MDX in Analysis Services: Calculated Members: Introduction

About the Series …

This is the seventh 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
are assumed for MSSQL Server 2000, MSSQL Server 2000 Analysis
, and the related Books Online and Samples.


In our
last tutorial, Using
Sets in MDX Queries
, we began
an exploration of MDX queries. We discussed the MDX expressions
and MDX query statements, and as part of this overview, discussed
key MDX concepts and terminology. We followed our overview with an
exploration of MDX query building from the ground up, using the MDX
Sample Application as a vehicle for crafting our statements and practicing
their use. We then delved
into set functions, and the creation and use of sets, discussing
their importance in our MDX queries. We built the specification of members, and
the combination of multiple dimensions, into our row and column axes, to practice
the addition of truly multidimensional capabilities into the reports we produce
for ourselves, and for the information consumers whom we support.

Through this lesson, we
will introduce calculated members as a starting point for a group of articles to
come, where we will
focus on building and using calculated members within our queries to meet
various business needs. We will begin by previewing the creation of calculated
members to set the stage for the functionality and processes we will explore
together. We will discuss the two main ways of handling the creation
of calculated members within MDX, focusing on the use of the WITH operator to
specify a calculated member in an MDX query. Finally, we will practice the
creation of a calculated member in the article, building our expertise for more
advanced subsequent articles.

Calculated Members

Our knowledge of sets from
the previous lesson, Using Sets in MDX Queries has prepared us to create our first, simple
calculated member. To this end, we will build a quick "starter"
example to introduce fundamentals that will take us further into our
exploration of MDX queries. We shall return to calculated members many times
throughout the series, often using them to frame the delivery of concepts and
processes. We shall also incorporate, as we progress through the series,
aggregation and other functions into our calculated members, along with an
array of other uses, but, for now, let’s see what we can accomplish based upon
what we have already learned, coupled with a taste of things to come.

We will start with the
query with which we left off in our last lesson, first typing it into the
Sample Application from scratch, so that we can begin this lesson completely
independently. We will begin by taking the following steps:

Go to the Start
button on the PC, and then navigate to Microsoft SQL Server –-> Analysis Services, then to the MDX Sample

We are
initially greeted by the Connect dialog, shown in Illustration 1.

Illustration 1: The
Connect Dialog for the MDX Sample Application

above depicts
the name of my server, MOTHER, and properly indicates that we will be
connecting via the MSOLAP provider (the default).

Click OK.

Sample Application
window appears.

Clear the top
area (the Query pane) of any remnants of queries that might appear.

Ensure that FoodMart
is selected as the database name in the DB box of the toolbar.

Select the Warehouse
cube in the Cube drop-down list box.

Sample Application
window should resemble that shown in Illustration 2,
complete with the information from the Warehouse cube displaying in the Metadata
(left section of the Metadata pane).

Illustration 2: The MDX
Sample Application Window (Compressed)

Type the
following query into the Query pane:

{[Measures].[Warehouse Cost] , [Measures].[Warehouse Sales], [Measures].[Units Shipped]}
NonEmptyCrossJoin([Store].[Store State].Members, [Product].[Product Family].Members) ON ROWS
FROM Warehouse

This is the last query that we constructed and ran in the
previous article in the series, Using
Sets in MDX Queries
For more background on the query itself, or for more explanation of the
concepts that we sought to illustrate through its use, please see the article.

Click the Run
button on the toolbar to execute the query.

results dataset appears as shown in Illustration 3:

Illustration 3: Results
Dataset from Our First Query

will make a change to the query to
give it more flexibility in illustrating our current focus topic.

Change the
query from the following (area to change is annotated in a blue):

{[Measures].[Warehouse Cost] , [Measures].[Warehouse Sales], [Measures].[Units Shipped]}
NonEmptyCrossJoin([Store].[Store State].Members, [Product].[Product Family].Members) ON ROWS
FROM Warehouse

to the following:

[Measures].Members ON COLUMNS,
NonEmptyCrossJoin([Store].[Store State].Members, [Product].[Product Family].Members) ON ROWS
FROM Warehouse

essence, we are only changing the query to retrieve all measures
as columns, instead of only the three measures we specified

Type the
following into the Query pane, above the SELECT keyword:

	-- MXAS07:  Tutorial Query No. 1

is a "comment line." A comment line can actually consist of
anything that is appropriate and useful to the designer / creator, and perhaps
subsequent users, of the query. The double dashes ("–") functionally isolate, or "comment
out," the text, so that it does not affect the operation of the query, but
allows us to make notes that might be of use. Our present comment is simply
used to identify the query. We might, alternatively, have left information
here that would be of use to those who inherit or further evolve our work, such
as our reasoning in the design and operation of the query, the author’s name
and location, etc. Moreover, there are additional considerations for the use
of comment lines that we will broach at a later time. The present example of
its use will serve as a means of identification for queries and expressions – a
practice which we will use going forward in the series.

Save the query
as MXAS07-1.MDX, in an appropriate location, keeping it open.

Click the Run

results dataset appears as depicted in Illustration 4:

Illustration 4: Results
Dataset after Modifications

William Pearson
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.

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