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Expert Cube Development with Microsoft SQL Server 2008 Analysis Services

You're reading from   Expert Cube Development with Microsoft SQL Server 2008 Analysis Services Design and implement fast, scalable and maintainable cubes with Microsoft SQL Server 2008 Analysis Services with this book and eBook

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Product type Paperback
Published in Jul 2009
Publisher Packt
ISBN-13 9781847197221
Length 360 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (17) Chapters Close

Expert Cube Development with Microsoft SQL Server 2008 Analysis Services
Credits
About the Authors
About the Reviewers
Preface
1. Designing the Data Warehouse for Analysis Services FREE CHAPTER 2. Building Basic Dimensions and Cubes 3. Designing More Complex Dimensions 4. Measures and Measure Groups 5. Adding Transactional Data such as Invoice Line and Sales Reason 6. Adding Calculations to the Cube 7. Adding Currency Conversion 8. Query Performance Tuning 9. Securing the Cube 10. Productionization 11. Monitoring Cube Performance and Usage Index

Details about transactional data


The goal of a multidimensional cube is to analyze aggregated data across several dimensions. However, when there is some interesting data, the user might be interested in drilling down to a lower level of detail. For example, when it comes to sales analysis, it could be interesting to look at the individual invoices that caused a particular high volume of sales in a single month. This is a very common request for end users to make – in fact, the question is not if the users will need this, but when.

One approach to solve this issue is to add a regular dimension to the cube which has the same granularity as the fact table – as we saw in Chapter 2, this is referred to as a Fact dimension. Using columns on the fact table like invoice number, invoice line number, notes and so on, we can link each fact sale with a dimension member, calling the dimension itself something like "Document". At this point, the end users will have a dimension that can be used with other...

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