Introduction to SQL Server 2000 Analysis Services: Working with Dimensions


About the Series

This is the second article of the series, Introduction to MS SQL Server 2000 Analysis Services. As I stated in the first article, Creating Our First Cube, the primary focus of this series will be an introduction to the practical creation and manipulation of multidimensional OLAP cubes. The series is designed to provide hands-on application of the fundamentals of MS SQL Server 2000 Analysis Services (“Analysis Services”), with each installment progressively adding features 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.

Introduction

In the first article of the series, we used the Cube Wizard to build our first cube with the assistance of the Dimension Wizard. While the Dimension Wizard is a helpful tool for rapid cube design, we often come across scenarios where we have to take more direct control of the dimension design process. We accomplish this through the use of the Dimension Editor, which exposes numerous properties of a dimension that are not accessible to us through the use of the Dimension Wizard.

Using Analysis Services, we can create our basic dimensions through the use of the wizard, or we can use the manual Dimension and Cube Editors to build our dimensions — and indeed, our entire cube structure, from scratch. (I often do a rapid design of an overall cube “skeleton”- a “draft setup,” as it were, using the Wizards – which I then return to “fine tune” with the respective Editors. Using the Dimension Editor allows us to generate much more sophisticated cubes overall and to produce OLAP data sources that help us analyze more precisely the attributes of our business that we deem to be important.

In this article we will create dimensions similar to those with which we worked before, using the Dimension Editor to illustrate options for building a more customized cube. As we will see in the steps we undertake together, once we have created our dimensions, we can set and modify various properties for optimization and other purposes.

We will begin our exploration of dimensions by creating a database similar to the one we created in Lesson One, Creating Our First Cube. Database creation is ordinarily the first step in creating a cube. We will then work with two of the three main windows of Analysis Manager, the Main Console and the Dimension Editor (the Cube Editor, being the third of the main windows, does not play a significant role in this lesson), to recreate the dimensions we created via the Wizards in our first lesson. Our example will continue with the next two lessons, Handling Time Dimensions and Parent-Child Dimensions, leading to the fifth lesson, Working with the Cube Editor. In Lesson Five we will pull together the components constructed in Lessons Two through Four, to assemble a cube similar to, but more sophisticated than, the cube we generated in the first lesson.

In this article, we will:

  • Create a new OLAP database;
  • Become familiar with the Dimension Editor by creating a single-table dimension;
  • Learn to use the Dimension Editor to manipulate dimensions, and the hierarchical levels that exist within dimensions;
  • Create Multi-table Dimensions;
  • Manipulate dimension and member properties, and discuss design and development characteristics for each.

Page 2: Setting up the Database and Data Source

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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