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Expert Cube Development with SSAS Multidimensional Models

You're reading from  Expert Cube Development with SSAS Multidimensional Models

Product type Book
Published in Feb 2014
Publisher Packt
ISBN-13 9781849689908
Pages 402 pages
Edition 1st Edition
Languages

Table of Contents (19) Chapters

Expert Cube Development with SSAS Multidimensional Models
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Designing the Data Warehouse for Analysis Services 2. Building Basic Dimensions and Cubes 3. Designing More Complex Dimensions 4. Measures and Measure Groups 5. Handling Transactional-Level Data 6. Adding Calculations to the Cube 7. Adding Currency Conversion 8. Query Performance Tuning 9. Securing the Cube 10. Going in Production 11. Monitoring Cube Performance and Usage DAX Query Support Index

Scale-up and Scale-out


Buying better or more hardware, that is to say "scaling up", should be your last resort when trying to solve query performance problems. It's expensive and you need to be completely sure that it will indeed improve matters. Adding more memory will increase the space available for caching but nothing else; adding more or faster CPUs will lead to faster queries but you might be better off investing time in building more aggregations or tuning your MDX. Scaling up as much as your hardware budget allows is a good idea but may have little impact on the performance of individual problem queries unless you badly under-specified your Analysis Services server in the first place.

If your query performance degenerates as the number of concurrent users running queries increases, consider scaling-out by implementing what's known as an OLAP farm. This architecture is widely used in large implementations and involves multiple Analysis Services instances on different servers, and using...

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