Implementing analytics: a blueprint for design, development, and adoption

Front Cover......Page 1
Implementing Analytics......Page 4
Copyright Page......Page 5
Contents......Page 6
Acknowledgments......Page 12
Author Biography......Page 14
Introduction......Page 16
Part 1......Page 19
Part 2......Page 20
Part 3......Page 21
Audience......Page 22
1 Concept......Page 24
The Hype......Page 26
The Challenge of Definition......Page 27
Definition 1: Business Value Perspective......Page 28
Definition 2: Technical Implementation Perspective......Page 29
Analytics Techniques......Page 30
Algorithm versus Analytics Model......Page 31
Forecasting......Page 32
Clustering......Page 34
Predictive Analytics......Page 36
Prediction Methods......Page 37
Data Mining or Machine Learning......Page 38
Text Mining......Page 40
Decision Optimization......Page 41
Conclusion of Definition......Page 43
2 Information Continuum......Page 44
Building Blocks of the Information Continuum......Page 45
Theoretical Foundation in Data Sciences......Page 46
Skilled Human Resources......Page 47
Information Continuum Levels......Page 48
Search and Lookup......Page 49
Counts and Lists......Page 50
Operational Reporting......Page 51
Summary Reporting......Page 52
Historical (Snapshot) Reporting......Page 53
Metrics, KPIs, and Thresholds......Page 54
Implementation......Page 55
Analytical Applications......Page 56
Challenges......Page 57
Analytics Models......Page 58
Decision Strategies......Page 59
Monitoring and Tuning—Governance......Page 61
Summary......Page 63
3 Using Analytics......Page 64
Analytics Solution......Page 65
Analytics Solution......Page 66
Analytics Solution......Page 67
Analytics Solution......Page 68
Analytics Solution......Page 69
Analytics Solution......Page 70
Consumer Risk......Page 71
Insurance......Page 72
Analytics Solution......Page 73
Higher Education......Page 74
Manufacturing......Page 75
Analytics Solution......Page 76
Energy and Utilities......Page 77
The New Power Management Challenge......Page 78
Analytics Solution......Page 79
Credit Card Fraud......Page 80
Patterns of Problems......Page 81
Performance or Derived Variables......Page 82
2 Design......Page 84
Performance Variables......Page 86
What are Performance Variables?......Page 87
Reasons for Creating Performance Variables......Page 88
What If No Pattern is Reliably Available?......Page 90
Benefit of Using Performance Variables......Page 91
Range......Page 92
Discrete versus Continuous......Page 93
Nominal versus Ordinal......Page 95
Working Example......Page 96
Model and Characteristics in Predictive Modeling......Page 98
Model and Characteristics in Descriptive Modeling......Page 101
Predictive Model Validation......Page 102
Validation Approaches: Parallel Run......Page 104
Champion–Challenger: A Culture of Constant Innovation......Page 105
Decision Strategy......Page 108
Expert Business Rules......Page 110
Decision Automation and Business Rules......Page 111
Retail Bank......Page 112
Insurance Claims......Page 114
Decision Strategy in Descriptive Models......Page 115
Learning versus Applying......Page 117
ETL to the Rescue......Page 119
Reprocessing......Page 120
Business Process Innovation......Page 121
Analytics and Automated Decisions......Page 124
Monitoring Layer......Page 125
Organization and Process......Page 126
Audit Datamart......Page 127
Unique Features of Audit Datamart......Page 128
Control Definition......Page 129
Expert Controls......Page 130
Reporting and Action......Page 131
3 Implementation......Page 134
Lesson 1: Simplification......Page 136
Lesson 3: Evangelize......Page 137
Lesson 6: Data Management......Page 138
Business Problem......Page 140
Management Attention and Champion......Page 141
The Project......Page 142
Existing Technology......Page 143
Existing Skills......Page 144
ETL Design, Development, and Execution......Page 145
Metadata Management and Data Governance......Page 146
Reporting and Analysis......Page 147
Problem Statement......Page 148
Data and Value......Page 149
Wider Adoption......Page 150
Requirements: Historical Perspective......Page 152
Calculations......Page 153
Analytical and Reporting Systems......Page 155
Analytics and Decision Strategy......Page 156
Requirements Extraction......Page 157
Problem Statement and Goal......Page 158
Working Example from Consumer Credit......Page 160
Data Requirements......Page 162
Data Requirements Methodology......Page 164
Model and Decision Strategy Requirements......Page 165
Business Process Integration Requirements......Page 167
9 Analytics Implementation Methodology......Page 170
Centralized Approach......Page 171
Building on the Data Warehouse......Page 172
Methodology......Page 174
Requirements......Page 175
Profiling and Data—Analysis......Page 176
Syntactic Profiling......Page 177
Model and Decision Strategy—Analysis......Page 179
Operational Integration—Analysis......Page 180
Data Warehouse Extension......Page 181
Base Variables......Page 182
Model Characteristics......Page 183
Decision Strategy......Page 184
Strategy Firing Event......Page 185
Analytics Governance—Audit and Control......Page 186
Implementation......Page 187
Execution and Monitoring......Page 188
Organizational Structure......Page 190
BICC Organization Chart......Page 191
ETL......Page 193
Data Architecture......Page 194
Analytics Modeling......Page 195
Analytics Technology......Page 196
Information Delivery......Page 197
Analytics Specialist......Page 198
Analytics Datamart......Page 199
Base Analytics Data......Page 200
Performance Variables......Page 203
Third-Party Variables......Page 204
Model and Characteristics......Page 205
Model Execution, Audit, and Control......Page 206
Big Data......Page 208
Velocity......Page 209
Volume......Page 210
Controlling the Size......Page 211
Hadoop Technology Stack......Page 212
Hadoop Data Store......Page 213
Hadoop Solution Architecture......Page 214
Hadoop as an ETL Engine......Page 215
Hadoop as an Analytical Engine......Page 216
Big Data and Hadoop—Working Example......Page 217
Disintegration in Cloud Computing......Page 219
Analytics in Cloud Computing......Page 220
Objective 1: Simplification......Page 222
Objective 3: Democratization......Page 223
Objective 4: Innovation......Page 224
References......Page 226
Index......Page 230