Book Image

Expert Cube Development with Microsoft SQL Server 2008 Analysis Services

Book Image

Expert Cube Development with Microsoft SQL Server 2008 Analysis Services

Overview of this book

Microsoft's SQL Server Analysis Services 2008 is an OLAP server that allows users to analyze business data quickly and easily. However, designing cubes in Analysis Services can be a complex task: it's all too easy to make mistakes early on in development that lead to serious problems when the cube is in production. Learning the best practices for cube design before you start your project will help you avoid these problems and ensure that your project is a success. This book offers practical advice on how to go about designing and building fast, scalable, and maintainable cubes that will meet your users' requirements and help make your Business Intelligence project a success. This book gives readers insight into the best practices for designing and building Microsoft Analysis Services 2008 cubes. It also provides details about server architecture, performance tuning, security, and administration of an Analysis Services solution. In this book, you will learn how to design and implement Analysis Services cubes. Starting from designing a data mart for Analysis Services, through the creation of dimensions and measure groups, to putting the cube into production, we'll explore the whole of the development lifecycle. This book is an invaluable guide for anyone who is planning to use Microsoft Analysis Services 2008 in a Business Intelligence project.

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Expert Cube Development with Microsoft SQL Server 2008 Analysis Services
Jul, 2009 | 360 pages
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Table of Contents (17 chapters)
Expert Cube Development with Microsoft SQL Server 2008 Analysis Services
Expert Cube Development with Microsoft SQL Server 2008 Analysis Services
Credits
Credits
About the Authors
About the Authors
About the Reviewers
About the Reviewers
Preface
Preface
Free Chapter
1
Designing the Data Warehouse for Analysis Services
Designing the Data Warehouse for Analysis Services
The source database
Data modeling for Analysis Services
Physical database design for Analysis Services
Summary
2
Building Basic Dimensions and Cubes
Building Basic Dimensions and Cubes
Choosing an edition of Analysis Services
Setting up a new Analysis Services project
Creating data sources
Creating Data Source Views
Designing simple dimensions
Building a Simple Cube
Summary
3
Designing More Complex Dimensions
Designing More Complex Dimensions
Grouping and Banding
Slowly Changing Dimensions
Junk dimensions
Ragged hierarchies
Summary
4
Measures and Measure Groups
Measures and Measure Groups
Measures and aggregation
Measure groups
Dimension/measure group relationships
Summary
5
Adding Transactional Data such as Invoice Line and Sales Reason
Adding Transactional Data such as Invoice Line and Sales Reason
Details about transactional data
Drillthrough
Many-to-many dimension relationships
Summary
6
Adding Calculations to the Cube
Adding Calculations to the Cube
Different kinds of calculated members
Common calculations
Calculation dimensions
Named sets
Summary
7
Adding Currency Conversion
Adding Currency Conversion
Introduction to currency conversion
Where to perform currency conversion
The Add Business Intelligence Wizard
Measure expressions
Summary
8
Query Performance Tuning
Query Performance Tuning
How Analysis Services processes queries
Performance tuning methodology
Designing for performance
Performance-specific design features
MDX calculation performance
Caching
Scale-up and scale-out
Summary
9
Securing the Cube
Securing the Cube
Sample security requirements
Analysis Services security features
Administrative security
Data security
Dynamic cell security
Accessing Analysis Services from outside a domain
Managing security
Security and query performance
Summary
10
Productionization
Productionization
Making changes to a cube in production
Managing partitions
Managing processing
Analysis Services data directory maintenance
Backup
Copying databases between servers
Summary
11
Monitoring Cube Performance and Usage
Monitoring Cube Performance and Usage
Analysis Services and the operating system
Monitoring processing performance
Monitoring query performance
Monitoring usage
How to build a complete monitoring solution
Summary
Index
Index

Dynamic cell security

We can implement dynamic security for cell security in much the same way as we have seen with dimension security. In this section we'll use the same bridge table we used in the previous sections to model the relationship between users and resellers they have access to; our requirements will be as follows:

  • Members of the role will have complete access to all measures, except for Gross Profit

  • For Gross Profit, users will only have access to values for it for resellers they have been granted access to based on the data in our bridge table

  • We also need to hide the All member of the Reseller dimension to ensure that users cannot derive values for cells they don't have access to.

We can use this expression to control Read access in the Cell Data tab:

NOT (
    Measures.CurrentMember IS Measures.[Gross Profit] 
    AND (
        StrToMember ("[Users].[User].[" + UserName() + "]"),
        Measures.[Bridge Reseller Users Count]) = 0
        OR 
        Reseller.Reseller.CurrentMember...
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