Book Image

SQL Server Analysis Services 2012 Cube Development Cookbook

Book Image

SQL Server Analysis Services 2012 Cube Development Cookbook

Overview of this book

Microsoft SQL Server is a relational database management system. As a database, it is a software product whose primary function is to store and retrieve data as requested by other software applications. SQL Server Analysis Services adds OLAP and data mining capabilities for SQL Server databases. OLAP (online analytical processing) is a technique for analyzing business data for effective business intelligence. This practical guide teaches you how to build business intelligence solutions using Microsoft’s core product – SQL Server Analysis Services. The book covers the traditional multi-dimensional model which has been around for over a decade as well as the tabular model introduced with SQL Server 2012. Starting with comparing MultiDimensional and tabular models – discussing the values and limitations of each, you will then cover the essential techniques for building dimensions and cubes. Following on from this, you will be introduced to more advanced topics, such as designing partitions and aggregations, implementing security, and synchronizing databases for solutions serving many users. The book also covers administrative material, such as database backups, server configuration options, and monitoring and tuning performance. We also provide a primer on MultiDimensional eXpressions (MDX) as well as Data Analysis expressions (DAX) languages. This book provides you with data cube development techniques, and also the ongoing monitoring and tuning for Analysis Services.
Table of Contents (19 chapters)
SQL Server Analysis Services 2012 Cube Development Cookbook
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Chapter 1. Introduction to Multidimensional Data Model Design

In this chapter we will discuss the differences between Multidimensional databases (cubes) and Tabular Models in order to help you decide which is best for meeting your particular needs. More details on how to implement each of these will be covered in the rest of this cookbook. In this chapter we will explore the following concepts:

  • The business value of Business Intelligence

  • The challenges and barriers faced when implementing Business Intelligence

  • Strategies for overcoming these challenges and barriers

  • Choosing multidimensional or Tabular Models

  • Star- and Snowflake-relational schema

  • A sample scenario for choosing the Snowflake schema