Book Image

Getting Started with SQL Server 2012 Cube Development

Book Image

Getting Started with SQL Server 2012 Cube Development

Overview of this book

Analysis Services have been the number one OLAP engine for years. With the increased focus on business intelligence solutions, there is a shortage of professionals in this area. Start your journey into becoming a BI developer using the popular tools included in every SQL Server installation. Getting Started with SQL Server 2012 Cube Development teaches you through clear step-by-step exercises to create business intelligence solutions using Analysis Services. The knowledge gained through these practical examples can immediately be applied to your real-world problems. Getting Started with SQL Server 2012 Cube Development begins with an introduction to business intelligence and Analysis Services, the world's most-used cube engine. Guiding you through easy-to-understand examples to become a cube developer. Learn how to create a cube including all the advanced features such as KPIs, calculated measures, and time intelligence. Security and performance tuning will also be explored. You will learn how to perform and automate core tasks like deployment and processing. The main focus is on multidimensional cubes, but the creation of in-memory models will also be covered. You will learn everything you need to get started with cube development using SQL Server 2012.
Table of Contents (17 chapters)
Getting Started with SQL Server 2012 Cube Development
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Understanding cube aggregations


Analysis Services uses a multidimensional space that consists of cells containing the data.

Since the data in Analysis Services is stored on the physical disk, running a query that affects cells on the lowest level can be slow. If you consider the cube in the previous picture, running a SELECT statement that aggregates the Internet Sales amount would access all the cells in the cube. However, you can pre-aggregate the data on frequently used levels of the different attributes. In the previous picture, aggregating on the Bikes level and or on the Year level can—together with relevant hierarchies—improve performance considerably.

In the FirstCube project that is built on the AdventureWorksDW2012 database, you can take the DimDate dimension as an example. The lowest level of the date dimension is on the day level. The date dimension then contains the month, quarter, and year attributes and a hierarchy defining their relationship.

The month level of the DimDate dimension...