Expert Cube Development with SSAS Multidimensional Models. For Analysis Service cube designers this is the hands-on tutorial that will take your expertise to a whole new level. Written by a team of Microsoft SSAS experts, it digs deep to optimize your Bus - Helion

ebook

Autor: Alberto Ferrari, Marco Russon, Chris Webb
Tytuł oryginału: Expert Cube Development with SSAS Multidimensional Models. For Analysis Service cube designers this is the hands-on tutorial that will take your expertise to a whole new level. Written by a team of Microsoft SSAS experts, it digs deep to optimize your Bus
ISBN: 9781849689915
stron: 402, Format: ebook
Data wydania: 2014-02-24
Księgarnia: Helion

Cena książki: 159,00 zł

Osoby, które kupiły tę książkę, wybierały także »

Osoby które kupowały "Expert Cube Development with SSAS Multidimensional Models. For Analysis Service cube designers this is the hands-on tutorial that will take your expertise to a whole new level. Written by a team of Microsoft SSAS experts, it digs deep to optimize your Bus", wybierały także:

Windows Media Center. Domowe centrum rozrywki 66,67 zł, (8,00 zł -88%)
Ruby on Rails. Ćwiczenia 18,75 zł, (3,00 zł -84%)
DevOps w praktyce. Kurs video. Jenkins, Ansible, Terraform i Docker 190,00 zł, (39,90 zł -79%)
Przywództwo w świecie VUCA. Jak być skutecznym liderem w niepewnym środowisku 58,64 zł, (12,90 zł -78%)
Scrum. O zwinnym zarządzaniu projektami. Wydanie II rozszerzone 58,64 zł, (12,90 zł -78%)

Spis treści

Expert Cube Development with SSAS Multidimensional Models. For Analysis Service cube designers this is the hands-on tutorial that will take your expertise to a whole new level. Written by a team of Microsoft SSAS experts, it digs deep to optimize your Business Intelligence capabilities eBook -- spis treści

Expert Cube Development with SSAS Multidimensional Models
- Table of Contents
- Expert Cube Development with SSAS Multidimensional Models
- Credits
- About the Authors
- About the Reviewers
- www.PacktPub.com
  - Support files, eBooks, discount offers and more
    - Why subscribe?
    - Free access for Packt account holders
    - Instant updates on new Packt books
- 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
    - Downloading the color images of this 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
        
        Dimension tables
        
        Fact tables
    - Usage of schemas
    - Naming conventions
    - Views versus the Data Source View
  - Summary
- 2. Building Basic Dimensions and Cubes
  - Multidimensional and Tabular models
  - 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
    - Project deployment
    - Database processing
  - Summary
- 3. Designing More Complex Dimensions
  - Grouping and banding
    - Grouping
    - Banding
  - Modeling Slowly Changing Dimensions
    - Type I SCDs
    - Type II SCDs
      - Modeling attribute relationships on a Type II SCD
      - Handling member status
    - Type III SCDs
  - Modeling junk dimensions
  - Modeling ragged hierarchies
    - Modeling parent/child hierarchies
    - Ragged hierarchies with HideMemberIf
  - Summary
- 4. Measures and Measure Groups
  - Measures and aggregation
    - Useful properties of measures
      - FormatString
      - DisplayFolders
    - Built-in measure aggregation types
      - Basic aggregation types
      - DistinctCount
      - None
      - Semi-additive aggregation types
      - ByAccount
    - Dimension calculations
      - Unary operators and weights
      - Custom Member Formulas
    - Non-aggregatable values
  - Measure groups
    - Creating multiple measure groups
    - Creating measure groups from dimension tables
      - MDX formulas versus pre-calculating values
    - 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. Handling Transactional-Level Data
  - Details about transactional data
  - Drillthrough
    - Actions
    - Drillthrough actions
      - Drillthrough columns order
      - Drillthrough and calculated members
    - Drillthrough modeling
      - Drillthrough using a transaction detail 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 modeling 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-date calculations
    - Ratios over a hierarchy
    - Previous period growths
    - Same period previous year
    - Moving averages
    - Ranks
    - Formatting calculated measures
  - Calculation dimensions
    - Implementing a simple calculation dimension
    - The Time Intelligence wizard
      - 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
  - Understanding 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
      - The 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
      - Visual Totals
      - Restricting access to Dimension Members
      - 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. Going in Production
  - 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
  - SSAS Data Directory maintenance
  - Performing database 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
  - Monitoring usage
    - Monitoring usage with trace data
    - Monitoring usage with Performance Monitor counters
    - Monitoring usage with Dynamic Management Views
    - Activity Viewer
  - Building a complete monitoring solution
  - Summary
- A. DAX Query Support
  - Implementation details
    - Mapping Multidimensional objects to Tabular concepts
    - Unsupported features
    - New functionality in Analysis Services
  - Connecting Power View to a Multidimensional model
  - Running DAX queries against a Multidimensional model
    - Executing DAX queries
    - DAX queries and attributes
- Index