Data mining as a discipline is largely transparent to the world. Most of the time, we never even notice that it’s happening. But whenever we sign up for a grocery store shopping card, place a purchase using a credit card, or surf the Web, we are creating data. These data are stored in large sets on powerful computers owned by the companies we deal with every day. Lying within those data sets are patterns—indicators of our interests, our habits, and our behaviors. Data mining allows people to locate and interpret those patterns, helping them make better informed decisions and better serve their customers. That being said, there are also concerns about the practice of data mining. Privacy watchdog groups in particular are vocal about organizations that amass vast quantities of data, some of which can be very personal in nature.

The intent of this book is to introduce you to concepts and practices common in data mining. It is intended primarily for undergraduate college students and for business professionals who may be interested in using information systems and technologies to solve business problems by mining data, but who likely do not have a formal background or education in computer science. Although data mining is the fusion of applied statistics, logic, artificial intelligence, machine learning and data management systems, you are not required to have a strong background in these fields to use this book. While having taken introductory college-level courses in statistics and databases will be helpful, care has been taken to explain within this book, the necessary concepts and techniques required to successfully learn how to mine data.