Data Mining in Management and Practice

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AI68M9IBFQC
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Geliefert zwischen Mi., 21.01.2026 und Do., 22.01.2026

Details

Leverage the competative advantage of data mining in management with this step by step Data mining in management- The ability to recognize and track patterns within data-provides companies with a powerful competitive advantage. Building Data Mining Application is the one book that bridges this gap.Unique in its breadths, ease of reading,and depth, the book demonstratrates to business users. Beginning with an over view of the current state of data mining tools market. The book progresses to show you how to build and use use for corporation's best advantage. The book focuseses on several business processes, including customer relationship management, Fraud Detection and Management,Corporate Analysis and Risk Management.Real-word business Examples Real time Retail project had been explored to show common business problems encountered by a variety of major industries The authors clear-cutwriting style shows you to 1) Understand where data mining can be used to the greatest benefit 2)Data mining methodology and application in management. 3)Data mining in management for understanding customer. 4)Data mining challenges in retailing and how it is resolved. 5)Implemented Data Mining

Autorentext

Neville C Pradeep currently serves as Professor at PSN College of Technology had 5 years of Experience in sales interlinked with HR in Marketing Industry, in diversified sector at various level in Service and Industrial Marketing.Nevile C Pradeep having 2 yrs of experience had published 13 articles. Have Passion towards retailing, data mining.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783846584422
    • Auflage Aufl.
    • Sprache Englisch
    • Genre Economy
    • Größe H220mm
    • Jahr 2012
    • EAN 9783846584422
    • Format Kartonierter Einband (Kt)
    • ISBN 978-3-8465-8442-2
    • Titel Data Mining in Management and Practice
    • Autor Neville C. Pradeep
    • Untertitel 1.Data mining methodology and application 2.Data mining in Management strategies 3.Implemented Data Mining
    • Herausgeber LAP Lambert Academic Publishing
    • Anzahl Seiten 412

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