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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Using Data Mining for Forecasting Data Management Needs

Using Data Mining for Forecasting Data Management Needs
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Author(s): Qingyu Zhang (Arkansas State University, USA) and Richard S. Segall (Arkansas State University, USA)
Copyright: 2008
Pages: 18
Source title: Handbook of Computational Intelligence in Manufacturing and Production Management
Source Author(s)/Editor(s): Dipak Laha (Jadavpur University, India) and Purnendu Mandal (Lamar University, USA)
DOI: 10.4018/978-1-59904-582-5.ch021


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This chapter illustrates the use of data mining as a computational intelligence methodology for forecasting data management needs. Specifically, this chapter discusses the use of data mining with multidimensional databases for determining data management needs for the selected biotechnology data of forest cover data (63,377 rows and 54 attributes) and human lung cancer data set (12,600 rows of transcript sequences and 156 columns of gene types). The data mining is performed using four selected software of SAS® Enterprise MinerTM, Megaputer PolyAnalyst® 5.0, NeuralWare Predict®, and Bio- Discovery GeneSight®. The analysis and results will be used to enhance the intelligence capabilities of biotechnology research by improving data visualization and forecasting for organizations. The tools and techniques discussed here can be representative of those applicable in a typical manufacturing and production environment. Screen shots of each of the four selected software are presented, as are conclusions and future directions.

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