Access system tables in calculation - sql

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.

Related

SSAS OLAP Cube - Sum measure only works when keys are present

(This is a mock of my actual setup to help me figure out the problem.)
I have one fact table and one dimension table, linked by an id field.
My goal is to make a measure that sums up all "thing_count" (integer) values in my cube.
If the user splits by nothing, it should show the total "thing_count" for all records in the fact table. If it's split by "category_name" from the dimension, it should show the total "thing_count" for each category.
I tried to achieve this by creating a SUM measure in my cube:
It works, but not in the way I intend it to
It always shows (null) unless I drag in the "id" field from the dimension.
Measure only:
Measure and category:
Measure, category, and id:
How can I make the measure show the value without keys needing to be present?
Edit:
For GregGalloway's request (I've edited the names so the screenshots are easier to follow):
One common explanation for this behavior (no aggregation) is that you have inadvertently commented out the CALCULATE; statement in your MDX script in the cube. Please check that statement is still present.

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

SSAS: How to handle date dimension when date is null

I'm trying to add a new column to my SSAS cube. The column is a date field, and links to my DimDate table (a Date dimension). This date represents the project completion date.
However.... not all of the projects have a project completion date due to old projects not ever being assigned this value. And this is expected. We don't want to put bogus dates into the field just to get SSAS to work.
When processing the cube, it crashes with:
Errors in the OLAP storage engine: The attribute key cannot be found when
processing: Table: 'dbo_FactMyTable', Column: 'MyDate_id', Value: '0'.
The attribute is 'Date Id'.
I can't disable "missing values" for the entire project because in most cases, this really is an error. How can I disable missing values for this dimension?
Or is there a better way to handle missing dates/values like this?
Small correction - based on your question, you need to change Processing error handling for special Measure Group, not Dimension. You can do it for all dimensions linked to some measure group, but not to specific dimension.
You can process individual measure group with _Table: 'dbo_FactMyTable'_ first with necessary missing value settings, and then - process rest of your cube with default settings.
Main problem here - how to process rest of the cube. You might have sophisticated system which creates processing XMLA scripts dynamically based on data update knowledge (I do it with SSIS); in this case you would not ask this question. Suppose your environment is simpler - you update cube and would like to process it as a whole completely. In such scenario I would sudgest the following workflow:
Process Default all Dimensions (will do initial processing or in structure changes)
Process Update all Dimensions
Process Cube with Unprocess - invalidating it
Process your special measure group
Process Cube with Process Default
This will first update Dimensions, then - clear processing status flag from all measure groups in the Cube. After that you process your measure group with special flags; this set processing status for this MG. And then during Process Default on Cube - only unprocessed MGs will be covered, which excludes your special MG from processing scope.
The answer is a bit complicated, but this article did a great job of explaining it, including screen shots for the SSAS-challenged like me.
http://msbusinessintelligence.blogspot.com/2015/06/handling-null-dates-in-sql-server.html?m=1

SSAS hide measure for certain dimension

How to hide measure or a scope if user choose certain dimension or go to certain dimension hierarchy level?
Thanks.
Try something like this in your MDX script:
FREEZE([Measures].[My Measure], [Product].[Subcategory].[All]);
([Measures].[My Measure], [Product].[Product].Members, [Product].[Subcategory].[Subcategory].Members) = null;
Freeze ensures the next statement won't null out the category level totals. The next statement bulls out that measure for the whole product dimension up to the subcategory totals but not above.
Note this is fine for nulling out meaningless numbers but isn't a security feature. A savvy user could do a drillthrough command to get the product level numbers. Or a savvy user could connect in a special way and clear the whole MDX script for his session so he sees the detailed product data.
For a more secure approach:
If you can null out product data for all measures then setup role based security. In dimension data security only grant access to member Subcategory.All only but uncheck visual totals on the advanced tab so that the subcategory grand total is the real total.
Or setup a second slimmed down Product dimension that only has the top levels not the detailed product levels. Then only tie that dimension to this measure group.
Or create a second measure group that does a group by in SQL and joins to the Product dimension only at the Category level. Thus there is no detailed data only rollups. Then with security control whether a used sees the detailed measures or the summary measures.
On measure properties you can set set visible property to false for the measure you want to hide. Another option is to use perspective and choose again what you want to hide or not.

Managing PerformancePoint Filters With Slowly Changing Dimensions

Just a bit of background info:
I have dimension table which uses SCD2 to track user changes in our company (team changes, job title changes etc) See example below:
I've built an Analysis Services Cube and created all the necessary hierarchy's for the dimensions and it works well when navigating and drilling down through the fact table.
The problem I have is with the filters on the PerformancePoint dashboard. As I'm using the User Dimension table with it's multiple instances of users it's showing duplicates up in the list. I can understand why as the surrogate ID is being referenced on the Dimension. But if I choose the first instance of the A-team I will see all their sales for a particular period and if I choose the second instance I will see all their sales for a different period.
What is the best way to handle this type of behavior? Ideally I'd like to see a distinct list of teams in alphabetical order and when I choose the team name it shows all of their data over time.
I've considered using MDX query filters but I'd like to see if there's anything I haven't thought about.
I realise this isn't an easy and quick question but any help would be appreciated!
The answer was simple after having a trawl through my User Dimension table on the Cube.
Under my user dimension I added 2 duplicate attributes to my attributes list ("Team Filter" is a copy of "Team", "User Filter" a copy of "User Name") these will be used only for filtering the dashboard.
Under the attribute properties for each duplicate I then set AttributeHierarchyOptimizedState to "Not Optimized", I also set their AttributeHierarchyVisible to false as I'd shown the two duplicate attributes in the hierarchy window in the middle.
Deploy your Cube to the server and go in to PerformancePoint. Create a new MDX Filter (this image shows the finished filter)
This is the code I used, it only shows dimension members which have a fact against them (reduces the list a considerable amount) and by using allmembers at the dimension it also gives me the option to show "All" at the top of the list.
Deploy the new filters and now you can see the distinct list of users and teams, works perfectly and selects every instance (regardless of the SCD2 row)