Chapters in this book

1. Frontmatter i
2. Contents v
3. Preface xxv
4. Chapter 1 Introduction 1
5. Chapter 2 Business Intelligence Application and Future 9
6. Chapter 3 Data Warehousing Evolution and Fundamentals 15
7. Chapter 4 Data Warehouse Types and Design Objectives 19
8. Chapter 5 Growth Contributors 23
9. Chapter 6 Data Warehouse Characteristics 29
10. Chapter 7 Star Schema 35
11. Chapter 8 Data Warehouse Process 39
12. Chapter 9 Architecture 45
13. Chapter 10 Metadata 49
14. Chapter 11 Source Data 53
15. Chapter 12 Data Conversion and Migration 59
16. Chapter 13 Data Quality 65
17. Chapter 14 ETL Process 71
18. Chapter 15 ETL Issues, Tools, and ELT 79
19. Chapter 16 Data Storage 87
20. Chapter 17 Data Modeling 93
21. Chapter 18 Data Warehouse Engine and Operating System 97
22. Chapter 19 Hardware 103
23. Chapter 20 Data Access 109
24. Chapter 21 Tool Selection and Data Mining 115
25. Chapter 22 Features of Front- End Tools 121
26. Chapter 23 Data Marts 127
27. Chapter 24 Implementation Approaches 133
28. Chapter 25 Inmon versus Kimball 139
29. Chapter 26 Multidimensionality 145
30. Chapter 27 Facts and Dimensions 151
31. Chapter 28 OLAP 157
32. Chapter 29 OLAP models 161
33. Chapter 30 Multidimensional Database 165
34. Chapter 31 OLAP: Comparisons, Tools, and Vendors 169
35. Chapter 32 Planning for the Data Warehouse Initiative 175
36. Chapter 33 Implementation Prerequisites and Approach 183
37. Chapter 34 Common Mistakes and Risks 189
38. Chapter 35 Project Resources 195
39. Chapter 36 Project Definition and Initiation 203
40. Chapter 37 Project Planning 209
41. Chapter 38 Analysis 217
42. Chapter 39 Analysis: Additional Topics 225
43. Chapter 40 Design 231
44. Chapter 41 Design: Data Modeling and OLAP Design 239
45. Chapter 42 Design: Additional Topics 245
46. Chapter 43 Documentation 253
47. Chapter 44 Development 261
48. Chapter 45 Testing and Training 267
49. Chapter 46 Deployment and Operation 275
50. Chapter 47 Trends 281
51. Index 287