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.
Note: To follow along with the steps we undertake, the following components, samples and tools are recommended, and should be installed according to the respective documentation that accompanies MSSQL Server 2005:
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.
Note: Current Service Pack updates are assumed for the operating system, MSSQL Server 2005 ("MSSQL Server"), MSSQL Server 2005 Analysis Services ("Analysis Services"), MSSQL Server 2005 Reporting Services ("Reporting Services") and the related Books Online and Samples. Images are from a Windows 2003 Server environment, but the steps performed in the articles, together with the views that result, will be quite similar within any environment that supports MSSQL Server 2005 and its component applications.
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.
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.