Profit-driven business analytics: a practitioner's guide to transforming big data into added value
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Hoboken, New Jersey
Wiley
[2018]
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| Series: | Wiley & SAS business series
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis Klappentext |
| Physical Description: | xvii, 398 Seiten Diagramme |
| ISBN: | 9781119286554 |
Staff View
MARC
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Record in the Search Index
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| adam_text | Contents
Foreword xv
Acknowledgments xvii
Chapter 1 A Value-Centric Perspective Towards Analytics 1
Introduction 1
Business Analytics 3
Profit-Driven Business Analytics 9
Analytics Process Model 14
Analytical Model Evaluation 17
Analytics Team 19
Profiles 19
Data Scientists 20
Conclusion 23
Review Questions 24
Multiple Choice Questions 24
Open Questions 25
References 25
Chapter 2 Analytical Techniques 28
Introduction 28
Data Preprocessing 29
Denormalizing Data for Analysis 29
Sampling 30
Exploratory Analysis 31
Missing Values 31
Outlier Detection and Handling 32
Principal Component Analysis 33
Types of Analytics 37
Predictive Analytics 37
Introduction 37
Linear Regression 38
Logistic Regression 39
Decision Trees 45
Neural Networks 52
ix
X ^CONTENTS
Ensemble Methods 56
Bagging 57
Boosting 57
Random Forests 58
Evaluating Ensemble Methods 59
Evaluating Predictive Models 59
Splitting Up the Dataset 59
Performance Measures for Classification Models 63
Performance Measures for Regression Models 67
Other Performance Measures for Predictive Analytical
Models 68
Descriptive Analytics 69
Introduction 69
Association Rules 69
Sequence Rules 72
Clustering 74
Survival Analysis 81
Introduction 81
Survival Analysis Measurements 83
Kaplan Meier Analysis 85
Parametric Survival Analysis 87
Proportional Hazards Regression 90
Extensions of Survival Analysis Models 92
Evaluating Survival Analysis Models 93
Social Network Analytics 93
Introduction 93
Social Network Definitions 94
Social Network Metrics 95
Social Network Learning 97
Relational Neighbor Classifier 98
Probabilistic Relational Neighbor Classifier 99
Relational Logistic Regression 100
Collective Inferencing 102
Conclusion 102
Review Questions 103
Multiple Choice Questions 103
Open Questions 108
Notes 110
References 110
Chapter 3 Business Applications 114
Introduction 114
Marketing Analytics 114
Introduction 114
CONTENTS ^ Xi
RFM Analysis 115
Response Modeling 116
Churn Prediction 118
X-selling 120
Customer Segmentation 121
Customer Lifetime Value 123
Customer Journey 129
Recommender Systems 131
Fraud Analytics 134
Credit Risk Analytics 139
HR Analytics 141
Conclusion 146
Review Questions 146
Multiple Choice Questions 146
Open Questions 150
Note 151
References 151
Chapter 4 Uplift Modeling 154
Introduction 154
The Case for Uplift Modeling: Response Modeling
Effects of a Treatment 158
Experimental Design, Data Collection, and Data
Preprocessing 161
Experimental Design 161
Campaign Measurement of Model Effectiveness
Uplift Modeling Methods 170
Two-Model Approach 172
Regression-Based Approaches 174
Tree-Based Approaches 183
Ensembles 193
Continuous or Ordered Outcomes 198
Evaluation of Uplift Models 199
Visual Evaluation Approaches 200
Performance Metrics 207
Practical Guidelines 210
Two-Step Approach for Developing Uplift Models
Implementations and Software 212
Conclusion 213
Review Questions 214
Multiple Choice Questions 214
Open Questions 216
Note 217
References 217
155
164
210
xii ►contents
Chapter 5 Profit-Driven Analytical Techniques 220
Introduction 220
Profit-Driven Predictive Analytics 221
The Case for Profit-Driven Predictive Analytics 221
Cost Matrix 222
Cost-Sensitive Decision Making with Cost-Insensitive
Classification Models 228
Cost-Sensitive Classification Framework 231
Cost-Sensitive Classification 234
Pre-Training Methods 235
During-Training Methods 247
Post-Training Methods 253
Evaluation of Cost-Sensitive Classification Models 255
Imbalanced Class Distribution 256
Implementations 259
Cost-Sensitive Regression 259
The Case for Profit-Driven Regression 259
Cost-Sensitive Learning for Regression 260
During Training Methods 260
Post-Training Methods 261
Profit-Driven Descriptive Analytics 267
Profit-Driven Segmentation 267
Profit-Driven Association Rules 280
Conclusion 283
Review Questions 284
Multiple Choice Questions 284
Open Questions 289
Notes 290
References 291
Chapter 6 Profit-Driven Model Evaluation
and implementation 296
Introduction 296
Profit-Driven Evaluation of Classification Models 298
Average Misclassification Cost 298
Cutoff Point Tuning 303
ROC Curve-Based Measures 310
Profit-Driven Evaluation with Observation-Dependent
Costs 334
Profit-Driven Evaluation of Regression Models 338
Loss Functions and Error-Based Evaluation Measures 339
REC Curve and Surface 341
Conclusion 345
CONTENTS « XÜi
Review Questions 347
Multiple Choice Questions 347
Open Questions 350
Notes 351
References 352
Chapter 7 Economie Impact 355
Introduction 355
Economie Value of Big Data and Analytics 355
Total Cost of Ownership (TCO) 355
Return on Investment (ROI) 357
Profit-Driven Business Analytics 359
Key Economic Considerations 359
In-Sourcing versus Outsourcing 359
On Premise versus the Cloud 361
Open-Source versus Commercial Software 362
Improving the ROI of Big Data and Analytics 364
New Sources of Data 364
Data Quality 367
Management Support 369
Organizational Aspects 370
Cross-Fertilization 371
Conclusion 372
Review Questions 373
Multiple Choice Questions 373
Open Questions 376
Notes 377
References 377
About the Authors 378
index 381
Profit Driven Business Analytics details a progressive value-centric
strategy for using analytics to heighten the accuracy of your business
decisions and skyrocket your bottom line. Based on the authorial
team’s worldwide consulting experience and high-quality research,
this step-by-step guide opens up a road map to handling data,
optimizing data analytics for specific companies, and continuously
evaluating and improving the entire process. Written to give leadership
teams the tools and know-how to transform their organizations into
forward-edge mechanisms of profitable analytics, this complete,
practical approach enables you to:
Customize the latest analytical business solutions into a reliable
system for creating real, value-increasing insight into every part
of an organization
Gain a real-world perspective on advanced analytics through
illustrative case studies and online access to practice materials
and tools
Confidently roll out the covered methodology at any company,
from conception through ongoing management-including tips
for hiring a data scientist
See the dollar signs in your data with Profit Driven Business Analytics.
|
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| spelling | Verbeke, Wouter 1983- Verfasser (DE-588)1082577898 aut Profit-driven business analytics a practitioner's guide to transforming big data into added value Wouter Verbeke, Bart Baesens, Cristián Bravo Hoboken, New Jersey Wiley [2018] xvii, 398 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier Wiley & SAS business series Management / Statistical methods Management / Data processing Big data Value added Strategic planning Big Data (DE-588)4802620-7 gnd rswk-swf Data Mining (DE-588)4428654-5 gnd rswk-swf Business Intelligence (DE-588)4588307-5 gnd rswk-swf Data Mining (DE-588)4428654-5 s Big Data (DE-588)4802620-7 s Business Intelligence (DE-588)4588307-5 s DE-604 Baesens, Bart 1975- Verfasser (DE-588)136707467 aut Bravo, Cristián Verfasser aut Erscheint auch als Online-Ausgabe, ePDF 978-1-119-44317-9 Erscheint auch als Online-Ausgabe, ePub 978-1-119-28698-1 Digitalisierung UB Augsburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030122976&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Augsburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030122976&sequence=000002&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Verbeke, Wouter 1983- Baesens, Bart 1975- Bravo, Cristián Profit-driven business analytics a practitioner's guide to transforming big data into added value Management / Statistical methods Management / Data processing Big data Value added Strategic planning Big Data (DE-588)4802620-7 gnd Data Mining (DE-588)4428654-5 gnd Business Intelligence (DE-588)4588307-5 gnd |
| subject_GND | (DE-588)4802620-7 (DE-588)4428654-5 (DE-588)4588307-5 |
| title | Profit-driven business analytics a practitioner's guide to transforming big data into added value |
| title_auth | Profit-driven business analytics a practitioner's guide to transforming big data into added value |
| title_exact_search | Profit-driven business analytics a practitioner's guide to transforming big data into added value |
| title_full | Profit-driven business analytics a practitioner's guide to transforming big data into added value Wouter Verbeke, Bart Baesens, Cristián Bravo |
| title_fullStr | Profit-driven business analytics a practitioner's guide to transforming big data into added value Wouter Verbeke, Bart Baesens, Cristián Bravo |
| title_full_unstemmed | Profit-driven business analytics a practitioner's guide to transforming big data into added value Wouter Verbeke, Bart Baesens, Cristián Bravo |
| title_short | Profit-driven business analytics |
| title_sort | profit driven business analytics a practitioner s guide to transforming big data into added value |
| title_sub | a practitioner's guide to transforming big data into added value |
| topic | Management / Statistical methods Management / Data processing Big data Value added Strategic planning Big Data (DE-588)4802620-7 gnd Data Mining (DE-588)4428654-5 gnd Business Intelligence (DE-588)4588307-5 gnd |
| topic_facet | Management / Statistical methods Management / Data processing Big data Value added Strategic planning Big Data Data Mining Business Intelligence |
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