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 Surviv…