Michael J A Berry Poradie kníh (chronologicky)

"When Berry and Linoff wrote the first edition of Data Mining Techniques in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new edition--more than 50% new and revised-- is a significant update from the previous one, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company ..."--Publisher description

In this follow-up to their successful first book, the authors provide a case study-based guide to best practices in commercial data mining. Shifting the focus from understanding techniques to achieving business results, the emphasis is on customer relationship management. Readers will learn to apply data mining techniques to solve practical business challenges. The book begins with fundamental principles of data mining and customer relationship management, followed by a series of candid case studies from various industries such as e-commerce, banking, cataloging, retailing, and telecommunications. These cases illustrate how to formulate business problems, analyze data, evaluate results, and apply insights to similar challenges across different sectors. The authors demonstrate how to leverage data mining to enhance customer loyalty, target the right prospects, identify new markets, and recognize cross-selling opportunities both online and offline. Additionally, a companion website offers information on data mining products, service providers, conferences, courses, and full-color illustrations from the book. This resource is positioned as essential for professionals seeking to deepen their understanding and application of data mining in business contexts.