Mastering Enterprise BI: Working with Measure Groups

About the Series …

This
article is a member of the series Introduction to MSSQL Server Analysis Services. The series is designed to provide
hands-on application of the fundamentals of MS SQL Server Analysis Services,
with each installment progressively presenting features and techniques designed
to meet specific real – world needs. For more information on the series,
please see my initial article, Creating Our First
Cube.

• Microsoft SQL
  Server 2005 Database Engine

• Microsoft SQL
  Server 2005 Analysis Services

• Microsoft SQL
  Server 2005 Integration Services

• Business
  Intelligence Development Studio

• Microsoft SQL
  Server 2005 sample databases

• The Analysis Services
  Tutorial sample project and other samples that are available with the
  installation of the above.

To
successfully replicate the steps of the article, you also need to have:

• Membership
  within one of the following:

  • the Administrators
    local group on the Analysis Services computer

  • the Server
    role in the instance of Analysis Services

• Read permissions within any SQL
  Server 2005 sample databases we access within our practice session, as
  appropriate.

About the Mastering Enterprise
BI Articles …

Having implemented, and developed within, most of the major
enterprise BI applications for over fourteen years, and having developed an
appreciation for the marriage of ease of use and analytical power
through my background in Accounting and Finance, I have come to appreciate the
leadership roles Cognos and other vendors have played in the evolution of OLAP
and enterprise reporting. As I have stated repeatedly, however, I have become
convinced that the components of the Microsoft integrated business intelligence
solution (including MSSQL Server, Analysis Services, and Reporting
Services) will commoditize business intelligence. It is therefore easy to
see why a natural area of specialization for me has become the conversion of Cognos
(and other) enterprise business intelligence to the Microsoft solution. In addition to converting formerly
dominant business intelligence systems, such as Cognos, Business Objects / Crystal,
MicroStrategy and others, to the Reporting Services architecture, I
regularly conduct strategy sessions about these conversions with large
organizations in a diverse range of industries – the interest grows daily as
awareness of the solution becomes pervasive. Indeed, the five-to-six-plus
figures that many can shave from their annual IT budgets represent a compelling
sweetener to examining this incredible toolset.

The purpose of the Mastering
Enterprise BI subset of my Introduction to MSSQL Server Analysis
Services series is to focus on techniques for
implementing features in Analysis Services that parallel – or outstrip – those
found in the more "mature" enterprise OLAP packages. In many cases, which I try to
outline in my articles at appropriate junctures, the functionality of the OLAP
solutions within well-established, but expensive, packages, such as Cognos
PowerPlay Transformer and Cognos PowerPlay, can be met – often
exceeded – in most respects by the Analysis Services / Reporting Services
combination – at a tiny fraction of the cost. The vacuum of documentation
comparing components of the Microsoft BI solution to their counterparts among
the dominant enterprise BI vendors, to date, represents a serious "undersell"
of both Analysis Services and Reporting Services, particularly
from an OLAP reporting perspective. I hope to contribute to making this arena
more accessible to everyone, and to share my implementation and conversion
experiences as the series evolves – and, within the context of the Mastering
Enterprise BI articles, to demonstrate that the ease of replicating popular
enterprise BI features in Analysis Services will be yet another reason
that the Microsoft solution will commoditize business intelligence.

For
more information about the Mastering Enterprise BI articles, see
the section entitled "About the
Mastering
Enterprise BI Articles" in my article Relative
Time Periods in an Analysis Services Cube, Part I.

Introduction

The advent of MSSQL
Server Analysis Services 2005 witnessed the introduction of many new
concepts within a dramatically more sophisticated design environment. Measure
Groups represent one of myriad enhancements that we encounter early in
exploring and implementing Analysis Services 2005 for use within
enterprise Business Intelligence environments. A Measure Group not only
holds the measures from a given fact table, but it also houses the aggregations
of those measures for various dimensional hierarchies that we designate.

When we couple a
dimension with a Measure Group, we associate the measures within the
group with the appropriate levels of the hierarchy within that dimension. This
allows us the flexibility of using the same "grain mapping" between
the level and other measures we might wish to add to the same group. The most
obvious advantage that accrues is the capability to maintain different Measure
Groups with different meaningful levels, eliminating confusion and delivering
new levels of design friendliness.

Measure Groups are, therefore, logical
collections of related measures, whose purpose is to make life easier for
solution and application designers. In this article, we will examine Measure
Groups, and get hands-on exposure to the process of adding them to a basic cube
we construct within the new Business Intelligence Development Studio. We
will overview the creation of Measure Groups, and discuss ways in which
they can offer flexibility in cube and solution / application design and
development. As a part of our examination of the steps, we will:

• Prepare Analysis
  Services, and our environment, by creating an Analysis Services Project
  to house our development steps, and to serve as a platform for the design of a
  quick cube model, within which to perform subsequent procedures in our session;

• Create a Data
  Source containing the information Analysis Services needs to connect
  to a database;

• Create a Data
  Source View containing schema information;

• Build a cube
  based upon our Data Source and Data Source View, containing data
  from our sample relational tables;

• Add examples
  of Measure Groups as part of cube design;

• Assign, via
  the Dimensional Usage tab of the Designer, granularity at measure
  / dimension intersects for representative members of the new Measure Groups;

• Deploy our Analysis
  Services Solution;

• Browse the Cube,
  focusing on the new Measure Groups and associated details.