Executive Education Institute - Data Mining

Author: Michael Berry, Gordon Linoff; Translated by Yuan Li and others
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Features: Provides concise and practical MBA solutions for tough problems faced by corporate executives, serving as a desk reference for CEOs, CFOs, CTOs, and CIOs. The series is used by the top ten business schools in the U.S.: Stanford University Graduate School of Business, Harvard Business School, The Wharton School of the University of Pennsylvania, MIT Sloan School of Management, Northwestern University Kellogg School of Management, Duke University Fuqua School of Business, University of Chicago Graduate School of Business, Columbia Business School, Dartmouth College Tuck School of Business, and UC Berkeley Haas School of Business. Data mining is the fastest-growing technology in the information field. Many different leaders and experts, such as statisticians and database specialists, have found opportunities for growth in it, making data mining an increasingly popular topic of discussion in the business world. With the development of information technology, people have become more sophisticated in collecting data, leading to a rapid accumulation of massive datasets, reaching GB or even TB levels. High-dimensional data has also become mainstream. These vast datasets and their high-dimensional characteristics make traditional data analysis methods seem inadequate. The continuous advancements in computer performance have made it possible to expect computers to assist us in analyzing and understanding data, enabling us to make informed decisions based on rich datasets.