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

Managing processing


During development we can process cubes or dimensions whenever we want; in a production environment processing needs more thought though. On a very simple project we might be able to get away with doing a full process on our entire Analysis Services database if it only takes a few minutes to complete. However, we usually have large data volumes to manage and a limited amount of time to perform any processing, so a full process simply isn't feasible—we need to think carefully how we can only process the data that needs to be processed, and do that processing in the most efficient way possible.

Analysis Services processing can be broken down into two different tasks:

  • Dimension Processing involves loading data into a dimension and building indexes on it.

  • Partition Processing is more complex. Before we can query a cube, all of the dimensions in the cube need to be processed and we need to process the cube itself too. A cube is made up of measure groups and a measure group...