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

Backup and restore


Assuring data availability is the primary responsibility of each database administrator, so collecting and validating SSAS database backups is essential for your job security. You can only collect full database backups—Analysis Services does not support backups at individual cube, measure group, or dimension level, nor does it support incremental or differential backups. Hence, when building SSAS databases, it is imperative to consider which data sets need to be backed up together. For example, if 80 percent of user queries examine current data and only 20 percent check historical data, you could implement two databases—one for historical and the other for recent data. If historical data changes rarely, you may only need to backup the historical database once a month, whereas the database with daily changes should be backed up more frequently. Much like other database platforms, when thinking about your SSAS backup strategy, you should consider how much data loss is acceptable...