Designing a data warehouse: supporting customer relationship management
he main subject of this book is data warehousing. A data warehouse is a special kind of database that, in recent years, has attracted a great deal of interest in the information technology industry. Quite a few books have been published about data warehousing generally, but very few have focused on...
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| Язык: | Spanish English |
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| 100 | 1 | |9 190960 |a Todman, Chris | |
| 245 | |a Designing a data warehouse: supporting customer relationship management |c Chris Todman |h imp | ||
| 264 | |a New Jersey |b Prentice Hall |c 2001 | ||
| 300 | |a xx, 323 páginas: |b gra |c 23.5 cm | ||
| 504 | |a incl. ref. | ||
| 505 | 0 | |a 1. Preface 2. Acknowledgments 3. Customer Relationship Management 1. The Business Dimension 2. Business Goals 3. Business Strategy 4. The Value Proposition 5. Customer Relationship Management 6. Summary 4. An Introduction To Data Warehousing 1. Introduction 2. What Is A Data Warehouse? 3. Dimensional Analysis 4. Building A Data Warehouse 5. Problems When Using Relational Databases 6. Summary 5. Design Problems We Have To Face Up To 1. Dimensional Data Models 2. What Works For Crm 3. Summary 6. The Implications Of Time In Data Warehousing 1. The Role Of Time 2. Problems Involving Time 3. Capturing Changes 4. First-Generation Solutions For Time 5. Variations On A Theme 6. Conclusion To The Review Of First-Generation Methods 7. The Conceptual Model 1. Requirements Of The Conceptual Model 2. The Identification Of Changes To Data 3. Dot Modeling 4. Dot Modeling Workshops 5. Summary 8. The Logical Model 1. Logical Modeling 2. The Implementation Of Retrospection 3. The Use Of The Time Dimension 4. Logical Schema 5. Performance Considerations 6. Choosing A Solution 7. Frequency Of Changed Data Capture 8. Constraints 9. Evaluation And Summary Of The Logical Model 9. The Physical Implementation 1. The Data Warehouse Architecture 2. Crm Applications 3. Backup Of The Data 4. Archival 5. Extraction And Load 6. Summary 10. Business Justification 1. The Incremental Approach 2. The Submission 3. Summary 11. Managing The Project 1. Introduction 2. What Are The Deliverables? 3. What Assumptions And Risks Should I Include? 4. What Sort Of Team Do I Need? 5. Summary 12. Software Products 1. Extraction, Transformation, And Loading 2. Olap 3. Query Tools 4. Data Mining 5. Campaign Management 6. Personalization 7. Metadata Tools 8. Sorts 13. The Future 1. Temporal Databases (Temporal Extensions) 2. Olap Extensions To Sql 3. Active Decision Support 4. External Data 5. Unstructured Data 6. Search Agents 7. Dss Aware Applications 14. Wine Club Temporal Classifications 15. Dot Model For The Wine Club 1. Appendix B Dot Model For The Wine Club 16. Logical Model For The Wine Club 17. Customer Attributes 1. Household And Personal Attributes 2. Behavioral Attributes 3. Financial Attributes 4. Employment Attributes 5. Interests And Hobby Attributes | |
| 520 | 3 | |a he main subject of this book is data warehousing. A data warehouse is a special kind of database that, in recent years, has attracted a great deal of interest in the information technology industry. Quite a few books have been published about data warehousing generally, but very few have focused on the design of data warehouses. There are some notable exceptions, and these will be cited in this book, which concentrates, principally, on the design aspects of data warehousing. Data warehousing is all about making information available. No one doubts the value of information, and everyone agrees that most organizations have a potential "Aladdin's Cave" of information that is locked away within their operational systems. A data warehouse can be the key that opens the door to this information. There is strong evidence to suggest that our early foray in the field of data warehousing, what I refer to as first-generation data warehouses, has not been entirely successful. As is often the case with new ideas, especially in the information technology (IT) industry, the IT practitioners were quick to spot the potential, and they tried hard to secure the competitive advantage for their organizations that the data warehouse promised. In doing so I believe two points were overlooked. The first point is that, at first sight, a data warehouse can appear to be quite a simple application. In reality it is anything but simple. Quite apart from the basic issue of sheer scale (data warehouse databases are amongst the largest on earth) and the consequent performance difficulties presented by this, the data structures are inherently more complex thantheearly pioneers of these systems realized. As a result, there was a tendency to over-simplify the design so that, although the database was simple to understand and use, many important questions could not be asked. | |
| 650 | 0 | |9 92495 |a Procesamiento electronico de datos | |
| 650 | 0 | |9 63432 |a Administracion de bases de datos | |
| 650 | 0 | |9 102093 |a Almacenamiento de datos | |
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