Cover -- Title Page -- Copyright -- Contents -- 1 Data Warehousing, Business Intelligence, and Dimensional Modeling Primer -- Different Worlds of Data Capture and Data Analysis -- Goals of Data Warehousing and Business Intelligence -- Publishing Metaphor for DW/BI Managers -- Dimensional Modeling Introduction -- Star Schemas Versus OLAP Cubes -- Fact Tables for Measurements -- Dimension Tables for Descriptive Context -- Facts and Dimensions Joined in a Star Schema -- Kimball's DW/BI Architecture -- Operational Source Systems -- Extract, Transformation, and Load System -- Presentation Area to Support Business Intelligence -- Business Intelligence Applications -- Restaurant Metaphor for the Kimball Architecture -- Alternative DW/BI Architectures -- Independent Data Mart Architecture -- Hub-and-Spoke Corporate Information Factory Inmon Architecture -- Hybrid Hub-and-Spoke and Kimball Architecture -- Dimensional Modeling Myths -- Myth 1: Dimensional Models are Only for Summary Data -- Myth 2: Dimensional Models are Departmental, Not Enterprise -- Myth 3: Dimensional Models are Not Scalable -- Myth 4: Dimensional Models are Only for Predictable Usage -- Myth 5: Dimensional Models Can't Be Integrated -- More Reasons to Think Dimensionally -- Agile Considerations -- Summary -- 2 Kimball Dimensional Modeling Techniques Overview -- Fundamental Concepts -- Gather Business Requirements and Data Realities -- Collaborative Dimensional Modeling Workshops -- Four-Step Dimensional Design Process -- Business Processes -- Grain -- Dimensions for Descriptive Context -- Facts for Measurements -- Star Schemas and OLAP Cubes -- Graceful Extensions to Dimensional Models -- Basic Fact Table Techniques -- Fact Table Structure -- Additive, Semi-Additive, Non-Additive Facts -- Nulls in Fact Tables -- Conformed Facts -- Transaction Fact Tables.

Periodic Snapshot Fact Tables -- Accumulating Snapshot Fact Tables -- Factless Fact Tables -- Aggregate Fact Tables or OLAP Cubes -- Consolidated Fact Tables -- 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 -- Conformed Dimensions -- Shrunken Dimensions -- Drilling Across -- Value Chain -- Enterprise Data Warehouse Bus Architecture -- Enterprise Data Warehouse Bus Matrix -- Detailed Implementation Bus Matrix -- Opportunity/Stakeholder Matrix -- Dealing with Slowly Changing Dimension Attributes -- Type 0: Retain Original -- Type 1: Overwrite -- Type 2: Add New Row -- Type 3: Add New Attribute -- Type 4: Add Mini-Dimension -- Type 5: Add Mini-Dimension and Type 1 Outrigger -- Type 6: Add Type 1 Attributes to Type 2 Dimension -- Type 7: Dual Type 1 and Type 2 Dimensions -- Dealing with Dimension Hierarchies -- Fixed Depth Positional Hierarchies -- Slightly Ragged/Variable Depth Hierarchies -- Ragged/Variable Depth Hierarchies with Hierarchy Bridge Tables -- Ragged/Variable Depth Hierarchies with Pathstring Attributes -- 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 -- Supertype and Subtype Schemas for Heterogeneous Products -- Real-Time Fact Tables -- Error Event Schemas -- 3 Retail Sales -- Four-Step Dimensional Design Process -- Step 1: Select the Business Process -- Step 2: Declare the Grain -- Step 3: Identify the Dimensions -- Step 4: Identify the Facts -- Retail Case Study -- Step 1: Select the Business Process -- Step 2: Declare the Grain -- Step 3: Identify the Dimensions -- Step 4: Identify the Facts -- Dimension Table Details -- Date Dimension -- Product Dimension -- Store Dimension -- Promotion Dimension -- Other Retail Sales Dimensions -- Degenerate Dimensions for Transaction Numbers -- Retail Schema in Action -- Retail Schema Extensibility -- Factless Fact Tables -- Dimension and Fact Table Keys -- Dimension Table Surrogate Keys -- Dimension Natural and Durable Supernatural Keys -- Degenerate Dimension Surrogate Keys -- Date Dimension Smart Keys -- Fact Table Surrogate Keys -- Resisting Normalization Urges -- Snowflake Schemas with Normalized Dimensions -- Outriggers -- Centipede Fact Tables with Too Many Dimensions -- Summary -- 4 Inventory -- Value Chain Introduction -- Inventory Models -- Inventory Periodic Snapshot -- Inventory Transactions.

Inventory Accumulating Snapshot -- Fact Table Types -- Transaction Fact Tables -- Periodic Snapshot Fact Tables -- Accumulating Snapshot Fact Tables -- Complementary Fact Table Types -- Value Chain Integration -- Enterprise Data Warehouse Bus Architecture -- Understanding the Bus Architecture -- Enterprise Data Warehouse Bus Matrix -- 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 -- Procurement Case Study -- Procurement Transactions and Bus Matrix -- Single Versus Multiple Transaction Fact Tables -- Complementary Procurement Snapshot -- Slowly Changing Dimension Basics -- Type 0: Retain Original -- Type 1: Overwrite -- Type 2: Add New Row -- Type 3: Add New Attribute -- Type 4: Add Mini-Dimension -- Hybrid Slowly Changing Dimension Techniques -- Type 5: Mini-Dimension and Type 1 Outrigger -- Type 6: Add Type 1 Attributes to Type 2 Dimension -- Type 7: Dual Type 1 and Type 2 Dimensions -- Slowly Changing Dimension Recap -- Summary -- 6 Order Management -- Order Management Bus Matrix -- Order Transactions -- Fact Normalization -- Dimension Role Playing -- Product Dimension Revisited -- Customer Dimension -- Deal Dimension -- Degenerate Dimension for Order Number -- Junk Dimensions -- Header/Line Pattern to Avoid -- Multiple Currencies -- Transaction Facts at Different Granularity -- Another Header/Line Pattern to Avoid -- Invoice Transactions -- Service Level Performance as Facts, Dimensions, or Both -- Profit and Loss Facts -- Audit Dimension.

Accumulating Snapshot for Order Fulfillment Pipeline -- Lag Calculations -- Multiple Units of Measure -- Beyond the Rearview Mirror -- Summary -- 7 Accounting -- Accounting Case Study and Bus Matrix -- General Ledger Data -- General Ledger Periodic Snapshot -- Chart of Accounts -- Period Close -- Year-to-Date Facts -- Multiple Currencies Revisited -- General Ledger Journal Transactions -- Multiple Fiscal Accounting Calendars -- Drilling Down Through a Multilevel Hierarchy -- Financial Statements -- 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 -- CRM Overview -- Operational and Analytic CRM -- Customer Dimension Attributes -- Name and Address Parsing -- International Name and Address Considerations -- Customer-Centric Dates -- Aggregated Facts as Dimension Attributes -- Segmentation Attributes and Scores -- Counts with Type 2 Dimension Changes -- Outrigger for Low Cardinality Attribute Set -- Customer Hierarchy Considerations -- Bridge Tables for Multivalued Dimensions -- Bridge Table for Sparse Attributes -- Bridge Table for Multiple Customer Contacts -- Complex Customer Behavior -- Behavior Study Groups for Cohorts -- Step Dimension for Sequential Behavior -- Timespan Fact Tables -- Tagging Fact Tables with Satisfaction Indicators -- Tagging Fact Tables with Abnormal Scenario Indicators -- Customer Data Integration Approaches.

Master Data Management Creating a Single Customer Dimension.