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

Implementing dynamic dimension security


In the previous section, you learned how to restrict a role's access to certain dimension hierarchy members. This worked well for a dimension with few categories and a single role. As long as you can group users into a few roles depending on their job function, this approach will suffice. However, when the number of roles grows to hundreds, you'll find that managing security can become very cumbersome and tedious. Clearly, creating a new role to expose a specific data set to each retail customer is unacceptable. Fortunately, you can work around this limitation using a security measure group.

Although it takes several steps to implement, the security measure group utilizes relatively straightforward concepts. You need to identify the attribute to secure, perhaps the sales territory that each cube user should be able to browse. Next, you create a measure group defining the mapping between the user and sales territory. The security role will then use the...