Language : English
Published : 2009-01-09
Pages : 408
Green to Gold
From the Publishers Weekly review: “Two experts from Yale tackle the business wake-up-call du jour-environmental responsibility-from every angle in this thorough, earnest guidebook: pragmatically, passionately, financially and historically. Though “no company the authors know of is on a truly long-term sustainable course,” Esty and Winston label the forward-thinking, green-friendly (or at least green-acquainted) companies WaveMakers and set out to assess honestly their path toward environmental responsibility, and its impact on a company’s bottom line, customers, suppliers and reputation. Following the evolution of business attitudes toward environmental concerns, Esty and Winston offer a series of fascinating plays by corporations such as Wal-Mart, GE and Chiquita (Banana), the bad guys who made good, and the good guys-watchdogs and industry associations, mostly-working behind the scenes. A vast number of topics huddle beneath the umbrella of threats to the earth, and many get a thorough analysis here: from global warming to electronic waste “take-back” legislation to subsidizing sustainable seafood. For the responsible business leader, this volume provides plenty of (organic) food for thought. “
Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms. Quotes This book provides a comprehensive coverage of important data mining techniques. Numerous examples are provided to lucidly illustrate the key concepts. -Sanjay Ranka, University of Florida In my opinion this is currently the best data mining text book on the market. I like the comprehensive coverage which spans all major data mining techniques including classification, clustering, and pattern mining (association rules). -Mohammed Zaki, Rensselaer Polytechnic Institute
Praise for the Second Edition ” full of vivid and thought-provoking anecdotes…needs to be read by anyone with a serious interest in research and marketing.” Research Magazine “Shmueli et al. have done a wonderful job in presenting the field of data mining – a welcome addition to the literature.” ComputingReviews.com “Excellent choice for business analysts…The book is a perfect fit for its intended audience.” Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization ” extremely well organized, clearly written and introduces all of the basic ideas quite well.” Robert L. Phillips, Professor of Professional Practice, Columbia Business School Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft(R) Office Excel(R) add-in XLMiner(R) to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes: * Real-world examples to build a theoretical and practical understanding of key data mining methods * End-of-chapter exercises that help readers better understand the presented material * Data-rich case studies to illustrate various applications of data mining techniques * Completely new chapters on social network analysis and text mining * A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint(R) slides * Free 140-day license to use XLMiner for Education software Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology.
Endorsed by the Australian Human Resources Institute (AHRI – the national association representing human resource and people management professionals), Managing Human Resources 4th edition presents a concise coverage of key HRM topics typically taught in a 12 or 13-week teaching semester. The 4th edition has been thoroughly updated to reflect the impact of the Fair Work Act on the employment relationship between employers and employees, as well as on the work of HR professionals. Numerous practical examples throughout the text highlight contemporary HR issues, such as: Employee engagement Flexible working arrangements Work-life balance Generational issues in the workplace Skills shortages in various industries The importance of effective employee recruitment and training The cost of involuntary staff turnover Increasing diversity in the workplace Outsourcing Corporate social and ethical responsibility Globalisation In addition to a thorough analysis of the contemporary HR landscape in Australia, the text provides useful comparisons with HR practices in regional countries such as India, China and Japan.