Details

The Data Warehouse Toolkit

The Definitive Guide to Dimensional Modeling
3. Aufl.

von: Ralph Kimball, Margy Ross
47,99 €
Verlag:	Wiley
Format:	EPUB
Veröffentl.:	01.07.2013
ISBN/EAN:	9781118732281
Sprache:	englisch
Anzahl Seiten:	608

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Titelbeschreibung

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. <ul> <li>Authored by Ralph Kimball and Margy Ross, known worldwide as educators, consultants, and influential thought leaders in data warehousing and business intelligence</li> <li>Begins with fundamental design recommendations and progresses through increasingly complex scenarios</li> <li>Presents unique modeling techniques for business applications such as inventory management, procurement, invoicing, accounting, customer relationship management, big data analytics, and more</li> <li>Draws real-world case studies from a variety of industries, including retail sales, financial services, telecommunications, education, health care, insurance, e-commerce, and more</li> </ul> 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.

Inhaltsverzeichnis

Introduction xxvii 1 Data Warehousing, Business Intelligence, and Dimensional Modeling Primer 1 Different Worlds of Data Capture and Data Analysis 2 Goals of Data Warehousing and Business Intelligence 3 Dimensional Modeling Introduction 7 Kimball’s DW/BI Architecture 18 Alternative DW/BI Architectures 26 Dimensional Modeling Myths 30 More Reasons to Think Dimensionally 32 Agile Considerations 34 Summary 35 2 Kimball Dimensional Modeling Techniques Overview 37 Fundamental Concepts 37 Basic Fact Table Techniques 41 Basic Dimension Table Techniques 46 Integration via Conformed Dimensions 50 Dealing with Slowly Changing Dimension Attributes 53 Dealing with Dimension Hierarchies 56 Advanced Fact Table Techniques 58 Advanced Dimension Techniques 62 Special Purpose Schemas 67 3 Retail Sales 69 Four-Step Dimensional Design Process 70 Retail Case Study 72 Dimension Table Details 79 Retail Schema in Action 94 Retail Schema Extensibility 95 Factless Fact Tables 97 Dimension and Fact Table Keys 98 Resisting Normalization Urges 104 Summary 109 4 Inventory 111 Value Chain Introduction 111 Inventory Models 112 Fact Table Types 119 Value Chain Integration 122 Enterprise Data Warehouse Bus Architecture 123 Conformed Dimensions 130 Conformed Facts 138 Summary 139 5 Procurement 141 Procurement Case Study 141 Procurement Transactions and Bus Matrix 142 Slowly Changing Dimension Basics 147 Hybrid Slowly Changing Dimension Techniques 159 Slowly Changing Dimension Recap 164 Summary 165 6 Order Management 167 Order Management Bus Matrix 168 Order Transactions 168 Invoice Transactions 187 Accumulating Snapshot for Order Fulfillment Pipeline 194 Summary 199 7 Accounting 201 Accounting Case Study and Bus Matrix 202 General Ledger Data 203 Budgeting Process 210 Dimension Attribute Hierarchies 214 Consolidated Fact Tables 224 Role of OLAP and Packaged Analytic Solutions 226 Summary 227 8 Customer Relationship Management 229 CRM Overview 230 Customer Dimension Attributes 233 Bridge Tables for Multivalued Dimensions 245 Complex Customer Behavior 249 Customer Data Integration Approaches 256 Low Latency Reality Check 260 Summary 261 9 Human Resources Management 263 Employee Profile Tracking 263 Headcount Periodic Snapshot 267 Bus Matrix for HR Processes 268 Packaged Analytic Solutions and Data Models 270 Recursive Employee Hierarchies 271 Multivalued Skill Keyword Attributes 274 Survey Questionnaire Data 277 Summary 279 10 Financial Services 281 Banking Case Study and Bus Matrix 282 Dimension Triage to Avoid Too Few Dimensions 283 Supertype and Subtype Schemas for Heterogeneous Products 293 Hot Swappable Dimensions 296 Summary 296 11 Telecommunications 297 Telecommunications Case Study and Bus Matrix 297 General Design Review Considerations 299 Design Review Guidelines 304 Draft Design Exercise Discussion 306 Remodeling Existing Data Structures 309 Geographic Location Dimension 310 Summary 310 12 Transportation 311 Airline Case Study and Bus Matrix 311 Extensions to Other Industries 317 Combining Correlated Dimensions 318 More Date and Time Considerations 321 Localization Recap 324 Summary 324 13 Education 325 University Case Study and Bus Matrix 325 Accumulating Snapshot Fact Tables 326 Factless Fact Tables 329 More Educational Analytic Opportunities 336 Summary 336 14 Healthcare 339 Healthcare Case Study and Bus Matrix 339 Claims Billing and Payments 342 Electronic Medical Records 348 Facility/Equipment Inventory Utilization 351 Dealing with Retroactive Changes 351 Summary 352 15 Electronic Commerce 353 Clickstream Source Data 353 Clickstream Dimensional Models 357 Integrating Clickstream into Web Retailer’s Bus Matrix 368 Profitability Across Channels Including Web 370 Summary 373 16 Insurance 375 Insurance Case Study 376 Policy Transactions 379 Premium Periodic Snapshot 385 More Insurance Case Study Background 388 Claim Transactions 390 Claim Accumulating Snapshot 392 Policy/Claim Consolidated Periodic Snapshot 395 Factless Accident Events 396 Common Dimensional Modeling Mistakes to Avoid 397 Summary 401 17 Kimball DW/BI Lifecycle Overview 403 Lifecycle Roadmap 404 Lifecycle Launch Activities 406 Lifecycle Technology Track 416 Lifecycle Data Track 420 Lifecycle BI Applications Track 422 Lifecycle Wrap-up Activities 424 Common Pitfalls to Avoid 426 Summary 427 18 Dimensional Modeling Process and Tasks 429 Modeling Process Overview 429 Get Organized 431 Design the Dimensional Model 434 Summary 441 19 ETL Subsystems and Techniques 443 Round Up the Requirements 444 The 34 Subsystems of ETL 449 Extracting: Getting Data into the Data Warehouse 450 Cleaning and Conforming Data 455 Delivering: Prepare for Presentation 463 Managing the ETL Environment 483 Summary 496 20 ETL System Design and Development Process and Tasks 497 ETL Process Overview 497 Develop the ETL Plan 498 Develop One-Time Historic Load Processing 503 Develop Incremental ETL Processing 512 Real-Time Implications 520 Summary 526 21 Big Data Analytics 527 Big Data Overview 527 Recommended Best Practices for Big Data 531 Summary 542 Index 543

Autorenportrait

RALPH KIMBALL, PhD, has been a leading visionary in the data warehouse and business intelligence industry since 1982. The Data Warehouse Toolkit book series have been bestsellers since 1996. MARGY ROSS is President of the Kimball Group and the coauthor of five Toolkit books with Ralph Kimball. She has focused exclusively on data warehousing and business intelligence for more than 30 years.

Back cover copy

The most authoritative and comprehensive guide to dimensional modeling, from its originators—fully updated Ralph Kimball introduced the industry to the techniques of dimensional modeling in the first edition of The Data Warehouse Toolkit (1996). Since then, dimensional modeling has become the most widely accepted approach for presenting information in data warehouse and business intelligence (DW/BI) systems. The Data Warehouse Toolkit is recognized as the definitive source for dimensional modeling techniques, patterns, and best practices. This third edition of the classic reference delivers the most comprehensive library of dimensional modeling techniques ever assembled. Fully updated with fresh insights and best practices, this book provides clear guidelines for designing dimensional models—and does so in a style that serves the needs of those new to data warehousing as well as experienced professionals. All the techniques in the book are illustrated with real-world case studies based on the authors' actual DW/BI design experiences. In addition, the Kimball Group's "official" list of dimensional modeling techniques is summarized in a single chapter for easy reference, with pointers from each technique to the case studies where the concepts are brought to life. The third edition of The Data Warehouse Toolkit covers: <ul> <li>Practical design techniques—both basic and advanced—for dimension and fact tables</li> <li>14 case studies, including retail sales, electronic commerce, customer relationship management, procurement, inventory, order management, accounting, human resources, financial services, healthcare, insurance, education, telecommunications, and transportation</li> <li>Sample data warehouse bus matrices for 12 case studies</li> <li>Dimensional modeling pitfalls and mistakes to avoid</li> <li>Enhanced slowly changing dimension techniques type 0 through 7</li> <li>Bridge tables for ragged variable depth hierarchies and multivalued attributes</li> <li>Best practices for Big Data analytics</li> <li>Guidelines for collaborative, interactive design sessions with business stakeholders</li> <li>An overview of the Kimball DW/BI project lifecycle methodology</li> <li>Comprehensive review of extract, transformation, and load (ETL) systems and design considerations</li> <li>The 34 ETL subsystems and techniques to populate dimension and fact tables</li> </ul>