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Posted Aug 16, 2004

Introduction to MSSQL Server 2000 Analysis Services: Derived Measures vs. Calculated Measures

By William Pearson

About the Series ...

This article is a member of the series Introduction to MSSQL Server 2000 Analysis Services. The series is designed to provide hands-on application of the fundamentals of MS SQL Server 2000 Analysis Services, with each installment progressively adding features and techniques designed to meet specific real-world needs. For more information on the series, as well as the hardware / software requirements to prepare for the exercises we will undertake, please see my initial article, Creating Our First Cube.

Note: Service Pack 3 / 3a updates are assumed for MSSQL Server 2000, MSSQL Server 2000 Analysis Services, and the related Books Online and Samples. Images are from a Windows 2003 Server environment, upon which I have also implemented MS Office 2003, but the steps performed in the articles, together with the views that result, will be quite similar within any environment that supports MSSQL Server 2000 and MSSQL Server 2000 Analysis Services ("Analysis Services" or "MSAS"). The same is generally true, except where differences are specifically noted, when MS Office 2000 and above are used in the environment, in cases where MS Office components are presented in the article.


In dealing with MSAS implementations on a daily basis, and especially when being called upon to tune MSAS implementations performed by others, I come across the less-than-optimal use of calculated members quite often. As most of us know, calculated members are dimensions or measures (depending upon the designated parent dimension) that are constructed, using a formula, from other dimensions or measures in our cubes. A typical example of a calculated member that is designed for a measure, to which we will refer in this article as a calculated measure, is a Profit calculated measure that is created by subtracting a cost / expense measure from a sales / revenue measure. Another common calculated measure is a variance measure, which is created by taking a difference between an actual and a budgeted value (or similar kinds of values), among other approaches.

If the calculation / formula that we use in creating the calculated measure consists of a simple match between two measures, we can often use a derived measure instead. In this article, we will discuss the advantages and disadvantages involved, and compare and contrast the methods of adding these sorts of measures to our cubes. In examining the use of derived measures to enhance cube response times, we will:

  • Discuss the drawbacks in using calculated members in cases where a derived measure might be substituted;
  • Discuss benefits and disadvantages that might accrue through the use of derived measures;
  • Describe an illustrative scenario, upon which we will determine that a derived measure can offer a tuning solution for a group of hypothetical information consumers;
  • Implement a simple solution through creation of a derived measure to replace an existing calculated measure;
  • Explain the results we obtain from the steps we take to accomplish the solution.

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