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 drillthrough actions


Drillthrough is a very frequently used functionality that allows the examination of detailed level data values. Earlier versions of Analysis Services allowed for executing queries against the relational data source, thereby enabling leaf-level data to remain in the relational format. Unfortunately, this often led to poor performance, which could not be controlled from SSAS. Starting with SSAS 2005, drillthrough only works within the cube space and requires any detailed data to be imported into the MOLAP storage. Clearly the major drawback of this approach is that we might have to build huge dimensions in order to expose data at the transaction level. An alternative approach is to implement an Excel macro to run a query against the relational data source if the user needs to see such data.

How to do it...

Let us define a drillthrough action as follows:

  1. Choose New Drillthrough Action after right-clicking on the SSDT Action Organizer within the Actions tab. Supply...