MDX Scripting Statements: Introducing the Simple CASE Statement - Page 2
June 4, 2007
Preparation: Access SQL Server Management Studio
To reinforce our understanding of the basics we have covered, we will use the CASE statement within a couple of queries that illustrate its operation, focusing, within this article, upon scenarios where we use the simple CASE statement to meet the business requirements of a hypothetical client. (As we have noted earlier, we examine the searched type of the statement, which returns specific values based upon its evaluation of a set of Boolean expressions, in an independent article dedicated to the details surrounding that type.) We will undertake our practice exercises within scenarios that place the CASE statement within the context of meeting basic requirements similar to those we might encounter in our respective daily environments. The intent is to demonstrate the use of the statement in a straightforward, memorable manner.
We will turn to the SQL Server Management Studio as a platform from which to construct and execute the MDX we examine, and to view the results datasets we obtain. If you do not know how to access the SQL Server Management Studio in preparation for using it to query an Analysis Services cube (we will be using the sample Adventure Works cube in the Adventure Works DW Analysis Services database), please perform the steps of the following procedure, located in the References section of my articles index:
This procedure will take us through opening a new Query pane, upon which we will create our first query within the section that follows.
Procedure: Satisfy Business Requirements with MDX
Lets assume, for purposes of our practice example, that we have received a request for assistance from representatives of our client, the Adventure Works organization. Analysts within the VP - Sales group, with whom we have worked in the past to deliver solutions to meet various reporting and analysis needs, inform us that they have received a request to generate some tag values for a specific analysis task that has been discussed at a recent meeting with Marketing group peers.
The analysts tell us that the values under immediate consideration involve Internet Order Quantities, but, as is typically the case in our collaborative sessions, they want to develop an approach that will work equally well with other measures that have similar analysis potential. (As we have noted in other sessions of our series, our client colleagues often derive parameterized queries in Reporting Services from the basic MDX syntax we assemble together, and can thus create self-serve reports that allow information consumers to dictate what measure they wish to analyze, and myriad other options, at run time.) The desired immediate end is to simply return the Internet Order Quantity recorded for the initial year of operations, Calendar Year 2001, for each Postal Code for a sample State-Province. (They have chosen Washington as a start, but assure us that they realize that the State-Province can be parameterized in the reports they eventually build, based upon the sample logic that we help them to devise.)
Our client colleagues tell us that they wish to classify the Internet Order Quantity for each of the Postal Codes. They will place the activity label in a column to the right of the Internet Order Quantity column of the returned dataset, using the logic found in Table 1.
Table 1: Desired Activity Labels for Quantities Associated with Each Postal Code
As is often the case, this basic need might be met multiple ways with an MDX query. Because the analysts have made known the desire to eventually evolve the query to allow parameterization of the State-Province, as well as Calendar Year and so forth, we want to propose a sample that lends itself to flexible modification later. Once again, the richness of MDX affords us a number of avenues to this objective. While parameterization is itself not a consideration in our current level of query design, we want to make it easy to accomplish within Reporting Services. (The same concepts would, of course, apply with other OLAP reporting tools that afford developer access to the MDX syntax that underlies them).
After we initially explain the use of the CASE statement as a candidate for meeting the requirement, our client colleagues state that they are interested in understanding how they might apply conditional logic via this function, within the context of a practical scenario such as the immediate requirement. The simple CASE statement appears an adequate mechanism for evaluating the Internet Order Quantity measure for each individual Postal Code against several WHEN clauses, and for returning the label result appropriate for the respective Postal Codes value for the year. For Internet Order Quantities that do not match a scalar value specified in any of the When Expressions that is, quantities of ten (10) and above the scalar value of the Else Result Expression (Substantial) will be returned.
We discuss our reasoning with the analyst group, and then offer to illustrate the use of the CASE statement to meet the immediate need, both to solidify the analysts new understanding and to assist in rounding their overall MDX vocabularies. We then set about the assembly of our example to illustrate the use of CASE.