The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition

The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition

Released July 2013
Publisher(s): Wiley
ISBN: 9781118530801

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Book description

Updated new edition of Ralph Kimball's groundbreaking book on dimensional modeling for data warehousing and business intelligence!

The first edition of Ralph Kimball's The Data Warehouse Toolkit introduced the industry to dimensional modeling, and now his books are considered the most authoritative guides in this space. This new third edition is a complete library of updated dimensional modeling techniques, the most comprehensive collection ever. It covers new and enhanced star schema dimensional modeling patterns, adds two new chapters on ETL techniques, includes new and expanded business matrices for 12 case studies, and more.

  • Authored by Ralph Kimball and Margy Ross, known worldwide as educators, consultants, and influential thought leaders in data warehousing and business intelligence

  • Begins with fundamental design recommendations and progresses through increasingly complex scenarios

  • Presents unique modeling techniques for business applications such as inventory management, procurement, invoicing, accounting, customer relationship management, big data analytics, and more

  • Draws real-world case studies from a variety of industries, including retail sales, financial services, telecommunications, education, health care, insurance, e-commerce, and more

Design dimensional databases that are easy to understand and provide fast query response with The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition.

Table of contents

  1. Cover
  2. Introduction
    1. Intended Audience
      1. Chapter Preview
      2. Website Resources
      3. Summary
  3. Chapter 1: Data Warehousing, Business Intelligence, and Dimensional Modeling Primer
    1. Different Worlds of Data Capture and Data Analysis
    2. Goals of Data Warehousing and Business Intelligence
    3. Dimensional Modeling Introduction
    4. Kimball's DW/BI Architecture
    5. Alternative DW/BI Architectures
    6. Dimensional Modeling Myths
    7. More Reasons to Think Dimensionally
    8. Agile Considerations
    9. Summary
  4. Chapter 2: Kimball Dimensional Modeling Techniques Overview
    1. Fundamental Concepts
    2. Basic Fact Table Techniques
    3. Basic Dimension Table Techniques
    4. Integration via Conformed Dimensions
    5. Dealing with Slowly Changing Dimension Attributes
    6. Dealing with Dimension Hierarchies
    7. Advanced Fact Table Techniques
    8. Advanced Dimension Techniques
    9. Special Purpose Schemas
  5. Chapter 3: Retail Sales
    1. Four-Step Dimensional Design Process
    2. Retail Case Study
    3. Dimension Table Details
    4. Retail Schema in Action
    5. Retail Schema Extensibility
    6. Factless Fact Tables
    7. Dimension and Fact Table Keys
    8. Resisting Normalization Urges
    9. Summary
  6. Chapter 4: Inventory
    1. Value Chain Introduction
    2. Inventory Models
    3. Fact Table Types
    4. Value Chain Integration
    5. Enterprise Data Warehouse Bus Architecture
    6. Conformed Dimensions
    7. Conformed Facts
    8. Summary
  7. Chapter 5: Procurement
    1. Procurement Case Study
    2. Procurement Transactions and Bus Matrix
    3. Slowly Changing Dimension Basics
    4. Hybrid Slowly Changing Dimension Techniques
    5. Slowly Changing Dimension Recap
    6. Summary
  8. Chapter 6: Order Management
    1. Order Management Bus Matrix
    2. Order Transactions
    3. Invoice Transactions
    4. Accumulating Snapshot for Order Fulfillment Pipeline
    5. Summary
  9. Chapter 7: Accounting
    1. Accounting Case Study and Bus Matrix
    2. General Ledger Data
    3. Budgeting Process
    4. Dimension Attribute Hierarchies
    5. Consolidated Fact Tables
    6. Role of OLAP and Packaged Analytic Solutions
    7. Summary
  10. Chapter 8: Customer Relationship Management
    1. CRM Overview
    2. Customer Dimension Attributes
    3. Bridge Tables for Multivalued Dimensions
    4. Complex Customer Behavior
    5. Customer Data Integration Approaches
    6. Low Latency Reality Check
    7. Summary
  11. Chapter 9: Human Resources Management
    1. Employee Profile Tracking
    2. Headcount Periodic Snapshot
    3. Bus Matrix for HR Processes
    4. Packaged Analytic Solutions and Data Models
    5. Recursive Employee Hierarchies
    6. Multivalued Skill Keyword Attributes
    7. Survey Questionnaire Data
    8. Summary
  12. Chapter 10: Financial Services
    1. Banking Case Study and Bus Matrix
    2. Dimension Triage to Avoid Too Few Dimensions
    3. Supertype and Subtype Schemas for Heterogeneous Products
    4. Hot Swappable Dimensions
    5. Summary
  13. Chapter 11: Telecommunications
    1. Telecommunications Case Study and Bus Matrix
    2. General Design Review Considerations
    3. Design Review Guidelines
    4. Draft Design Exercise Discussion
    5. Remodeling Existing Data Structures
    6. Geographic Location Dimension
    7. Summary
  14. Chapter 12: Transportation
    1. Airline Case Study and Bus Matrix
    2. Extensions to Other Industries
    3. Combining Correlated Dimensions
    4. More Date and Time Considerations
    5. Localization Recap
    6. Summary
  15. Chapter 13: Education
    1. University Case Study and Bus Matrix
    2. Accumulating Snapshot Fact Tables
    3. Factless Fact Tables
    4. More Educational Analytic Opportunities
    5. Summary
  16. Chapter 14: Healthcare
    1. Healthcare Case Study and Bus Matrix
    2. Claims Billing and Payments
    3. Electronic Medical Records
    4. Facility/Equipment Inventory Utilization
    5. Dealing with Retroactive Changes
    6. Summary
  17. Chapter 15: Electronic Commerce
    1. Clickstream Source Data
    2. Clickstream Dimensional Models
    3. Integrating Clickstream into Web Retailer's Bus Matrix
    4. Profitability Across Channels Including Web
    5. Summary
  18. Chapter 16: Insurance
    1. Insurance Case Study
    2. Policy Transactions
    3. Premium Periodic Snapshot
    4. More Insurance Case Study Background
    5. Claim Transactions
    6. Claim Accumulating Snapshot
    7. Policy/Claim Consolidated Periodic Snapshot
    8. Factless Accident Events
    9. Common Dimensional Modeling Mistakes to Avoid
    10. Summary
  19. Chapter 17: Kimball DW/BI Lifecycle Overview
    1. Lifecycle Roadmap
    2. Lifecycle Launch Activities
    3. Lifecycle Technology Track
    4. Lifecycle Data Track
    5. Lifecycle BI Applications Track
    6. Lifecycle Wrap-up Activities
    7. Common Pitfalls to Avoid
    8. Summary
  20. Chapter 18: Dimensional Modeling Process and Tasks
    1. Modeling Process Overview
    2. Get Organized
    3. Design the Dimensional Model
    4. Summary
  21. Chapter 19: ETL Subsystems and Techniques
    1. Round Up the Requirements
    2. The 34 Subsystems of ETL
    3. Extracting: Getting Data into the Data Warehouse
    4. Cleaning and Conforming Data
    5. Delivering: Prepare for Presentation
    6. Managing the ETL Environment
    7. Summary
  22. Chapter 20: ETL System Design and Development Process and Tasks
    1. ETL Process Overview
    2. Develop the ETL Plan
    3. Develop One-Time Historic Load Processing
    4. Develop Incremental ETL Processing
    5. Real-Time Implications
    6. Summary
  23. Chapter 21: Big Data Analytics
    1. Big Data Overview
    2. Recommended Best Practices for Big Data
    3. Summary
  24. Index
  25. Advertisement

Product information

  • Title: The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition
  • Author(s):
  • Release date: July 2013
  • Publisher(s): Wiley
  • ISBN: 9781118530801