Non-Intrusive Context Aware Transactional Framework to Derive Business Insights on Big Data

DOI: 10.4236/jsip.2015.62007   PDF   HTML   XML   3,176 Downloads   3,588 Views  

Abstract

To convert invisible, unstructured and time-sensitive machine data into information for decision making is a challenge. Tools available today handle only structured data. All the transaction data are getting captured without understanding its future relevance and usage. It leads to other big data analytics related issue in storing, archiving, processing, not bringing in relevant business insights to the business user. In this paper, we are proposing a context aware pattern methodology to filter relevant transaction data based on the preference of business.

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Chidambaram, S. , Rubini, P. and Sellam, V. (2015) Non-Intrusive Context Aware Transactional Framework to Derive Business Insights on Big Data. Journal of Signal and Information Processing, 6, 73-78. doi: 10.4236/jsip.2015.62007.

Conflicts of Interest

The authors declare no conflicts of interest.

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