MDX in Analysis Services: Calculated Members: Further Considerations and Perspectives

October 27, 2003

About the Series ...

This is the eighth tutorial article of the series, MDX in Analysis Services. The series is designed to provide hands-on application of the fundamentals of MDX from the perspective of MS SQL Server 2000 Analysis Services ("Analysis Services,"); our primary focus is the manipulation of multidimensional data sources, using MDX expressions in a variety of scenarios designed to meet real-world business intelligence needs.

For more information on the series, as well as the hardware / software requirements to prepare for the tutorials we will undertake, please see the first lesson of this series: MDX Concepts and Navigation.

Note: At the time of writing, Service Pack 3 updates are assumed for MSSQL Server 2000, MSSQL Server 2000 Analysis Services, and the related Books Online and Samples.

Introduction

In our last tutorial, Calculated Members: Introduction, we saw through practice that we can easily create and display calculated members within our queries to meet various business needs. We discussed the two main ways of handling the creation of calculated members within MDX, focusing on the use of the WITH operator to create a dynamic calculated member in an MDX query. Then, we practiced the creation of a straightforward calculated member, deriving a useful value from existing measures, and formatting the new calculated measure to meet an illustrated objective.

Our introduction to dynamic calculated members set the stage for the more advanced functionality and processes of calculated members that we will begin to explore in this and following lessons. We will reinforce our knowledge of calculated members, and then broaden our understanding through an examination of multiple additional perspectives of these highly useful components in our MDX toolset. In addition, we will explore a means for controlling the order in which calculated members are solved, discussing why precedence of calculation might be critical to generating the results we expect.








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