daily transaction amounts for the accounts.
I need to calculate cumulative transaction amounts for different accounts for different periods of time. The catch is that whatever is the first period shown on the resulting report should get its transaction amount as-is from the fact table and all the following periods in the report should have cumulative amounts.
For example, I might have a single account on rows and on columns I could have [Date].[Calendar].[Calendar Year].[&2005]:[Date].[Calendar].[Calendar Year].[&2010]. The transaction amount for 2005 should have the sum of transaction amounts that took place in 2005 for that specific account. For the following year, 2006, the transaction amount should be TransactionAmountsIn2005 + TransactionAmountsIn2006. Same goes for the remaining of the years.
My problem is that I don't really know how to specify this kind of calculated member in the cube because the end-user who is responsible for writing the actual MDX queries that produce the reports could use any range of periods on any hierarchy level of the Date dimension.
Hope this made some sense.
Teeri,
I would avoid letting the end-user actually write MDX queries and just force them to use ranges you defined. To clarify, just give them a start and end date, or a range if you will, to select and then go from there. I've worked with accounting and finance developing cubes (General Ledger, etc) for years and this is usually what they were ultimately looking for.
Good luck!