EFFECTIVE METRICS, DATA CLUSTERING AND SEARCHING MECHANISMS FOR DATA MANAGEMENT IN ERP SYSTEMS

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K. Mohammed Hussain , J. Thangakumar , D. Venkata Subramanian

Abstract

This paper proposes a fuzzy based clustering search approach for an ERP system and searching mechanisms along with most appropriate metrics. In real time scenarios it is cumbersome to search for a particular piece of data from a data mart used by ERP applications. The situation becomes worse when it is difficult to search for the string when numerous strings are available. This work proposes a clustering approach which uses a fuzzy inference engine to make the search more effective and fast. The proposed technique reduces the processing time by 82% and the memory usage by 8%, compared to the conventional technique of searching the students’ or faculty data from the experimental ERP data sets. This paper also provides the comprehensive list of the metrics which can be considered to be incorporated as part of the framework and deployment of any ERP system.


 

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