large samples and discrete time measurements found in marketing data. The chapter on memory-based reasoning now also includes a discussion of collaborative filtering, another technique based on nearest neighbors that has become popular with Web retailers as a way of generating recommendations.

The third part of the book talks about applying the techniques in a business context, including a chapter on finding customers in data, one on the relationship of data mining and data warehousing, another on the data mining environment (both corporate and technical), and a final chapter on putting data mining to work in an organization. A new chapter in this part covers preparing data for data mining, an extremely important topic since most data miners report that transforming data takes up the majority of time in a typical data mining project.

Like the first edition, this book is aimed at current and future data mining practitioners. It is not meant for software developers looking for detailed instructions on how to implement the various data mining algorithms nor for researchers trying to improve upon those algorithms. Ideas are presented in nontechnical language with minimal use of mathematical formulas and arcane jargon. Each data mining technique is shown in a real business context with examples of its use taken from real data mining engagements. In short, we have tried to write the book that we would have liked to read when we began our own data mining careers.

- Michael J. A. Berry, October, 2003

Contents

Acknowledgments xix

About the Authors xxi

Introduction xxiii

Chapter 1 Why and What Is Data Mining? 1

Analytic Customer Relationship Management 2

The Role of Transaction Processing Systems 3

The Role of Data Warehousing 4

The Role of Data Mining 5

The Role of the Customer Relationship Management Strategy 6

What Is Data Mining? 7

What Tasks Can Be Performed with Data Mining? 8

Classification 8

Estimation 9

Prediction 10

Affinity Grouping or Association Rules 11

Clustering 11

Profiling 12

Why Now? 12

Data Is Being Produced 12

Data Is Being Warehoused 13

Computing Power Is Affordable 13

Interest in Customer Relationship Management Is Strong 13

Every Business Is a Service Business 14

Information Is a Product 14 Commercial Data Mining Software Products

Have Become Available 15