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

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• Expert Cube Development with Microsoft SQL Server 2008 Analysis Services
  • Table of Contents
  • Expert Cube Development with Microsoft SQL Server 2008 Analysis Services
  • Credits
  • About the Authors
  • About the Reviewers
  • Preface
    • What this book covers
    • What you need for this book
    • Who this book is for
    • Conventions
    • Reader feedback
    • Customer support
      • Downloading the example code and database for the book
      • Errata
      • Piracy
      • Questions
  • 1. Designing the Data Warehouse for Analysis Services
    • The source database
      • The OLTP database
      • The data warehouse
      • The data mart
    • Data modeling for Analysis Services
      • Fact tables and dimension tables
      • Star schemas and snowflake schemas
      • Junk dimensions
      • Degenerate dimensions
      • Slowly Changing Dimensions
      • Bridge tables, or factless fact tables
      • Snapshot and transaction fact tables
      • Updating fact and dimension tables
      • Natural and surrogate keys
      • Unknown members, key errors, and NULLability
    • Physical database design for Analysis Services
      • Multiple data sources
      • Data types and Analysis Services
      • SQL queries generated during cube processing
        • Dimension processing
        • Dimensions with joined tables
        • Reference dimensions
        • Fact dimensions
        • Distinct count measures
        • Indexes in the data mart
      • Usage of schemas
      • Naming conventions
      • Views versus the Data Source View
    • Summary
  • 2. 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
      • Using the New Dimension' wizard
      • Using the Dimension Editor
        • Adding new attributes
        • Configuring a Time dimension
        • Creating user hierarchies
        • Configuring attribute relationships
    • Building a Simple Cube
      • Using the 'New Cube' wizard
      • Deployment
      • Processing
    • Summary
  • 3. Designing More Complex Dimensions
    • Grouping and Banding
      • Grouping
      • Banding
    • Slowly Changing Dimensions
      • Type I SCDs
      • Type II SCDs
        • Modeling attribute relationships on a Type II SCD
        • Handling member status
      • Type III SCDs
    • Junk dimensions
    • Ragged hierarchies
      • Parent/child hierarchies
      • Ragged hierarchies with HideMemberIf
    • Summary
  • 4. Measures and Measure Groups
    • Measures and aggregation
      • Useful properties of measures
        • Format String
        • Display folders
      • Built-in measure aggregation types
        • Basic aggregation types
        • Distinct Count
        • None
        • Semi-additive aggregation types
        • By Account
      • Dimension calculations
        • Unary operators and weights
        • Custom Member Formulas
      • Non-aggregatable values
    • Measure groups
      • Creating multiple measure groups
      • Creating measure groups from dimension tables
      • Handling different dimensionality
      • Handling different granularities
      • Non-aggregatable measures: a different approach
      • Using linked dimensions and measure groups
      • Role-playing dimensions
    • Dimension/measure group relationships
      • Fact relationships
      • Referenced relationships
      • Data mining relationships
    • Summary
  • 5. Adding Transactional Data such as Invoice Line and Sales Reason
    • Details about transactional data
    • Drillthrough
      • Actions
      • Drillthrough actions
        • Drillthrough Columns order
        • Drillthrough and calculated members
      • Drillthrough modeling
        • Drillthrough using a transaction details dimension
        • Drillthrough with ROLAP dimensions
        • Drillthrough on Alternate Fact Table
        • Drillthrough recap
    • Many-to-many dimension relationships
      • Implementing a many-to-many dimension relationship
      • Advanced modelling with many-to-many relationships
      • Performance issues
    • Summary
  • 6. Adding Calculations to the Cube
    • Different kinds of calculated members
    • Common calculations
      • Simple calculations
      • Referencing cell values
      • Aggregating members
      • Year-to-dates
      • Ratios over a hierarchy
      • Previous period growths
      • Same period previous year
      • Moving averages
      • Ranks
      • Formatting calculated measures
    • Calculation dimensions
      • Implementing a simple calculation dimension
      • Calculation dimension pitfalls and problems
        • Attribute overwrite
        • Limitations of calculated members
      • Calculation dimension best practices
    • Named sets
      • Regular named sets
      • Dynamic named sets
    • Summary
  • 7. Adding Currency Conversion
    • Introduction to currency conversion
      • Data collected in a single currency
      • Data collected in a multiple currencies
    • Where to perform currency conversion
    • The Add Business Intelligence Wizard
      • Concepts and prerequisites
      • How to use the Add Business Intelligence wizard
        • Data collected in a single currency with reporting in multiple currencies
        • Data collected in multiple currencies with reporting in a single currency
        • Data stored in multiple currencies with reporting in multiple currencies
    • Measure expressions
      • DirectSlice property
      • Writeback
    • Summary
  • 8. Query Performance Tuning
    • How Analysis Services processes queries
    • Performance tuning methodology
    • Designing for performance
    • Performance-specific design features
      • Partitions
        • Why partition?
        • Building partitions
        • Planning a partitioning strategy
        • Unexpected partition scans
      • Aggregations
        • Creating an initial aggregation design
        • Usage-based optimization
        • Monitoring partition and aggregation usage
        • Building aggregations manually
        • Common aggregation design issues
    • MDX calculation performance
      • Diagnosing Formula Engine performance problems
      • Calculation performance tuning
        • Tuning algorithms used in MDX
          • Using named sets to avoid recalculating set expressions
        • Using calculated members to cache numeric values
        • Tuning the implementation of MDX
    • Caching
      • Formula cache scopes
      • Other scenarios that restrict caching
      • Cache warming
        • Create Cache statement
        • Running batches of queries
    • Scale-up and scale-out
    • Summary
  • 9. Securing the Cube
    • Sample security requirements
    • Analysis Services security features
      • Roles and role membership
      • Securable objects
      • Creating roles
      • Membership of multiple roles
      • Testing roles
    • Administrative security
    • Data security
      • Granting read access to cubes
      • Cell security
      • Dimension security
      • Applying security to measures
      • Dynamic security
      • Dynamic dimension security
      • Dynamic security with stored procedures
      • Dimension security and parent/child hierarchies
    • Dynamic cell security
    • Accessing Analysis Services from outside a domain
    • Managing security
    • Security and query performance
      • Cell security
      • Dimension security
      • Dynamic security
    • Summary
  • 10. Productionization
    • Making changes to a cube in production
    • Managing partitions
      • Relational versus Analysis Services partitioning
      • Building a template partition
      • Generating partitions in Integration Services
    • Managing processing
      • Dimension processing
      • Partition processing
      • Lazy Aggregations
      • Processing reference dimensions
      • Handling processing errors
      • Managing processing with Integration Services
      • Push-mode processing
      • Proactive caching
    • Analysis Services data directory maintenance
    • Backup
    • Copying databases between servers
    • Summary
  • 11. Monitoring Cube Performance and Usage
    • Analysis Services and the operating system
      • Resources shared by the operating system
        • CPU
        • Memory
        • I/O operations
      • Tools to monitor resource consumption
        • Windows Task Manager
        • Performance counters
        • Resource Monitor
      • Analysis Services memory management
        • Memory differences between 32 bit and 64 bit
        • Controlling the Analysis Services Memory Manager
        • Out of memory conditions in Analysis Services
      • Sharing SQL Server and Analysis Services on the same machine
    • Monitoring processing performance
      • Monitoring processing with trace data
        • SQL Server Profiler
        • ASTrace
        • XMLA
        • Flight Recorder
      • Monitoring Processing with Performance Monitor counters
      • Monitoring Processing with Dynamic Management Views
    • Monitoring query performance
      • Monitoring queries with trace data
      • Monitoring queries with Performance Monitor counters
      • Monitoring queries with Dynamic Management Views
      • MDX Studio
    • Monitoring usage
      • Monitoring Usage with Trace Data
      • Monitoring usage with Performance Monitor counters
      • Monitoring usage with Dynamic Management Views
      • Activity Viewer
    • How to build a complete monitoring solution
    • Summary
  • Index

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