A Review on Big Data Mining, Distributed Programming Frameworks and Privacy Preserving Data Mining Techniques

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Y. Sowmya
Dr. M Naga Ratna, Dr.C Shoba Bindu


Data mining gradually became big data mining as the enterprises are causing exponential growth of data. Comprehensive mining of such data can bestow accurate business intelligence. Towards this end big data mining has become a new buzz word in the mining paradigm. The emergence of technologies such as virtualization and cloud computing paved way for the processing of big data which is characterized by Volume, Velocity and Variety. For big data processing, a new programming model, MapReduce is used. This framework runs in distributed environment to process huge amount of data. There are many distributed programming frameworks such as Hadoop, Haloop, Dryad, Sailfish, and AROM that are based on MapReduce and equivalent programming paradigms. The success of enterprises in future depends on the intelligent mining of big data for comprehensive business intelligence. At the same time privacy preserving data mining also important as the data mining should not be taken place at the cost of privacy. In this paper we explore big data mining, distributed programming frameworks and the privacy preserving data mining practices and techniques.


Keywords: Big data mining, privacy preserving data mining, distributed programming frameworks


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