Book Image

Expert Cube Development with Microsoft SQL Server 2008 Analysis Services

Book Image

Expert Cube Development with Microsoft SQL Server 2008 Analysis Services

Overview of this book

Microsoft's SQL Server Analysis Services 2008 is an OLAP server that allows users to analyze business data quickly and easily. However, designing cubes in Analysis Services can be a complex task: it's all too easy to make mistakes early on in development that lead to serious problems when the cube is in production. Learning the best practices for cube design before you start your project will help you avoid these problems and ensure that your project is a success. This book offers practical advice on how to go about designing and building fast, scalable, and maintainable cubes that will meet your users' requirements and help make your Business Intelligence project a success. This book gives readers insight into the best practices for designing and building Microsoft Analysis Services 2008 cubes. It also provides details about server architecture, performance tuning, security, and administration of an Analysis Services solution. In this book, you will learn how to design and implement Analysis Services cubes. Starting from designing a data mart for Analysis Services, through the creation of dimensions and measure groups, to putting the cube into production, we'll explore the whole of the development lifecycle. This book is an invaluable guide for anyone who is planning to use Microsoft Analysis Services 2008 in a Business Intelligence project.
Table of Contents (17 chapters)
Expert Cube Development with Microsoft SQL Server 2008 Analysis Services
Credits
About the Authors
About the Reviewers
Preface
Index

Summary


With processing complete, you can take a look at your cube for the first time, either in the Browser tab of the Cube Editor or in your client tool of choice. Now is a good time to reflect on what we've seen of the cube development process so far:

  • We've created a very basic cube from a single fact table and a few dimensions rather than attempting to build something more complex. This has allowed us to get a feel for our data and have something to show our users quickly so that they can check if we're on the right track.

  • We built a single Data Source and Data Source View. Since we spent time getting our data modeling right earlier, there is very little to do here other than connect to our data warehouse and select the tables or views we want to work with.

  • We built a few of the less complex dimensions we need, configuring attribute relationships and creating user hierarchies as necessary.

  • We ran the 'New Cube' wizard to build our basic cube, then deployed and processed it so that it can...