Organizational Data Mining

Organizational Data Mining

Hamid R. Nemati (The University of North Carolina at Greensboro, USA) and Christopher D. Barko (The University of North Carolina at Greensboro, USA)
Copyright: © 2005 |Pages: 5
DOI: 10.4018/978-1-59140-557-3.ch168
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Abstract

Data mining is now largely recognized as a business imperative and considered essential for enabling the execution of successful organizational strategies. The adoption rate of data mining by enterprises is growing quickly, due to noteworthy industry results in applications such as credit assessment, risk management, market segmentation, and the ever-increasing volumes of corporate data available for analysis. The quantity of data being captured is staggering—data experts estimate that in 2002, the world generated five exabytes of information. This amount of data is more than all the words ever spoken by human beings (Hardy, 2004). The rate of growth is just as astounding—the amount of data produced in 2002 was up 68% from just two years earlier. The size of the typical business database has grown a hundred-fold during the past five years as a result of Internet commerce, ever-expanding computer systems, and mandated recordkeeping by government regulations (Hardy, 2004). Following this trend, a recent survey of corporations across 23 countries revealed that the largest transactional database almost doubled in size to 18 TB (terabytes), while the largest decision-support database grew to almost 30 TB (Reddy, 2004).

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