# Set Functions: The StripCalculatedMembers() Function

### About the Series …

This article is a member of the series, MDX Essentials.
The series is designed to provide hands-on application of the fundamentals of
the Multidimensional Expressions (MDX) language, with each tutorial
progressively adding features designed to meet specific real-world needs.

For more information about the series in general, as well as
the software and systems requirements for getting the most out of the lessons
included, please see my first article, MDX at First Glance: Introduction to MDX Essentials.

Note: Current updates are assumed for MSSQL
Server
, MSSQL Server Analysis Services, and the related Books
Online
and Samples.

### Overview

In
this lesson, we will introduce StripCalculatedMembers(), a basic set function
which is often “just what the doctor ordered” in the context of the specific
need. The general purpose of StripCalculatedMembers() is to retrieve the
members of a specified set, after removing any calculated
members
.

StripCalculatedMembers()
can be leveraged
in a wide range of activities, from the support of simple list generation, to the
support of sophisticated conditional and other calculations and presentations.
We will introduce the function, commenting upon its operation and touching upon
creative effects that we can employ it to deliver. As a part of our
discussion, we will:

• Examine the syntax surrounding the function;
• Undertake illustrative examples of the uses of the function in
practice exercises;
• Briefly discuss the results datasets we obtain in the practice
examples.

### The StripCalculatedMembers() Function

#### Introduction

According to the Analysis Services Books Online, the StripCalculatedMembers()
function “returns a set generated by removing calculated members from a
specified set.” StripCalculatedMembers() has numerous applications. For
example, the function can be leveraged within queries to create datasets, in
reporting applications such as MSSQL Server Reporting Services, for the
support of picklists within the reports, for the support of axes within various
end presentations, and so forth. The StripCalculatedMembers() function
provides an intuitive option anytime we need to present, in a returned dataset,
all members –minus calculated members – that belong to a specified
set
.

As we have noted to have been the case
with many individual MDX functions we have examined within this series,
combining StripCalculatedMembers()
with other functions allows us to further extend its power. We will get a taste
of this synergy in the practice exercises that follow.

We will examine the syntax for the StripCalculatedMembers()
function after a brief discussion in the next section. We will then explore,
from the straightforward context of MDX queries, and within practice examples
constructed to support hypothetical business needs, some of the capabilities it
offers the knowledgeable user. This will allow us to activate what we explore
in the Discussion and Syntax sections, and afford
us some hands-on exposure in creating expressions that employ the StripCalculatedMembers()
function.

#### Discussion

To restate our initial explanation of its
operation, the StripCalculatedMembers() function examines a set expression that we specify
and returns the members that remain after it removes all calculated
members
. StripCalculatedMembers()
can be used for a great deal more
than simple list retrieval, as we have intimated. When coupled with other
functions or used within MDX scripts, among other applications, we can leverage
StripCalculatedMembers() to support a wide range of analysis and
reporting utility.

Let’s discuss syntax to further clarify the operation of StripCalculatedMembers().

#### Syntax

Syntactically, in using the StripCalculatedMembers()
function to return a set of members (minus calculated members), the
set expression upon which we seek to apply the function is specified within
the parentheses to the right of the StripCalculatedMembers keyword. The
function removes calculated members from the set expression (a
valid MDX expression that returns a set) enclosed within the parentheses,
and returns a set representing only the base members contained
within the scope of the set expression. As we shall see, StripCalculatedMembers()
removes all calculated members from a set, including those
added within the query itself (via the WITH MEMBER keywords). StripCalculatedMembers()
also removes all calculated members added to a specified set
using either of the AddCalculatedMembers() or .AllMembers functions,
both of which return calculated members defined on the Analysis
Server
.

NOTE:
For more detail surrounding the AddCalculatedMembers() function, see Set
Functions: The AddCalculatedMembers() Function
, and for information about
the .AllMembers function, see Set
Functions: The .AllMembers Function
. Both articles are members of my MDX
Essentials
series at Database
Journal
.

For a general introduction to
calculated
members
,
together with a discussion of further considerations and perspectives involved
in working with calculated members, see Calculated
Members: Introduction
and Calculated
Members: Further Considerations and Perspectives
, respectively, both of which
are members of my MDX in
Analysis Services
series at Database
Journal
.

The general syntax for the
application of StripCalculatedMembers() appears in the following string:

`  StripCalculatedMembers( <<Set_Expression>> )`

Putting StripCalculatedMembers() to work is
straightforward. When using the function to return the members, minus
any calculated members, contained within a set expression, we
simply supply the required set expression within the parentheses
to the right of the StripCalculatedMembers keyword.

As an example, say we specify, within a query executed
against the sample Adventure Works cube, a column axis containing all
members of the Product Categories level of the Product dimension
(specified as {[Product].[Product Categories].[Category].MEMBERS}), with
a row axis such as the following:

`  STRIPCALCULATEDMEMBERS( {[Measures].ALLMEMBERS} )`

Moreover,
say that we add a WHERE clause to filter the retrieved data set to Calendar
Year 2004
. Depending upon the calculated members we have defined
within our cube (we might have added calculated members beyond those that
appear in the pristine sample cube), we would expect to retrieve results
similar to those depicted in Illustration 1.

Illustration 1: Example Returned Data: StripCalculatedMembers()
Function Employed in Query

We can see, within the dataset
returned above, that only base members / measures appear. (If we remove
the StripCalculatedMembers() from around the rest of the row axis
specification, we will see that a greater number of measures (both base
and calculated) now appear, and that the column axis increases
dramatically (from 30 measures, in my local cube, to 50-plus measures).

Because of the relative ease
with which we can employ StripCalculatedMembers(), and because of the
flexibility with which we can exploit it to meet various business needs
(particularly those meeting metadata requirements), the function can become a
popular member of our analysis and reporting toolsets. It is easy, for
example, when considering the above scenario, to see that we might simply
parameterize “on / off” behavior for the StripCalculatedMembers() function
within a client application, such as Reporting Services, to allow
information consumers to choose either “include” or “exclude” behavior with
regard to calculated members within axes or picklists at report run
time.

We will get some hands-on
exposure to the StripCalculatedMembers() function in the section that
follows.

William Pearson
Bill has been working with computers since before becoming a "big eight" CPA, after which he carried his growing information systems knowledge into management accounting, internal auditing, and various capacities of controllership. Bill entered the world of databases and financial systems when he became a consultant for CODA-Financials, a U.K. - based software company that hired only CPA's as application consultants to implement and maintain its integrated financial database - one of the most conceptually powerful, even in his current assessment, to have emerged. At CODA Bill deployed financial databases and business intelligence systems for many global clients. Working with SQL Server, Oracle, Sybase and Informix, and focusing on MSSQL Server, Bill created Island Technologies Inc. in 1997, and has developed a large and diverse customer base over the years since. Bill's background as a CPA, Internal Auditor and Management Accountant enable him to provide value to clients as a liaison between Accounting / Finance and Information Services. Moreover, as a Certified Information Technology Professional (CITP) - a Certified Public Accountant recognized for his or her unique ability to provide business insight by leveraging knowledge of information relationships and supporting technologies - Bill offers his clients the CPA's perspective and ability to understand the complicated business implications and risks associated with technology. From this perspective, he helps them to effectively manage information while ensuring the data's reliability, security, accessibility and relevance. Bill has implemented enterprise business intelligence systems over the years for many Fortune 500 companies, focusing his practice (since the advent of MSSQL Server 2000) upon the integrated Microsoft business intelligence solution. He leverages his years of experience with other enterprise OLAP and reporting applications (Cognos, Business Objects, Crystal, and others) in regular conversions of these once-dominant applications to the Microsoft BI stack. Bill believes it is easier to teach technical skills to people with non-technical training than vice-versa, and he constantly seeks ways to graft new technology into the Accounting and Finance arenas. Bill was awarded Microsoft SQL Server MVP in 2009. Hobbies include advanced literature studies and occasional lectures, with recent concentration upon the works of William Faulkner, Henry James, Marcel Proust, James Joyce, Honoré de Balzac, and Charles Dickens. Other long-time interests have included the exploration of generative music sourced from database architecture.