Catalogue


Data mining : building competitive advantage /
Robert Groth.
imprint
Upper Saddle River, N.J. : Prentice Hall PTR, c2000.
description
xxvi, 299 p. : ill. ; 25 cm. + 1 computer laser optical disc (4 3/4 in.)
ISBN
0130862711
format(s)
Book
Holdings
Subjects
subject
More Details
imprint
Upper Saddle River, N.J. : Prentice Hall PTR, c2000.
isbn
0130862711
catalogue key
4289033
 
Includes bibliographical references (p. 259-260) and index.
A Look Inside
About the Author
Author Affiliation
Robert Groth has worked in the high tech arena for over 14 years and has consulted for many Fortune 500 companies on large-scale data mining projects.
Excerpts
Introduction or Preface
Preface In the two short years since the first version of this book was published, the data-mining industry has progressed at nothing short of light speed. Just look at a few of the more significant events: SAS Institute releases Enterprise Miner. SPSS buys ISL and their Clementine data-mining software. Yahoo! buys HyperParallel, Inc. Aspen Technologies buys NeuralWorks. Oracle Corporation buys Thinking Machines. Many data mining vendors, like DataMind, remake themselves to apply data mining to industry applications. Version One of this book emphasized all the attention data mining has recently received, citing many sources such as an article in Bank Systems & Technology, January 1996, which stated: "Data mining is the most important application in financial services in 1996." In a 1996 commercial by IBM, played during the SuperBowl, fashion models discuss the use and advantages of data mining. Finally, there was a graph from the META Group projecting the data-mining market to be a $800 million dollar market by the year 2000. Data mining is still gaining momentum and the players are rapidly changing. A second version of this book was needed to update discussions on current players and industry trends. For example, there is a major push in today''s industry to change from a tools-oriented focus to a more solution-oriented focus. This version of the book greatly expands on how data mining solves business problems. You the reader want to understand not only the current trends in the industry, but also what data mining is and how it can be applied to provide competitive advantage. META Group made the comment: "The majority of global 2000 organizations will find data-mining technologies to be critical to their business success by the year 2000." While this is interesting, there are specific reasons why this statement is true. The burning questions you should be asking are: Why are global 2000 organizations finding data mining to be "critical"? What are the benefits of data mining, both to me and my business? How do I make the most of data mining? The Purpose of This Book This text, Data Mining: Building Competitive Advantage, resulted from the revelation that data mining is becoming mainstream and that there are few books about data mining devoted to the business professional. It provides an innovative, easy approach to learning data mining for business professionals, students, and consultants. The CD-ROM at the back of the book makes learning data mining a hands-on activity. You can try out different software packages available for data mining and learn how these tools are being used to solve industry problems. This book focuses on how knowledge discovery is used in different industries, and discusses several of the data-mining software products available. Sample studies are provided for specific industries, including retail, banking, insurance, and healthcare. This text takes a different approach to introducing data mining than the academic books currently on the market. The focus of this book is on industry applications, discussions of specific business problems, and a hands-on teaching style to demonstrate how tools can be used to attain business benefit. This book provides answers to the following basic questions: What is data mining? How is data mining used in industry today? Why use data mining? Which vendors are in the data-mining market? Where do you go to find information on data mining? How do you data mine? Industry Focus Data mining is an evolving field, with great variety in terminology and methodology. To gain a reasonable understanding of data mining, you should have a broad perspective on how it is being used within the industry today. Data-mining tools currently on the market are also discussed, as well as how to get more information on the vendors and Web sites available to you. This book covers industry applications of data mining in various industries, including: banking and finance retail and marketing telecommunications healthcare This book broadens the scope of what is relevant to learning data mining. Not only should you learn the methodology and terminology needed to use data mining, you should also learn specific examples of how to achieve fast results in the corporate environment. You never hear as much as you should about industry solutions of data mining. Most companies are reluctant to discuss findings that lead to dramatic returns on investment, for competitive reasons. Industry applications making use of data-mining technology drive competitive advantage. People use data-mining technology to predict outcomes: which customers are likely to respond to specific marketing campaigns, claims that are fraudulent, or products customers are most likely to buy. The more success a company has in predicting such outcomes, the more tight-lipped they are prone to become. Hands-On Teaching Style This book also provides a hands-on approach to learning data mining. By devoting three hours of your time, you can use the enclosed CD-ROM to familiarize yourself with data mining''s major processes. Once we cover the concepts of data mining, we''ll go directly to exercises that show the ease of turning data into information. The CD-ROM contains demonstrations of two data-mining tools: Angoss KnowledgeSeekerTM, and RightPoint Software''s DataCruncher. Audience This book gives a general overview of data mining and is written for a broad-based audience. The book will be useful to: Business Professionals Anyone in business who deals with large amounts of data should consider the data-mining tools and applications described in this book. Effort is made to provide industry examples as well as to make the use of data-mining products understandable. Database Administrators (DBAs) Database administrators should be interested in this book, since it explains how end users can extract data from relational databases and data warehouses in order to mine data. Sample data structures are described for different industries. The data fields used in different types of data-mining studies are also discussed in detail. Marketing Analysts Data mining is especially useful to marketing organizations, because it allows them to profile customers to a previously unavailable level. Some people refer to this as "one-to-one" marketing. In general, today''s distributors of mass mailings use data-mining tools. In several years, data mining will be a mandatory strategic requirement of marketing organizations. Students Students who desire a practical introduction to the basics of data mining and the current market can start with this book. Systems Analysts and Consultants Consultants can benefit from the discussions of the vendors involved and by industry-specific examples. Scope of This Book Data Mining: Building Competitive Advantagedoes not include detailed explanations of the algorithms used with data mining. If you want to learn more about the algorithms, I would suggest Advances in Knowledge Discovery and Data Mining, by Usama M. Fayyad, Gregory Piatestsky-Shapiro, Padhraic Smyth, and Ramasamy Uthurusam. This book, at over 550 pages, is the most comprehensive work available today on the technical approaches used in data mining. This book is devoted to the business professional and targets an audience of professionals who do not necessarily have a statistics background and who want to learn about data-mining applications, or who wish to attempt data mining. Organization of This Book Data Mining
Introduction or Preface
Preface In the two short years since the first version of this book was published, the data-mining industry has progressed at nothing short of light speed. Just look at a few of the more significant events: SAS Institute releases Enterprise Miner. SPSS buys ISL and their Clementine data-mining software. Yahoo! buys HyperParallel, Inc. Aspen Technologies buys NeuralWorks. Oracle Corporation buys Thinking Machines. Many data mining vendors, like DataMind, remake themselves to apply data mining to industry applications. Version One of this book emphasized all the attention data mining has recently received, citing many sources such as an article in Bank Systems & Technology, January 1996, which stated: "Data mining is the most important application in financial services in 1996." In a 1996 commercial by IBM, played during the SuperBowl, fashion models discuss the use and advantages of data mining. Finally, there was a graph from the META Group projecting the data-mining market to be a $800 million dollar market by the year 2000. Data mining is still gaining momentum and the players are rapidly changing. A second version of this book was needed to update discussions on current players and industry trends. For example, there is a major push in today's industry to change from a tools-oriented focus to a more solution-oriented focus. This version of the book greatly expands on how data mining solves business problems. You the reader want to understand not only the current trends in the industry, but also what data mining is and how it can be applied to provide competitive advantage. META Group made the comment: "The majority of global 2000 organizations will find data-mining technologies to be critical to their business success by the year 2000." While this is interesting, there are specific reasons why this statement is true. The burning questions you should be asking are: Why are global 2000 organizations finding data mining to be "critical"? What are the benefits of data mining, both to me and my business? How do I make the most of data mining? The Purpose of This Book This text,Data Mining: Building Competitive Advantage, resulted from the revelation that data mining is becoming mainstream and that there are few books about data mining devoted to the business professional. It provides an innovative, easy approach to learning data mining for business professionals, students, and consultants. The CD-ROM at the back of the book makes learning data mining a hands-on activity. You can try out different software packages available for data mining and learn how these tools are being used to solve industry problems. This book focuses on how knowledge discovery is used in different industries, and discusses several of the data-mining software products available. Sample studies are provided for specific industries, including retail, banking, insurance, and healthcare. This text takes a different approach to introducing data mining than the academic books currently on the market. The focus of this book is on industry applications, discussions of specific business problems, and a hands-on teaching style to demonstrate how tools can be used to attain business benefit. This book provides answers to the following basic questions: What is data mining? How is data mining used in industry today? Why use data mining? Which vendors are in the data-mining market? Where do you go to find information on data mining? How do you data mine? Industry Focus Data mining is an evolving field, with great variety in terminology and methodology. To gain a reasonable understanding of data mining, you should have a broad perspective on how it is being used within the industry today. Data-mining tools currently on the market are also discussed, as well as how to
Introduction or Preface
PrefaceIn the two short years since the first version of this book was published, the data-mining industry has progressed at nothing short of light speed. Just look at a few of the more significant events: SAS Institute releases Enterprise Miner. SPSS buys ISL and their Clementine data-mining software. Yahoo! buys HyperParallel, Inc. Aspen Technologies buys NeuralWorks. Oracle Corporation buys Thinking Machines. Many data mining vendors, like DataMind, remake themselves to apply data mining to industry applications.Version One of this book emphasized all the attention data mining has recently received, citing many sources such as an article in Bank Systems & Technology, January 1996, which stated: "Data mining is the most important application in financial services in 1996." In a 1996 commercial by IBM, played during the SuperBowl, fashion models discuss the use and advantages of data mining. Finally, there was a graph from the META Group projecting the data-mining market to be a $800 million dollar market by the year 2000.Data mining is still gaining momentum and the players are rapidly changing. A second version of this book was needed to update discussions on current players and industry trends. For example, there is a major push in today's industry to change from a tools-oriented focus to a more solution-oriented focus.This version of the book greatly expands on how data mining solves business problems. You the reader want to understand not only the current trends in the industry, but also what data mining is and how it can be applied to provide competitive advantage. META Group made the comment: "The majority of global 2000 organizations will find data-mining technologies to be critical to their business success by the year 2000." While this is interesting, there are specific reasons why this statement is true. The burning questions you should be asking are: Why are global 2000 organizations finding data mining to be "critical"? What are the benefits of data mining, both to me and my business? How do I make the most of data mining? The Purpose of This BookThis text,Data Mining: Building Competitive Advantage, resulted from the revelation that data mining is becoming mainstream and that there are few books about data mining devoted to the business professional. It provides an innovative, easy approach to learning data mining for business professionals, students, and consultants. The CD-ROM at the back of the book makes learning data mining a hands-on activity. You can try out different software packages available for data mining and learn how these tools are being used to solve industry problems.This book focuses on how knowledge discovery is used in different industries, and discusses several of the data-mining software products available. Sample studies are provided for specific industries, including retail, banking, insurance, and healthcare.This text takes a different approach to introducing data mining than the academic books currently on the market. The focus of this book is on industry applications, discussions of specific business problems, and a hands-on teaching style to demonstrate how tools can be used to attain business benefit.This book provides answers to the following basic questions: What is data mining? How is data mining used in industry today? Why use data mining? Which vendors are in the data-mining market? Where do you go to find information on data mining? How do you data mine? Industry FocusData mining is an evolving field, with great variety in terminology and methodology. To gain a reasonable understanding of data mining, you should have a broad perspective on how it is being used within the industry today. Data-mining tools currently on the market are also discussed, as well as how to
First Chapter

Preface

In the two short years since the first version of this book was published, the data-mining industry has progressed at nothing short of light speed. Just look at a few of the more significant events:

  • SAS Institute releases Enterprise Miner.
  • SPSS buys ISL and their Clementine data-mining software.
  • Yahoo! buys HyperParallel, Inc.
  • Aspen Technologies buys NeuralWorks.
  • Oracle Corporation buys Thinking Machines.
  • Many data mining vendors, like DataMind, remake themselves to apply data mining to industry applications.

Version One of this book emphasized all the attention data mining has recently received, citing many sources such as an article in Bank Systems & Technology, January 1996, which stated: "Data mining is the most important application in financial services in 1996." In a 1996 commercial by IBM, played during the SuperBowl, fashion models discuss the use and advantages of data mining. Finally, there was a graph from the META Group projecting the data-mining market to be a $800 million dollar market by the year 2000.

Data mining is still gaining momentum and the players are rapidly changing. A second version of this book was needed to update discussions on current players and industry trends. For example, there is a major push in today's industry to change from a tools-oriented focus to a more solution-oriented focus.

This version of the book greatly expands on how data mining solves business problems. You the reader want to understand not only the current trends in the industry, but also what data mining is and how it can be applied to provide competitive advantage. META Group made the comment: "The majority of global 2000 organizations will find data-mining technologies to be critical to their business success by the year 2000." While this is interesting, there are specific reasons why this statement is true. The burning questions you should be asking are: Why are global 2000 organizations finding data mining to be "critical"? What are the benefits of data mining, both to me and my business? How do I make the most of data mining?

The Purpose of This Book

This text,Data Mining: Building Competitive Advantage, resulted from the revelation that data mining is becoming mainstream and that there are few books about data mining devoted to the business professional. It provides an innovative, easy approach to learning data mining for business professionals, students, and consultants. The CD-ROM at the back of the book makes learning data mining a hands-on activity. You can try out different software packages available for data mining and learn how these tools are being used to solve industry problems.

This book focuses on how knowledge discovery is used in different industries, and discusses several of the data-mining software products available. Sample studies are provided for specific industries, including retail, banking, insurance, and healthcare.

This text takes a different approach to introducing data mining than the academic books currently on the market. The focus of this book is on industry applications, discussions of specific business problems, and a hands-on teaching style to demonstrate how tools can be used to attain business benefit.

This book provides answers to the following basic questions:

  • What is data mining?
  • How is data mining used in industry today?
  • Why use data mining?
  • Which vendors are in the data-mining market?
  • Where do you go to find information on data mining?
  • How do you data mine?

Industry Focus

Data mining is an evolving field, with great variety in terminology and methodology. To gain a reasonable understanding of data mining, you should have a broad perspective on how it is being used within the industry today. Data-mining tools currently on the market are also discussed, as well as how to get more information on the vendors and Web sites available to you.

This book covers industry applications of data mining in various industries, including:

  • banking and finance
  • retail and marketing
  • telecommunications
  • healthcare

This book broadens the scope of what is relevant to learning data mining. Not only should you learn the methodology and terminology needed to use data mining, you should also learn specific examples of how to achieve fast results in the corporate environment.

You never hear as much as you should about industry solutions of data mining. Most companies are reluctant to discuss findings that lead to dramatic returns on investment, for competitive reasons. Industry applications making use of data-mining technology drive competitive advantage. People use data-mining technology to predict outcomes: which customers are likely to respond to specific marketing campaigns, claims that are fraudulent, or products customers are most likely to buy. The more success a company has in predicting such outcomes, the more tight-lipped they are prone to become.

Hands-On Teaching Style

This book also provides a hands-on approach to learning data mining. By devoting three hours of your time, you can use the enclosed CD-ROM to familiarize yourself with data mining's major processes.

Once we cover the concepts of data mining, we'll go directly to exercises that show the ease of turning data into information. The CD-ROM contains demonstrations of two data-mining tools: Angoss®KnowledgeSeekerTM, and RightPoint®Software's DataCruncher.

Audience

This book gives a general overview of data mining and is written for a broad-based audience. The book will be useful to:

Business Professionals

Anyone in business who deals with large amounts of data should consider the data-mining tools and applications described in this book. Effort is made to provide industry examples as well as to make the use of data-mining products understandable.

Database Administrators (DBAs)

Database administrators should be interested in this book, since it explains how end users can extract data from relational databases and data warehouses in order to mine data. Sample data structures are described for different industries. The data fields used in different types of data-mining studies are also discussed in detail.

Marketing Analysts

Data mining is especially useful to marketing organizations, because it allows them to profile customers to a previously unavailable level. Some people refer to this as "one-to-one" marketing. In general, today's distributors of mass mailings use data-mining tools. In several years, data mining will be a mandatory strategic requirement of marketing organizations.

Students

Students who desire a practical introduction to the basics of data mining and the current market can start with this book.

Systems Analysts and Consultants

Consultants can benefit from the discussions of the vendors involved and by industry-specific examples.

Scope of This Book

Data Mining: Building Competitive Advantagedoes not include detailed explanations of the algorithms used with data mining. If you want to learn more about the algorithms, I would suggestAdvances in Knowledge Discovery and Data Mining, by Usama M. Fayyad, Gregory Piatestsky-Shapiro, Padhraic Smyth, and Ramasamy Uthurusam. This book, at over 550 pages, is the most comprehensive work available today on the technical approaches used in data mining.

This book is devoted to the business professional and targets an audience of professionals who do not necessarily have a statistics background and who want to learn about data-mining applications, or who wish to attempt data mining.

Organization of This Book

Data Mining: Building Competitive Advantageis divided into three parts:

Part 1 Starting Out

The first chapters introduce data mining, discuss the data-mining process, and cover vendors involved in this market.

Chapter 1, "Introduction to Data Mining," introduces basic concepts of data mining and explains why data mining is important.

Chapter 2, "Getting Started With Data Mining," discusses several of the approaches taken in data mining and their potential benefits.

Chapter 3, "The Data-Mining Process," covers the process of data mining and introduces different types of studies as well as data-preparation issues.

Chapter 4, "Data-Mining Algorithms," discusses the types of algorithms and technologies being used today.

Chapter 5, "The Data-Mining Marketplace," introduces vendors in the data-mining market today, and includes discussion of applications such as SAS Enterprise Miner and IBM's Intelligent Miner.

Part 2 A Rapid Tutorial

Chapters 6 and 7 introduce two leading data-mining software products.

Chapter 6, "A Look at Angoss: KnowledgeSEEKER," covers the leading, commercial data-mining software product, which is based on a decision-tree model and is focused on end users. A business example for the healthcare industry is discussed.

Chapter 7, "A Look at RightPoint DataCruncher," covers an innovative commercial data-mining software product that is focused on marketing professionals. A business example for the telecommunications industry is discussed.

Part 3 Industry Focus

Chapters 8 and 9 focus on specific industry uses of data mining. Examples for each study performed are provided, with tips on how these can be performed on corporate database systems.

Chapter 8, "Industry Applications of Data Mining," looks at types of data-mining studies in banking and finance, retail, healthcare, and the telecommunications industry. Examples of companies performing data mining are provided.

Chapter 9, "Enabling Data Mining Through Data Warehouses," looks at how data warehouses provide a methodology for helping perform data-mining studies. Four data-warehouse industry examples are provided to discuss the type of data that would be integrated and introduce how some data-mining studies could be performed using these data warehouses.

CD-ROM Installation Requirements

The minimum system requirements for installing the CD-ROM included in this book are discussed in Appendix B. Each of the data-mining software products included in the CD-ROM have their own requirements.

The installed software enables you to run the CD-ROM-based tutorial included in this book. Additional files have been added specifically for this book beyond those provided by Angoss Software and RightPoint Software.

Summaries
Back Cover Copy
8627A-4"Finally, here's a book that explains in plain English what data mining is and how it's used to improve a company's bottom line . . . Groth takes a very complex and vast field and makes it comprehensible." Miguel A. Castro, Ph.D., President, Dovetail SolutionsData mining business solutions-practical, up-to-date, and hands-on!With data mining, you can achieve competitive advantage from the data you've already paid to compile. Data Mining: Building Competitive Advantage shows you how. You won't just learn the theory and concepts of data mining; you'll discover how to apply them-hands-on, through real applications!Coverage includes: Case studies in banking, finance, retail, healthcare, direct marketing, and telecommunications The data mining process, start to finish Today's newest, most successful approaches and algorithms Data mining pitfalls-and how to avoid them A close look at industry-leading tools from Angoss and RightPointWhether you're a manager, marketer, consultant, analyst, or database professional, Robert Groth will help you master data mining-and deliver all the competitive advantage it promises.About the WebsiteThe accompanying website includes full trial editions of two of the world's leading desktop data mining tools, Angoss KnowledgeSEEKER and RightPoint DataCruncher.
Bowker Data Service Summary
In recent years, data mining has moved from focusing on the specific tools available to focusing on the solutions businesses need. This book looks at the business solutions that data mining offers.
Unpaid Annotation
"Finally, here's a book that explains in plain English what data mining is and how it's used to improve a company's bottom line . . . Groth takes a very complex and vast field and makes it comprehensible." Miguel A. Castro, Ph.D., President, Dovetail Solutions Data mining business solutions-practical, up-to-date, and hands-on! With data mining, you can achieve competitive advantage from the data you've already paid to compile. Data Mining: Building Competitive Advantage shows you how. You won't just learn the theory and concepts of data mining; you'll discover how to apply them-hands-on, through real applications! Coverage includes: Case studies in banking, finance, retail, healthcare, direct marketing, and telecommunications The data mining process, start to finish Today's newest, most successful approaches and algorithms Data mining pitfalls-and how to avoid them A close look at industry-leading tools from Angoss(TM) and RightPoint(TM) Whether you're a manager, marketer, consultant, analyst, or database professional, Robert Groth will help you master data mining-and deliver all the competitive advantage it promises. About the CD-ROM The accompanying CD-ROM includes full trial editions of two of the world's leading desktop data mining tools, Angoss KnowledgeSEEKER(R) and RightPoint DataCruncher.
Back Cover Copy
8627A-4 "Finally, here's a book that explains in plain English what data mining is and how it's used to improve a company's bottom line . . . Groth takes a very complex and vast field and makes it comprehensible." Miguel A. Castro, Ph.D., President, Dovetail Solutions Data mining business solutions-practical, up-to-date, and hands-on! With data mining, you can achieve competitive advantage from the data you've already paid to compile. Data Mining: Building Competitive Advantage shows you how. You won't just learn the theory and concepts of data mining; you'll discover how to apply them-hands-on, through real applications! Coverage includes: Case studies in banking, finance, retail, healthcare, direct marketing, and telecommunications The data mining process, start to finish Today's newest, most successful approaches and algorithms Data mining pitfalls-and how to avoid them A close look at industry-leading tools from Angoss and RightPoint Whether you're a manager, marketer, consultant, analyst, or database professional, Robert Groth will help you master data mining-and deliver all the competitive advantage it promises. About the Website The accompanying website includes full trial editions of two of the world's leading desktop data mining tools, Angoss KnowledgeSEEKER and RightPoint DataCruncher.
Back Cover Copy
8627A-4 "Finally, here's a book that explains in plain English what data mining is and how it's used to improve a company's bottom line . . . Groth takes a very complex and vast field and makes it comprehensible." Miguel A. Castro, Ph.D., President, Dovetail Solutions Data mining business solutions-practical, up-to-date, and hands-on! With data mining, you can achieve competitive advantage from the data you've already paid to compile. Data Mining: Building Competitive Advantage shows you how. You won't just learn the theory and concepts of data mining; you'll discover how to apply them-hands-on, through real applications! Coverage includes: Case studies in banking, finance, retail, healthcare, direct marketing, and telecommunications The data mining process, start to finish Today's newest, most successful approaches and algorithms Data mining pitfalls-and how to avoid them A close look at industry-leading tools from Angoss and RightPoint Whether you're a manager, marketer, consultant, analyst, or database professional, Robert Groth will help you master data mining-and deliver all the competitive advantage it promises. About the Website The accompanying website includes full trial editions of two of the world's leading desktop data mining tools, Angoss KnowledgeSEEKER? and RightPoint DataCruncher.
Back Cover Copy
8627A-4"Finally, here's a book that explains in plain English what data mining is and how it's used to improve a company's bottom line . . . Groth takes a very complex and vast field and makes it comprehensible." Miguel A. Castro, Ph.D., President, Dovetail Solutions Data mining business solutions-practical, up-to-date, and hands-on! With data mining, you can achieve competitive advantage from the data you've already paid to compile. Data Mining: Building Competitive Advantage shows you how. You won't just learn the theory and concepts of data mining; you'll discover how to apply them-hands-on, through real applications! Coverage includes: Case studies in banking, finance, retail, healthcare, direct marketing, and telecommunications The data mining process, start to finish Today's newest, most successful approaches and algorithms Data mining pitfalls-and how to avoid them A close look at industry-leading tools from Angoss and RightPoint Whether you're a manager, marketer, consultant, analyst, or database professional, Robert Groth will help you master data mining-and deliver all the competitive advantage it promises. About the Website The accompanying website includes full trial editions of two of the world's leading desktop data mining tools, Angoss KnowledgeSEEKER and RightPoint DataCruncher.
Table of Contents
List of Figuresp. xv
Prefacep. xxi
The Purpose of This Bookp. xxii
Industry Focusp. xxii
Hands-On Teaching Stylep. xxiii
Audiencep. xxiii
Business Professionalsp. xxiii
Database Administrators (DBAs)p. xxiv
Marketing Analystsp. xxiv
Studentsp. xxiv
Systems Analysts and Consultantsp. xxiv
Scope of This Bookp. xxiv
Organization of This Bookp. xxiv
CD-ROM Installation Requirementsp. xxv
Acknowledgmentsp. xxvi
Starting Outp. 1
Introduction to Data Miningp. 3
What Is Data Mining?p. 3
Why Use Data Mining?p. 5
Examples of Using Data Miningp. 6
Case Studies of Implementing Data Miningp. 9
An Example of Data Mining at US WESTp. 9
An Example of Data Mining at Bass Exportp. 11
A Data-Mining Example at Reutersp. 12
A Process for Successfully Deploying Data Mining for Competitive Advantagep. 12
Problem Definitionp. 13
Discoveryp. 14
Implementationp. 15
Taking Actionp. 16
Monitoring the Resultsp. 17
Discussion of the Processp. 18
A Note on Privacy Issuesp. 19
Summaryp. 20
Getting Started with Data Miningp. 21
Classification (Supervised Learning)p. 22
Goalp. 22
Subject of the Studyp. 23
Clustering (Unsupervised Learning)p. 24
A Clustering Examplep. 25
Visualizationp. 26
Association (Market Basket)p. 28
The Trouble with Market-Basket Analysisp. 29
Assortment Optimizationp. 31
Sales Volume: Variety versus Substitutabilityp. 31
Costs: The Other Half of the Storyp. 33
Predictionp. 35
Challenger Outcomesp. 36
Margin of Victoryp. 36
Conducting a Cost Benefit Analysisp. 36
Estimationp. 38
Examples of Estimationp. 39
Summaryp. 39
The Data-Mining Processp. 41
Discussion of Data-Mining Methodologyp. 41
The SEMMA Methodology from SAS Institutep. 42
The Examplep. 44
Data Preparationp. 46
Getting at Your Datap. 47
Data-Qualification Issuesp. 50
Data-Quality Issuesp. 50
Binningp. 53
Data Derivationp. 54
Defining a Studyp. 54
Understanding Limitsp. 55
Choosing a Good Studyp. 56
Types of Studiesp. 56
What Elements to Analyze?p. 58
Issues of Samplingp. 60
Reading the Data and Building a Modelp. 61
On Accuracyp. 61
On Understandabilityp. 61
On Performancep. 62
Understanding Your Modelp. 62
Model Summarizationp. 63
Data Distributionp. 64
Validationp. 65
Predictionp. 67
Challenger Outcomesp. 68
Margin of Victoryp. 68
Understanding Why a Prediction Is Madep. 69
Summaryp. 69
Data-Mining Algorithmsp. 71
Introductionp. 72
Decision Treesp. 72
How Decision Trees Workp. 73
Strengths and Weaknesses of Decision Treesp. 74
Genetic Algorithmsp. 75
How Genetic Algorithms Workp. 75
Strengths and Weaknessesp. 76
Neural Networksp. 76
How It Worksp. 77
Different Types of Models to Build -- Unsupervised Learningp. 78
Strengths and Weaknesses of a Modelp. 79
Bayesian Belief Networksp. 80
How They Workp. 80
Strengths and Weaknesses of Bayesian Belief Networksp. 82
Statisticsp. 83
On Discriminant Analysisp. 83
On Regression Modelingp. 83
Strengths and Weaknessesp. 84
Advanced Algorithms for Associationp. 84
A Better Way of Discovery Associationsp. 85
Beyond Statistical Dependencep. 87
Understanding Associationsp. 88
Actionable and Effective MB Analysisp. 88
Algorithms for Assortment Optimizationp. 90
Cost: As Easy as ABC?p. 93
Relevant Costsp. 94
Business Goals: Bringing It All Togetherp. 95
Summaryp. 97
The Data-Mining Marketplacep. 99
Introduction (Trends)p. 99
Data Warehousing is Becoming Commonplacep. 100
Data Mining on the Internetp. 100
EIS Tool Vendors Integrating Data Miningp. 100
Information More Accessiblep. 101
Data-Mining Vendors Focusing More on Vertical Marketsp. 101
Data-Mining Vendorsp. 102
Visualizationp. 112
Examples of Data Visualizationp. 112
Vendor Listp. 115
Useful Web Sites/Commercially Available Codep. 117
Data-Mining Web Sitesp. 118
Finding Data Setsp. 118
Source Codep. 119
Data Sources for Miningp. 120
Summaryp. 123
A Rapid Tutorialp. 125
A Look at Angoss: KnowledgeSEEKERp. 127
Introductionp. 127
KnowledgeSTUDIOp. 128
KnowledgeSEEKER and Decision Treesp. 128
How Decision Trees Are Being Usedp. 128
Data Preparationp. 129
Defining the Studyp. 132
Defining the Goalp. 132
Starting Upp. 133
Setting the Dependent Variablep. 133
Building the Modelp. 134
Understanding the Modelp. 135
Looking at Different Splitsp. 135
Going to a Specific Splitp. 138
Growing the Treep. 138
Forcing a Splitp. 140
Validationp. 142
Defining a New Scenario for a Studyp. 142
Growing a Tree Automaticallyp. 143
Data Distributionp. 144
Predictionp. 145
Summaryp. 146
A Look at RightPoint DataCruncherp. 149
Introductionp. 149
RightPoint's Technologyp. 150
How RightPoint Is Being Usedp. 151
Data Preparationp. 151
Defining the Studyp. 156
Defining the Goalp. 156
Choosing a Dependent Variablep. 156
Setting Up a Studyp. 157
Starting RightPointp. 158
Setting Up Data Specificationsp. 161
Read Your Data/Build a Discovery Modelp. 170
Understanding the Modelp. 170
Evaluationp. 178
Refining the Modelp. 180
Conducting a Cost Benefit Analysisp. 182
Perform Predictionp. 185
Conducting What-If Analysesp. 185
Conducting Batch Predictionp. 187
Summaryp. 188
Industry Focusp. 189
Industry Applications of Data Miningp. 191
Data-Mining Applications in Banking and Financep. 191
Stock Forecastingp. 192
Cross-Selling and Customer Loyalty in the Banking Industryp. 193
Data-Mining Applications in Retailp. 198
An Example of Data Mining for Property Valuationp. 201
An Example of Analyzing Customer Profitability in Retailp. 203
Data-Mining Applications in Healthcarep. 204
Uses of Data Visualization in the Medical Industryp. 205
Data-Mining Applications in Telecommunicationsp. 207
Types of Studies in Telecommunicationsp. 209
Summaryp. 209
Enabling Data Mining Through Data Warehousesp. 211
Introductionp. 212
Data Acquisitionp. 213
Data Refinementp. 213
Data Warehouse Designp. 214
Data Warehouse and DataMart Implementationp. 214
A Data-Warehouse Example in Banking and Financep. 214
A Transactional Database System versus a Data Warehousep. 215
The Sample Data Modelp. 216
An Example of a Credit-Fraud Studyp. 219
An Example of a Retention-Management Studyp. 222
Data-Trends Analysisp. 227
A Data-Warehouse Example in Retailp. 227
The Sample Data Modelp. 228
What Types of Customers are Buying Different Types of Productsp. 230
An Example of Regional Studies and Othersp. 233
A Data-Warehouse Example in Healthcarep. 233
The Example Data Modelp. 233
A Look at Sample Studies in Healthcarep. 237
A Discussion on Adding Credit Data to Our Examplep. 237
A Data-Warehouse Example in Telecommunicationsp. 238
The Sample Data Modelp. 238
Data Collectionp. 241
Creating the Data Setp. 242
An Example Study on Product/Market Share Analysisp. 243
An Example Study of a Regional Market Analysisp. 244
Summaryp. 244
Data-Mining Vendorsp. 245
Data-Mining Playersp. 246
Visualization Toolsp. 249
Useful Web Sitesp. 250
Information Access Providersp. 250
Data-Warehousing Vendorsp. 252
Installing Demo Softwarep. 255
Installing Angoss KnowledgeSEEKER Demop. 255
Installing the RightPoint DataCruncher Demop. 256
Referencesp. 259
Indexp. 261
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