I a new to this site and to SSAS in general. I am currently doing some "on the job training" trying to put together an SSAS cube and I am experiencing some problems.
When I try to process the Cube it fails. This happens due to the fact that the Fact table used for the cube contains some 13 rows that have dates that are outside of the range of the Date dimension that I am using.
I am not sure what I should do to get around/fix this.
Exclude the rows?
Change the dimension?
I have tried to find an answer to this on my own, but it seems that my phrasing of the issue/problem has so far stopped me from finding relevant information.
Any advice or ideas would be greatly appreciated!
/Chriss
Related
I am responsible for creating period-over-period and trend reporting for our Team's Issue Management Department. What I need to do is at copy table Issues at month-end into a new table IssuesHist and add a column with the current date example: 1/31/21. Then at the next month-end I need to take another copy of the Issues table and append it to the existing IssuesHist table, and then add the column again with the current date. For example: 2/28/21.
I need to do this to be able to run comparative analysis on a period-over-period basis. The goal is to be able to identify any activity (opening new issues, closing old ones, reopening issues, etc.) that occurred over the period.
Example tables below:
Issues Table with the current data from our front-end tool
I need to copy the above into the new IssuesHist and add a date column like so
Then at the following month end I need to do the same thing. For example if the Issues table looked like this (changes highlighted in Red)
I would need to Append that to the bottom of the existing IssuesHist table with the new Date. So that I could run queries comparing the data periods to identify any changes.
My research has shown that a Temporal Table may be the best solution here, but I am unable to DIM our existing database's tables to include system versioning.
Please let me know what solution would work, best, and if you have any SQL Statement Tips.
Thank you!
I have two tables in my Ticket Management Application, "ExpositionPeriods" and "OrganisedVisits".
ExpositionPeriods - Defines the periods for which tickets can be purchased.
OrganisedVisits - Stores the tickets purchased information.
In the example below, we have 5 periods available, and tickets have been purchased for 2 of the periods.
The customer wants a report which shows "Number of visitors against each available period". That means if, for any period which doesn't have a visitor, the report should show "0" for that period. Something like this.
So far so good. Since the production database is humongous (~500 GB), it is not advisable to report on this database directly. Things turn to be challenging when I create an OLAP cube out of this schema and try to achieve the same report functionality in the cube. It seems the cube actually performs an action similar to SQL INNER JOIN as opposed to a LEFT OUTER JOIN and hence I do not see those Periods for which there are no tickets sold.
Is this how SSAS actually behaves? Am I missing out any particular setting that will indicate the SSAS engine to process the cube in a different manner so as to include the missing periods as well? Please note, end customers don't have access to MDX/DAX scripts, they can only use the cube by drag-drop measure and dimensions like in Excel pivot table.
In your image the browser is carrying out a non empty on rows on the date dimension. If you want to show the dates with no visitors then select the option to show empty cells.
You can define such scope in "calculations" as
SCOPE
([Measures].[Visitors]);
THIS=IIF(ISEMPTY([Measures].[Visitors]),0,[Measures].[Visitors]);
END SCOPE;
So you have zeros instead of nulls and side effect. You or customer can't hide empty cells, cause now it's not empty enough.
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
I have ssas DB with two cubes, they share the date dimension.
My query shows users on the dimension and visit as a measure. In the where clause I have range of dates.
I have this strange behavior that after a FULL cube process I don't see any data when applying the range. I'm sure that I have data for the range because when I filter each day desperately I can see data.
Another weird scenario is that if the date is on the dimension I can see data.
The thing that solve it is when process DATA the cubes.
This my query:
select non empty [Users].[User].[User] columns,
{[Measures].[Visits]} on rows
from [System Visit] where
([Dim_Date].[Georgian Calendar].[Date ID].&[20150125]:[Dim_Date].[Georgian Calendar].[Date ID].&[20150202])
Any thought what can be the issue?
Thanks
If you dont have the borders defined then your filter will work like NULL:a, b:NULL, or NULL:NULL depending on availability of border in the cube.
In this case, I would suggest all possible dates into your [Dim_Date].[Date ID] attribute.
I am relatively new to this depth of MDX, but here is my dilemma. My goal is to implement a calculated member using a .Net Stored Procedure. The calculation (XIRR) will be based on a set of cash flow dates and cash flow amounts. Ideally this would be a calculation in my cube that is available as a measure to Excel/Browser users.
So to start simple I am just trying to implement my own COUNT calculated member/measure (not even using .Net) to say count the # of members in a given dimensions based on the current context. So lets say I have a dimensions Customer with a Customer Id Key. And let's say there are a total of 100 customers in my database. So Count(Customer.CustomerId.AllMembers) would be 100. Now when you start using the browser and say filter on Customer.CustomerId.&1, Customer.CustomerId.&2 (customer id 1 and 2) I would expect my count calculated member to return 2 but it returns the total 100 count. I have tried using exists. I am sure there is something that I am just fundamentally not understanding yet.
Hopefully this makes sense, would hugely appreciate any help from someone that has a good understanding of SSAS/MDX and calculations. Thanks in advance.
Marty
You may have some issues here, I did when I tried to do a similar thing.
Your calculated member is not honouring the client sub-select, which is normal. What in theory you would do is create a dynamic set, and then use that in the calculated member to force the dimension count to be evaluated in the context of the subcube your filters have created. Mosha has a good article here: http://sqlblog.com/blogs/mosha/archive/2007/08/25/mdx-in-katmai-dynamic-named-sets.aspx
So you'd end up with something like:
CREATE DYNAMIC SET CurrentCube.Customers AS
EXISTING(Customer.CustomerId.CHILDREN);
CREATE MEMBER CurrentCube.Measures.CustomerCount AS
Customers.COUNT
Now the real problem you'll have is a bug in SSAS https://connect.microsoft.com/SQLServer/feedback/details/484865/calcuated-member-with-a-reference-to-dynamic-named-set-kills-the-cubes-performance so the code above, which will probably work just fine locally, will kill a production cube. This was an exciting learning experience for me.
See if you can get any of the workarounds to work, I couldn't.
I was able to get what I wanted, but I had to create query-scoped dynamic sets as part of the MDX query, I wasn't able to create it as a cube object:
WITH DYNAMIC SET Customers AS
EXISTING(Customer.CustomerId.CHILDREN);
MEMBER Measures.CustomerCount AS
Customers.COUNT
SELECT
Measures.CustomerCount
ON COLUMNS
FROM [Cube]
WHERE Customer.CustomerId.&[1]
Let us know how you get on.