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Author Kimball, Ralph
Title The Data Warehouse Toolkit : The Definitive Guide to Dimensional Modeling
Imprint New York : John Wiley & Sons, Incorporated, 2013
book jacket
Edition 3rd ed
Descript 1 online resource (602 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Note 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 -- Partial Conformity of Multiple Customer Dimensions -- Avoiding Fact-to-Fact Table Joins
Low Latency Reality Check
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
Description based on publisher supplied metadata and other sources
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2020. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
Link Print version: Kimball, Ralph The Data Warehouse Toolkit : The Definitive Guide to Dimensional Modeling New York : John Wiley & Sons, Incorporated,c2013 9781118530801
Subject Multidimensional databases
Electronic books
Alt Author Ross, Margy
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