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