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

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Autorzy:: Alberto Ferrari, Marco Russon, Chris Webb

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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 Alberto Ferrari, Marco Russon, Chris Webb - okładka ebooka

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O autorach ebooka

Alberto Ferrari - jest autorytetem w dziedzinie modelowania danych oraz usług analitycznych w dużych i złożonych hurtowniach danych.

Marco Russo is a Business Intelligence consultant and mentor. His main activities are related to data warehouse relational and multidimensional design, but he is also involved in the complete development lifecycle of a BI solution. He has particular competence and experience in sectors such as financial services (including complex OLAP designs in the banking area), manufacturing, gambling, and commercial distribution. Marco is also a book author, and in addition to his BI-related publications, he has authored books about .NET programming. He is also a speaker at international conferences such as TechEd, PASS Summit, SQLRally, and SQLBits. He achieved the unique SSAS Maestro certification and is also a Microsoft Certified Trainer with several Microsoft Certified Professional certifications.

Chris Webb (chris@crossjoin.co.uk) has been working with Microsoft Business Intelligence tools for 15 years in a variety of roles and industries. He is an independent consultant (www.crossjoin.co.uk) and trainer (www.technitrain.com) based in the UK, specializing in SQL Server Analysis Services, MDX, DAX, Power Pivot, and the whole Power BI stack. He is the co-author of MDX Solutions with Microsoft SQL Server Analysis Services 2005 and SQL Server Analysis Services 2012: The BISM Tabular Model. He is a regular speaker at user groups and conferences, and blogs about Microsoft BI at http://cwebbbi.wordpress.com/.

Alberto Ferrari, Marco Russon, Chris Webb - pozostałe książki

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Oceny i opinie klientów: 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 Alberto Ferrari, Marco Russon, Chris Webb (0) Weryfikacja opinii następuję na podstawie historii zamówień na koncie Użytkownika umieszczającego opinię. Użytkownik mógł otrzymać punkty za opublikowanie opinii uprawniające do uzyskania rabatu w ramach Programu Punktowego.

Szczegóły ebooka

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 Business Intelligence capabilities.
ISBN Ebooka:: 978-18-496-8991-5, 9781849689915
Data wydania ebooka:: 2014-02-24 Data wydania ebooka często jest dniem wprowadzenia tytułu do sprzedaży i może nie być równoznaczna z datą wydania książki papierowej. Dodatkowe informacje możesz znaleźć w darmowym fragmencie. Jeśli masz wątpliwości skontaktuj się z nami sklep@ebookpoint.pl.
Język publikacji:: angielski
Rozmiar pliku Pdf:: 7.1MB
Rozmiar pliku ePub:: 13.6MB
Rozmiar pliku Mobi:: 20.9MB

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Spis treści ebooka

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

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