We've already seen how Analysis Services can cache the values returned in the cells of a query, and how this can have a significant impact on the performance of a query. Both the Formula Engine and the Storage Engine can cache data, but may not be able to do so in all circumstances; similarly, although Analysis Services can share the contents of the cache between users there are several situations where it is unable to do so. Given that in most cubes there will be a lot of overlap in the data that users are querying, caching is a very important factor in the overall performance of the cube and as a result ensuring that as much caching as possible is taking place is a good idea.
Expert Cube Development with SSAS Multidimensional Models
Expert Cube Development with SSAS Multidimensional Models
Overview of this book
Table of Contents (19 chapters)
Expert Cube Development with SSAS Multidimensional Models
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Designing the Data Warehouse for Analysis Services
Building Basic Dimensions and Cubes
Designing More Complex Dimensions
Measures and Measure Groups
Handling Transactional-Level Data
Adding Calculations to the Cube
Adding Currency Conversion
Query Performance Tuning
Securing the Cube
Going in Production
Monitoring Cube Performance and Usage
DAX Query Support
Index
Customer Reviews