Business Intelligence: A Managerial Approach

Cover......Page 1
Contents......Page 10
Preface......Page 16
Chapter 1 Introduction to Business Intelligence......Page 24
 Opening Vignette: Norfolk Southern Uses Business Intelligence for Decision Support to Reach Success......Page 25
  The Business Pressures–Responses–Support Model......Page 27
  Definitions of BI......Page 29
  A Brief History of BI......Page 30
  The Architecture of BI......Page 31
  The Benefits of BI......Page 33
  Event-Driven Alerts......Page 36
  A Cyclical Process of Intelligence Creation and Use......Page 37
 1.4 Transaction Processing versus Analytic Processing......Page 38
  The Typical BI User Community......Page 39
  Appropriate Planning and Alignment with the Business Strategy......Page 40
  Justification and Cost–Benefit Analysis......Page 41
  Selected BI Vendors......Page 42
 1.7 Plan of the Book......Page 43
  Cases......Page 44
 Chapter Highlights......Page 45
 Exercises......Page 46
 End of Chapter Application Case......Page 47
 References......Page 48
Chapter 2 Data Warehousing......Page 50
 Opening Vignette: DirecTV Thrives with Active Data Warehousing......Page 51
  Characteristics of Data Warehousing......Page 53
  Operational Data Stores (ODS)......Page 54
  Enterprise Data Warehouses (EDWs)......Page 55
  Metadata......Page 56
 2.2 Data Warehousing Process Overview......Page 57
 2.3 Data Warehousing Architectures......Page 59
  Alternative Data Warehousing Architectures......Page 62
  Which Architecture Is the Best?......Page 64
  Data Integration......Page 66
  Extraction, Transformation, and Load (ETL)......Page 68
 2.5 Data Warehouse Development......Page 70
  Data Warehouse Development Approaches......Page 73
  Additional Data Warehouse Development Considerations......Page 75
  Representation of Data in Data Warehouse......Page 76
  Analysis of Data in Data Warehouse......Page 77
  OLAP Operations......Page 78
 2.6 Data Warehousing Implementation Issues......Page 81
  Massive Data Warehouses and Scalability......Page 85
 2.7 Real-Time Data Warehousing......Page 86
 2.8 Data Warehouse Administration, Security Issues, and Future Trends......Page 91
  The Future of Data Warehousing......Page 92
  Periodicals......Page 94
 Chapter Highlights......Page 95
 Exercises......Page 96
 End of Chapter Application Case......Page 98
 References......Page 99
Chapter 3 Business Performance Management......Page 102
 Opening Vignette: Double Down at Harrah’s......Page 103
  BPM and BI Compared......Page 106
  Strategic Planning......Page 108
  The Strategy Gap......Page 109
  Operational Planning......Page 110
  Financial Planning and Budgeting......Page 111
  Diagnostic Control Systems......Page 112
  Pitfalls of Variance Analysis......Page 113
 3.5 Act and Adjust: What Do We Need to Do Differently?......Page 116
  KPIs and Operational Metrics......Page 118
  Problems with Existing Performance Measurement Systems......Page 119
  Effective Performance Measurement......Page 121
  Balanced Scorecard (BSC)......Page 124
  Six Sigma......Page 127
  BPM Architecture......Page 133
  Commercial BPM Suites......Page 135
  BPM Market versus the BI Platform Market......Page 136
  Dashboards versus Scorecards......Page 138
  Dashboard Design......Page 139
  Data Visualization......Page 140
 Chapter Highlights......Page 143
 Questions for Discussion......Page 144
 Exercises......Page 145
 End of Chapter Application Case......Page 146
 References......Page 148
Chapter 4 Data Mining for Business Intelligence......Page 152
 Opening Vignette: Data Mining Goes to Hollywood!......Page 153
 4.1 Data Mining Concepts and Definitions......Page 156
  Definitions, Characteristics, and Benefits......Page 158
  How Data Mining Works......Page 162
 4.2 Data Mining Applications......Page 166
 4.3 Data Mining Process......Page 169
  Step 1: Business Understanding......Page 170
  Step 3: Data Preparation......Page 171
  Step 4: Modeling Building......Page 173
  Step 6: Deployment......Page 175
  Other Data Mining Standardized Processes and Methodologies......Page 177
 4.4 Data Mining Methods......Page 178
  Estimating the True Accuracy of Classification Models......Page 179
  Cluster Analysis for Data Mining......Page 185
  Association Rule Mining......Page 187
 4.5 Artificial Neural Networks for Data Mining......Page 190
  Elements of ANN......Page 191
  Applications of ANN......Page 193
 4.6 Data Mining Software Tools......Page 195
 4.7 Data Mining Myths and Blunders......Page 200
 Chapter Highlights......Page 201
 Key Terms......Page 202
 Exercises......Page 203
 End of Chapter Application Case......Page 206
 References......Page 207
Chapter 5 Text and Web Mining......Page 210
 Opening Vignette: Mining Text for Security and Counterterrorism......Page 211
 5.1 Text Mining Concepts and Definitions......Page 213
 5.2 Natural Language Processing......Page 216
  Security Applications......Page 221
  Biomedical Applications......Page 224
  Academic Applications......Page 226
 5.4 Text Mining Process......Page 227
  Task 1: Establish the Corpus......Page 228
  Task 2: Create the Term–Document Matrix......Page 229
  Task 3: Extract the Knowledge......Page 231
  Commercial Software Tools......Page 236
 5.6 Web Mining Overview......Page 237
 5.7 Web Content Mining and Web Structure Mining......Page 239
 5.8 Web Usage Mining......Page 241
 5.9 Web Mining Success Stories......Page 243
 Key Terms......Page 247
 Exercises......Page 248
 End of Chapter Application Case......Page 249
 References......Page 250
Chapter 6 Business Intelligence Implementation: Integration and Emerging Trends......Page 252
 Opening Vignette: BI Eastern Mountain Sports Increases Collaboration and Productivity......Page 253
  BI Implementations Factors......Page 256
  Managerial Issues Related to BI Implementation......Page 257
  Why Integrate?......Page 259
  Embedded Intelligent Systems......Page 260
  Integrating BI Applications and Back-End Systems......Page 261
  Middleware......Page 262
 6.4 On-Demand BI......Page 263
  Key Characteristics and Benefits......Page 264
  Privacy......Page 266
  Ethics in Decision Making and Support......Page 268
 6.7 The Web 2.0 Revolution......Page 269
  Web 2.0 Companies and New Business Models......Page 270
  A Definition and Basic Information......Page 271
  Major Social Network Services: Facebook and Orkut......Page 272
  Implications of Business and Enterprise Social Networks......Page 273
 6.9 Virtual Worlds......Page 276
 6.10 Social Networks and BI: Collaborative Decision Making......Page 280
  Collaboration in Virtual Teams’ Decision Making......Page 281
 6.11 RFID and New BI Application Opportunities......Page 283
 6.12 Reality Mining......Page 287
 Exercises......Page 290
 References......Page 292
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