The Data Warehouse Toolkit, 3rd Edition Ralph Kimball, Margy Ross Toolkit Definitive Guide To Dimensional Ing Wil
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- Cover
- Title Page
- Copyright
- Contents
- 1 Data Warehousing, Business Intelligence, and Dimensional Modeling Primer
- 2 Kimball Dimensional Modeling Techniques Overview
- Fundamental Concepts
- Basic Fact Table Techniques
- Basic Dimension Table Techniques
- Dimension Table Structure
- Dimension Surrogate Keys
- Natural, Durable, and Supernatural Keys
- Drilling Down
- Degenerate Dimensions
- Denormalized Flattened Dimensions
- Multiple Hierarchies in Dimensions
- Flags and Indicators as Textual Attributes
- Null Attributes in Dimensions
- Calendar Date Dimensions
- Role-Playing Dimensions
- Junk Dimensions
- Snowflaked Dimensions
- Outrigger Dimensions
- Integration via Conformed Dimensions
- Dealing with Slowly Changing Dimension Attributes
- Dealing with Dimension Hierarchies
- Advanced Fact Table Techniques
- Fact Table Surrogate Keys
- Centipede Fact Tables
- Numeric Values as Attributes or Facts
- Lag/Duration Facts
- Header/Line Fact Tables
- Allocated Facts
- Profit and Loss Fact Tables Using Allocations
- Multiple Currency Facts
- Multiple Units of Measure Facts
- Year-to-Date Facts
- Multipass SQL to Avoid Fact-to-Fact Table Joins
- Timespan Tracking in Fact Tables
- Late Arriving Facts
- Advanced Dimension Techniques
- Dimension-to-Dimension Table Joins
- Multivalued Dimensions and Bridge Tables
- Time Varying Multivalued Bridge Tables
- Behavior Tag Time Series
- Behavior Study Groups
- Aggregated Facts as Dimension Attributes
- Dynamic Value Bands
- Text Comments Dimension
- Multiple Time Zones
- Measure Type Dimensions
- Step Dimensions
- Hot Swappable Dimensions
- Abstract Generic Dimensions
- Audit Dimensions
- Late Arriving Dimensions
- Special Purpose Schemas
- 3 Retail Sales
- 4 Inventory
- Value Chain Introduction
- Inventory Models
- Fact Table Types
- Value Chain Integration
- Enterprise Data Warehouse Bus Architecture
- Conformed Dimensions
- Drilling Across Fact Tables
- Identical Conformed Dimensions
- Shrunken Rollup Conformed Dimension with Attribute Subset
- Shrunken Conformed Dimension with Row Subset
- Shrunken Conformed Dimensions on the Bus Matrix
- Limited Conformity
- Importance of Data Governance and Stewardship
- Conformed Dimensions and the Agile Movement
- Conformed Facts
- Summary
- 5 Procurement
- 6 Order Management
- 7 Accounting
- Accounting Case Study and Bus Matrix
- General Ledger Data
- Budgeting Process
- Dimension Attribute Hierarchies
- Fixed Depth Positional Hierarchies
- Slightly Ragged Variable Depth Hierarchies
- Ragged Variable Depth Hierarchies
- Shared Ownership in a Ragged Hierarchy
- Time Varying Ragged Hierarchies
- Modifying Ragged Hierarchies
- Alternative Ragged Hierarchy Modeling Approaches
- Advantages of the Bridge Table Approach for Ragged Hierarchies
- Consolidated Fact Tables
- Role of OLAP and Packaged Analytic Solutions
- Summary
- 8 Customer Relationship Management
- 9 Human Resources Management
- 10 Financial Services
- 11 Telecommunications
- 12 Transportation
- 13 Education
- 14 Healthcare
- 15 Electronic Commerce
- 16 Insurance
- Insurance Case Study
- Policy Transactions
- Dimension Role Playing
- Slowly Changing Dimensions
- Mini-Dimensions for Large or Rapidly Changing Dimensions
- Multivalued Dimension Attributes
- Numeric Attributes as Facts or Dimensions
- Degenerate Dimension
- Low Cardinality Dimension Tables
- Audit Dimension
- Policy Transaction Fact Table
- Heterogeneous Supertype and Subtype Products
- Complementary Policy Accumulating Snapshot
- 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
- Mistake 10: Place Text Attributes in a Fact Table
- Mistake 9: Limit Verbose Descriptors to Save Space
- Mistake 8: Split Hierarchies into Multiple Dimensions
- Mistake 7: Ignore the Need to Track Dimension Changes
- Mistake 6: Solve All Performance Problems with More Hardware
- Mistake 5: Use Operational Keys to Join Dimensions and Facts
- Mistake 4: Neglect to Declare and Comply with the Fact Grain
- Mistake 3: Use a Report to Design the Dimensional Model
- Mistake 2: Expect Users to Query Normalized Atomic Data
- Mistake 1: Fail to Conform Facts and Dimensions
- Summary
- 17 Kimball DW/BI Lifecycle Overview
- 18 Dimensional Modeling Process and Tasks
- 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
- Subsystem 9: Slowly Changing Dimension Manager
- Subsystem 10: Surrogate Key Generator
- Subsystem 11: Hierarchy Manager
- Subsystem 12: Special Dimensions Manager
- Subsystem 13: Fact Table Builders
- Subsystem 14: Surrogate Key Pipeline
- Subsystem 15: Multivalued Dimension Bridge Table Builder
- Subsystem 16: Late Arriving Data Handler
- Subsystem 17: Dimension Manager System
- Subsystem 18: Fact Provider System
- Subsystem 19: Aggregate Builder
- Subsystem 20: OLAP Cube Builder
- Subsystem 21: Data Propagation Manager
- Managing the ETL Environment
- Subsystem 22: Job Scheduler
- Subsystem 23: Backup System
- Subsystem 24: Recovery and Restart System
- Subsystem 25: Version Control System
- Subsystem 26: Version Migration System
- Subsystem 27: Workflow Monitor
- Subsystem 28: Sorting System
- Subsystem 29: Lineage and Dependency Analyzer
- Subsystem 30: Problem Escalation System
- Subsystem 31: Parallelizing/Pipelining System
- Subsystem 32: Security System
- Subsystem 33: Compliance Manager
- Subsystem 34: Metadata Repository Manager
- Summary
- 20 ETL System Design and Development Process and Tasks
- 21 Big Data Analytics
- Index
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