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