Table of Contents: “…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 Advertisement…”