Assisting decision making in the event-driven enterprise using wavelets

Authors:
Stephen Russell;Aryya Gangopadhyay;Victoria Yoon
Affiliations:
Department of Information Systems, University of Maryland Baltimore County, Maryland, USA;Department of Information Systems, University of Maryland Baltimore County, Maryland, USA;Department of Information Systems, University of Maryland Baltimore County, Maryland, USA
Venue:
Decision Support Systems
Year:
2008

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Abstract

This paper discusses issues related to data-driven decision support systems in event-driven enterprises and proposes Discrete Wavelet Transformation (DWT) as a method to improve these systems. DWT is proposed as a method of data reduction that reduces the effects of excessive data, enabling better visualization and scalability, while preserving patterns, trends, and surprises in the data. A procedural model for using a data-driven decision support system that integrates DWT is presented. Finally, the procedural model is evaluated in experiments based on real event-driven data from a large telecommunications company.