Guide to Enterprise Data Mining (Springer Professional Computing)

Data mining as a discipline and as a practice continues to grow at a tremendous rate. This book aims to introduce the underlying technology to the would-be data mining practitioner, provide a path to the delivery of a successful data mining project, and survey some of more popular data mining tools available today. The book provides the practical know-how required to deliver data mining solutions. In the first part, the technology is introduced through motivational examples that lead to an understanding of why a technique is useful in data mining and how to employ that technique. Part two draws on the commercial experiences of the authors and many years of interaction with the data mining community. Case studies reveal how to proceed through the major steps of a data mining project, and topics are discussed, such as data preparation, cleaning, preprocessing, feature selection, and results evaluation. In the final part, the Data Miner's Catalogue as published on the Web in 1999 and 2000 is expanded upon and updated, and hands-on examples using key tools are presented.