Organizational Data Mining: Leveraging Enterprise Data Resources for Optimal Performance

Organizational Data Mining: Leveraging Enterprise Data Resources for Optimal Performance

Hamid Nemati (The University of North Carolina at Greensboro, USA) and Christopher D. Barko (Laboratory Corporation of America, USA)
Release Date: July, 2003|Copyright: © 2004 |Pages: 388
DOI: 10.4018/978-1-59140-134-6
ISBN13: 9781591401346|ISBN10: 1591401348|EISBN13: 9781591401353
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Description & Coverage
Description:

Successfully competing in the new global economy requires immediate decision capability. This immediate decision capability requires quick analysis of both timely and relevant data. To support this analysis, organizations are piling up mountains of business data in their databases every day. Terabyte-sized (1,000 megabytes) databases are commonplace in organizations today, and this enormous growth will make petabyte-sized databases (1,000 terabytes) a reality within the next few years (Whiting, 2002). Those organizations making swift, fact-based decisions by optimally leveraging their data resources will outperform those organizations that do not. A technology that facilitates this process of optimal decision-making is known as Organizational Data Mining (ODM). Organizational Data Mining: Leveraging Enterprise Data Resources for Optimal Performance demonstrates how organizations can leverage ODM for enhanced competitiveness and optimal performance.

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Reviews and Testimonials

This book introduces the reader to Data Mining from the view points of business analysts and business professionals. Data Mining is discussed in a business context. It is not a mathematical book beyond the reach of managers. It provides a good mix of managerial as well as technical issues illustrated by real world cases and examples. For the Manager it illustrates the strategic and operational potential use of Data Mining. For the technical analysts, it has a good review of Data Mining techniques. It also covers the integration of Data Mining with Data Warehouse, OLAP, Decision Support Systems, and E-Commerce using traditional as well as emerging Soft Computing and Agent-based technologies. The author also explores the future challenges and opportunities for DM. The book Can be can be useful in both academic as well as professional class rooms. This book is interesting to anyone who is interested in the business applications of Data Mining. The book is very well written and easy to read. Over all I strongly recommend the book.

– Bijan Fazlollahi, Georgia State University,USA

The adage "knowledge is power" is widely accepted in the corporate circles, and tremendous amounts of data has been and is being accumulated towards the goal of acquiring more knowledge. But corporates are increasingly realizing that there is a wide gap between "data" and "knowledge". Data warehousing and data mining provide the techniques to refine and distill data into knowledge that can support enterprise decision making processes. This book provides a timely account of data warehousing and data mining applications for the organizations. It provides a balanced coverage of technical and organizational aspects of these techniques, supplemented by case studies of real commercial applications. Managers, practitioners, and research-oriented personnel can all benefit from the many illuminating chapters written by experts in the field.

– Fereidoon Sadri, University of North Carolina, USA
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Editor Biographies
Hamid Nemati is an associate professor of information systems in the Department of Information Systems and Operations Management at the University of North Carolina at Greensboro. He holds a doctorate from the University of Georgia and a Master of Business Administration from the University of Massachusetts. Before coming to UNCG, he was on the faculty of J. Mack Robinson College of Business Administration at Georgia State University. He has extensive professional experience in various consulting, business intelligence, and analyst positions and has consulted for a number of major organizations. His research specialization is in the areas of decision support systems, data warehousing, data mining, knowledge management, and information privacy and security. He has presented numerous research and scholarly papers nationally and internationally. His articles have appeared in a number of premier professional and scholarly journals.
Christopher D. Barko is an information technology professional at Laboratory Corporation of America, USA. His IT industry experience spans many years in various consulting, business intelligence, software engineering and analyst positions for a number of Fortune 500 organizations. He received his B.B.A. in Computer Information Systems from James Madison University and M.B.A. from the University of North Carolina at Greensboro where he specialized in Decision Support Systems. His current research interests include Organizational Data Mining, Business Intelligence and Customer Relationship Management and how these technologies can enhance the organizational decision-making process to optimize resource allocation and improve profitability. His research has been published in several leading journals such as the Journal of Data Warehousing, Journal of Computer Information Systems, and others. He is also President of Customer Analytics, Inc., a consultancy that leverages advanced analytics to deliver profitable and effective database marketing solutions.
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