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  • Book Overview & Buying Expert Cube Development with SSAS Multidimensional Models
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Expert Cube Development with SSAS Multidimensional Models

Expert Cube Development with SSAS Multidimensional Models

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Expert Cube Development with SSAS Multidimensional Models

Expert Cube Development with SSAS Multidimensional Models

4.5 (19)
Buy this Book

Overview of this book

An easy-to-follow guide full of hands on examples of real-world Analysis Services cube development tasks. Each topic is explained and placed in context, and for the more inquisitive reader, there also more in-depth details of the concepts used. If you are an Analysis Services cube designer wishing to learn more advanced topic and best practices for cube design, this book is for you.You are expected to have some prior experience with Analysis Services cube development.
Table of Contents (19 chapters)
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Expert Cube Development with SSAS Multidimensional Models
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Expert Cube Development with SSAS Multidimensional Models
Credits
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Credits
About the Authors
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About the Authors
About the Reviewers
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About the Reviewers
www.PacktPub.com
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www.PacktPub.com
Preface
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Preface
Lock Free Chapter
1
Designing the Data Warehouse for Analysis Services
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Designing the Data Warehouse for Analysis Services
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The source database
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Data modeling for Analysis Services
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Physical database design for Analysis Services
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Summary
2
Building Basic Dimensions and Cubes
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Building Basic Dimensions and Cubes
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Multidimensional and Tabular models
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Choosing an edition of Analysis Services
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Setting up a new Analysis Services project
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Creating data sources
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Creating Data Source Views
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Designing simple dimensions
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Building a simple cube
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Summary
3
Designing More Complex Dimensions
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Designing More Complex Dimensions
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Grouping and banding
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Modeling Slowly Changing Dimensions
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Modeling junk dimensions
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Modeling ragged hierarchies
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Summary
4
Measures and Measure Groups
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Measures and Measure Groups
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Measures and aggregation
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Measure groups
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Dimension/measure group relationships
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Summary
5
Handling Transactional-Level Data
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Handling Transactional-Level Data
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Details about transactional data
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Drillthrough
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Many-to-many dimension relationships
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Summary
6
Adding Calculations to the Cube
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Adding Calculations to the Cube
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Different kinds of calculated members
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Common calculations
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Calculation dimensions
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Named sets
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Summary
7
Adding Currency Conversion
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Adding Currency Conversion
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Introduction to currency conversion
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Where to perform currency conversion
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The Add Business Intelligence wizard
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Measure expressions
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Summary
8
Query Performance Tuning
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Query Performance Tuning
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Understanding how Analysis Services processes queries
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Performance tuning methodology
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Designing for performance
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Performance-specific design features
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MDX calculation performance
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Caching
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Scale-up and Scale-out
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Summary
9
Securing the Cube
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Securing the Cube
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Sample security requirements
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Analysis Services security features
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Administrative security
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Data security
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Dynamic cell security
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Accessing Analysis Services from outside a domain
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Managing security
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Security and query performance
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Summary
10
Going in Production
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Going in Production
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Making changes to a cube in production
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Managing partitions
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Managing processing
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SSAS Data Directory maintenance
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Performing database backup
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Copying databases between servers
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Summary
11
Monitoring Cube Performance and Usage
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Monitoring Cube Performance and Usage
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Analysis Services and the operating system
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Monitoring processing performance
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Monitoring query performance
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Monitoring usage
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Building a complete monitoring solution
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Summary
1
DAX Query Support
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DAX Query Support
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Implementation details
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Connecting Power View to a Multidimensional model
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Running DAX queries against a Multidimensional model
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Index
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Index

Summary

In this chapter we've learned how to optimize the performance of our cube so our users' queries execute as quickly as possible. We've looked at how Analysis Services processes queries and what the roles of the Storage Engine and the Formula Engine have in this; we've seen how building partitions and aggregations can improve the performance of the Storage Engine, and we've also seen how to write MDX to ensure that the Formula Engine works as efficiently as possible. Last of all, we've seen how important caching is to overall query performance and what we need to do to ensure that we can cache data as often as possible, and we've discussed how to scale-out Analysis Services using network load balancing to handle large numbers of concurrent users. In the next chapter, we'll take a look at how to apply security to the data in a cube.

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Programming languages
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