Adding User Configurations to an Analysis Server Cube Part 2

Part 2: Dynamic User Configurations

In Part 1 of this series, we hard-coded some MDX values into the cube. That approach works in that it produces the desired end result, but if the values need to change, a developer is needed to make it happen. What is needed is a way to persist the configuration values outside of the cube itself. In Part 2, we will create a configuration table to store the values. The structure is borrowed from that used by earlier versions of Integration Services:

Really, the only two fields absolutely required here are the Name and Value fields; the other two are added for administration and clarification. Next we’ll insert some fictional values into this configuration table:

Next, create a view that pivots the Configuration Name and Configuration Value fields with T-SQL code like this:


 

The dataset returned by this view will be a single row of data with one column for each Configuration named in the PIVOT section, and a static [DummyKey] value of -1.

 

Again, some purists may dislike my use of “SELECT * FROM …” in my view definition, but since I am limiting the columns returned via the ” . . . FOR ConfigurationName IN (…) . . .” statement of the PIVOT clause, there is not much chance of getting unneeded columns.

 

Next, add this view to the cube project Data Source View, then add it as a Measure Group to your cube. Delete the COUNT and the SUM(Dummy Key) measures that were added by the Measure Group wizard. Since there is only one row in the measure group’s base table, a SUM( ) aggregations for the configurations are fine. Lastly, since a Measure Group MUST be joined to at least one Dimension, on the Dimension Usage tab join the Configuration Measure Group to a dimension in your cube that meets the following criteria:

  1. The dimension has a member row with a key value of -1. (Data Warehouse designers typically add a -1 key as the “Unknown” member of the dimension table.)
  2. You will NOT be using the dimension in conjunction with the Configuration Values. This sounds rather counter intuitive based on cube design practices, but it is explained below.

Browsing the cube by any dimension OTHER than the one used to join the Configuration Measure Group will return the configuration measure values at every cube intersection. This is because you are actually selecting the [All] member of that one dimension, which includes the SUM of each Configuration Value. And since there is only one row at the [Unknown] member (Key = -1), the SUM at the [All] level is the one row. Browsing the cube INCLUDING the one dimension will show that the configuration values are ONLY available for the “Unknown” member, and not for any others. If your configuration values, whatever they represent, will NEVER be used with the dimension you have them joined to, then this is just fine. But if there is any possibility that the Configuration Measures would be needed for any and every dimension in the cube, then you need to do a little editing of the view. We’ll cover that in Part 3.

The advantage of this method over what was covered in Part 1 is that if the Configuration Values ever need to be changed, it is now simply a matter of changing a single value in a table and reprocessing the Measure Group instead of editing the cube design and redeploying the entire cube. To add additional configurations would involve the following:

  1. Add the entry in the table
  2. Edit the view to include the appropriate [ConfigurationName] in the PIVOT clause
  3. Refresh the Data Source View for the cube project
  4. Add a new measure to the Configuration Measure Group for the newly added column
  5. Deploy and process the cube

In Part 3, we will overcome the limitation of NOT being able to use the Configuration Measures for EVERY dimension.

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