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

Defining partition slice


As mentioned earlier, Analysis Services can intelligently decide which partitions to check for each query. For example, if we submit a query requesting reseller sales data for year 2005, SSAS should only have to check the Reseller Sales 2005 partition and not spend any time examining datafiles for 2006 or any other partitions. To exclude irrelevant partitions, Analysis Services checks the index files found within each partition folder; these files contain the range of internally assigned key values. You have already seen that we can partition measure groups by date; indeed, the majority of SSAS projects are partitioned by one of the levels found in the date dimension: day, month, quarter, or year. However, sometimes partitioning only at the date level is insufficient—you may have large volumes of intraday data that represents only a small portion of the total daily volume. In such case you can create partitions based on multiple attributes, for example, we could...