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Informationen zum Autor William H. Inmon is the acknowledged "Father of Data Warehousing" and a partner in www.billinmon.com, a Web site featuring information on data warehousing and related technologies. He has written more than 40 books on database and data warehousing technologies, and is a frequent speaker (and often the keynote) at major conferences. Klappentext * The new edition of the classic bestseller that launched the data warehousing industry covers new approaches and technologies, many of which have been pioneered by Inmon himself* In addition to explaining the fundamentals of data warehouse systems, the book covers new topics such as methods for handling unstructured data in a data warehouse and storing data across multiple storage media* Discusses the pros and cons of relational versus multidimensional design and how to measure return on investment in planning data warehouse projects* Covers advanced topics, including data monitoring and testing* Although the book includes an extra 100 pages worth of valuable content, the price has actually been reduced from $65 to $55 Zusammenfassung Explains the fundamentals of data warehouse systems. This book covers topics such as methods for handling unstructured data in a data warehouse and storing data across multiple storage media, and discusses the pros and cons of relational versus multidimensional design, and how to measure return on investment in planning data warehouse projects. Inhaltsverzeichnis Preface xix Acknowledgments xxvii Chapter 1 Evolution of Decision Support Systems 1 The Evolution 2 The Advent of DASD 4 PC/4GL Technology 4 Enter the Extract Program 5 The Spider Web 6 Problems with the Naturally Evolving Architecture 7 Lack of Data Credibility 7 Problems with Productivity 9 From Data to Information 12 A Change in Approach 14 The Architected Environment 16 Data Integration in the Architected Environment 18 Who Is the User? 20 The Development Life Cycle 20 Patterns of Hardware Utilization 22 Setting the Stage for Re-engineering 23 Monitoring the Data Warehouse Environment 25 Summary 28 Chapter 2 The Data Warehouse Environment 29 The Structure of the Data Warehouse 33 Subject Orientation 34 Day 1 to Day n Phenomenon 39 Granularity 41 The Benefits of Granularity 42 An Example of Granularity 43 Dual Levels of Granularity 46 Exploration and Data Mining 50 Living Sample Database 50 Partitioning as a Design Approach 53 Partitioning of Data 53 Structuring Data in the Data Warehouse 56 Auditing and the Data Warehouse 61 Data Homogeneity and Heterogeneity 61 Purging Warehouse Data 64 Reporting and the Architected Environment 64 The Operational Window of Opportunity 65 Incorrect Data in the Data Warehouse 67 Summary 69 Chapter 3 The Data Warehouse and Design 71 Beginning with Operational Data 71 Process and Data Models and the Architected Environment 78 The Data Warehouse and Data Models 79 The Data Warehouse Data Model 81 The Midlevel Data Model 84 The Physical Data Model 88 The Data Model and Iterative Development 91 Normalization and Denormalization 94 Snapshots in the Data Warehouse 100 Metadata 102 Managing Reference Tables in a Data Warehouse 103 Cyclicity of Data - The Wrinkle of Time 105 Complexity of Transformation and Integration 108 Triggering the Data Warehouse Record 112 Events 112 Components of the Snapshot 113 Some Examples 113 Profile Records 114 Managing Volume 115 Creating Multiple Profile Records 117 Going from the Data Warehouse to the Operation...
