The guide to targeting and leveraging business opportunities
using big data & analytics

By leveraging big data & analytics, businesses create the
potential to better understand, manage, and strategically
exploiting the complex dynamics of customer behavior. Analytics
in a Big Data World reveals how to tap into the powerful tool
of data analytics to create a strategic advantage and identify new
business opportunities. Designed to be an accessible resource, this
essential book does not include exhaustive coverage of all
analytical techniques, instead focusing on analytics techniques
that really provide added value in business environments.

The book draws on author Bart Baesens' expertise on the topics
of big data, analytics and its applications in e.g. credit risk,
marketing, and fraud to provide a clear roadmap for organizations
that want to use data analytics to their advantage, but need a good
starting point. Baesens has conducted extensive research on big
data, analytics, customer relationship management, web analytics,
fraud detection, and credit risk management, and uses this
experience to bring clarity to a complex topic.

• Includes numerous case studies on risk management, fraud
  detection, customer relationship management, and web analytics

• Offers the results of research and the author's personal
  experience in banking, retail, and government

• Contains an overview of the visionary ideas and current
  developments on the strategic use of analytics for business

• Covers the topic of data analytics in easy-to-understand terms
  without an undo emphasis on mathematics and the minutiae of
  statistical analysis

For organizations looking to enhance their capabilities via data
analytics, this resource is the go-to reference for leveraging data
to enhance business capabilities.

Autorentext

BART BAESENS is an associate professor at KU Leuven (Belgium) and a lecturer at the University of Southampton (United Kingdom), as well as an internationally known data analytics consultant. He is a foremost researcher in the areas of web analytics, customer relationship management, and fraud detection. His findings have been published in well-known international journals including Machine Learning and Management Science. Baesens is also co-author of the book Credit Risk Management: Basic Concepts (Oxford University Press, 2008).

Klappentext
A few years ago, big data was little more than a buzzword. Today, it's a reality for every business, but only a few firms are taking advantage of the new world of information. The science of analytics is a way to get inside customers' minds and understand the complex behavioral dynamics that affect business. Analytics in a Big Data World advances the discussion of big data by moving it out of the theoretical realm and into everyday business practice. It has been said that data is the new oil—an abundant resource of great value. The difference between data and oil, as top analytics researcher Bart Baesens understands, is that everyone has data. In areas like risk management, fraud detection, and customer relationship management, the potential gains afforded by big data analytics are well worth exploring. Reading Analytics in a Big Data World is the first step in extracting the valuable information waiting in your databases. By taking a practitioner's perspective, this book shows readers how to use the latest developments and new ideas in big data to build an analytics strategy with practical applications. The mathematics and theory have already been tested, so Analytics in a Big Data World draws on case studies and action plans, rather than dwelling unnecessarily on technical details. This realistic focus makes the guide ideal for analytics professionals who want to learn the latest techniques for leveraging data to expand markets. This latest addition to the Wiley and SAS Business Series is relevant to decisions that all businesses will need to make in the coming years. As the number of practical applications for data skyrockets, learning how to extract business value from big data becomes a competitive requirement. Bart Baesens has accomplished something significant with Analytics in a Big Data World, which delivers an action-oriented guide to staying competitive using the latest analytical models.

Zusammenfassung
The guide to targeting and leveraging business opportunities using big data & analytics By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior. Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments.

The book draws on author Bart Baesens' expertise on the topics of big data, analytics and its applications in e.g. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Baesens has conducted extensive research on big data, analytics, customer relationship management, web analytics, fraud detection, and credit risk management, and uses this experience to bring clarity to a complex topic.

• Includes numerous case studies on risk management, fraud detection, customer relationship management, and web analytics
• Offers the results of research and the author's personal experience in banking, retail, and government
• Contains an overview of the visionary ideas and current developments on the strategic use of analytics for business
• Covers the topic of data analytics in easy-to-understand terms without an undo emphasis on mathematics and the minutiae of statistical analysis
  For organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities.

Inhalt

Preface xiii

Acknowledgments xv

Chapter 1 Big Data and Analytics 1

Example Applications 2

Basic Nomenclature 4

Analytics Process Model 4

Job Profiles Involved 6

Analytics 7

Analytical Model Requirements 9

Notes 10

Chapter 2 Data Collection, Sampling, and Preprocessing 13

Types of Data Sources 13

Sampling 15

Types of Data Elements 17

Visual Data Exploration and Exploratory Statistical Analysis 17

Missing Values 19

Outlier Detection and Treatment 20

Standardizing Data 24

Categorization 24

Weights of Evidence Coding 28

Variable Selection 29

Segmentation 32

Notes 33

Chapter 3 Predictive Analytics 35

Target Definition 35

Linear Regression 38

Logistic Regression 39

Decision Trees 42

Neural Networks 48

Support Vector Machines 58

Ensemble Methods 64

Multiclass Classification Techniques 67

Evaluating Predictive Models 71

Notes 84

Chapter 4 Descriptive Analytics 87

Association Rules 87

Sequence Rules 94

Segmentation 95

Notes 104

Chapter 5 Survival Analysis 105

Survival Analysis Measurements 106

Kaplan Meier Analysis 109

Parametric Survival Analysis 111

Proportional Hazards Regression 114

Extensions of Survival Analysis Models 116

Evaluating Survival Analysis Models 117

Notes 117

Chapter 6 Social Network Analytics 119

Social Network Definitions 119

Social Network Metrics 121

Social Network Learning 123

Relational Neighbor Classifier 124

Probabilistic Relational Neighbor Classifier 125

Relational Logistic Regression 126

Collective Inferencing 128

Egonets 129

Bigraphs 130

Notes 132

Chapter 7 Analytics: Putting It All to Work 133

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