Data Mining with Big data applications, its challenges and Future Research

G. Vijaya kumara, P. Vamsi Krishna Raja

Abstract


Big data is the term for a collection of data sets which are enormous and complex, it contain organized and unstructured both kind of data. Data originates from all over the place, sensors used to assemble atmosphere information, presents via web-based networking media destinations, computerized pictures and recordings and so forth, This data is known as big data. Valuable data can be separated from this big data with the assistance of data mining. Data mining is a strategy for finding intriguing examples just as enlightening, reasonable models from enormous scale data. Right now reviewed sorts of big data and difficulties in big data for future. Separating valuable information from huge data-set like in all science and designing space, There will be most energizing open door in up and coming a very long time for big data. This paper incorporates big data, Data mining, Data mining with big data, Challenging issue and study papers of different organizations identified with big-data. Each organization concentrated on the most proficient method to oversee huge arrangement of data and how much organizations put resources into big-data just as what kind of return they get. Numerous specialized difficulties like implementations and visualizations are to be thought about in future. To oversee and dissect edge data investigate business openings getting from the research of edge data. Team up with the business to comprehend existing edge framework and the potential use for data. It concluded from the discoveries that Enterprise are as yet searching for the correct foundation instruments that will empower them to successfully deal with their big-data with their business needs.


References


“Big Data-A New World of Opportunities”, NESSI White Paper, December 2012

“Big Data Working Group Big Data Analytics for Security Intelligence”, September 2013 CLOUD SECURITY ALLIANCE Big Data Analytics for Security Intelligence

Purcell, Bernice. "The emergence of" big data" technology and analytics." Journal of Technology research 4 (2013): 1.

“Big-Data Computing: Creating revolutionary breakthroughs in commerce, science, and society”, Randal E. Bryant Carnegie Mellon University Randy H. Katz University of California, Berkeley Edward D. Lazowska University of Washington, Version 8: December 22, 2008

NIST Big Data Reference Architecture DRAFT Version 0.2 Reference Architecture Subgroup NIST Big Data Working Group (NBD-WG) September, 2013

Architecture Framework and Components for the Big Data Ecosystem Draft Version 0.2 Yuri Demchenko, Canh Ngo, Peter Membrey 12 September 2013 , System and Network Engineering, UNIVERSITEIT VAN AMSTERDAM

NIST Big Data Reference Architecture, DRAFT Version 10, Reference Architecture Subgroup NIST Big Data Working Group (NBD-WG) September, 2013

“Data Modeling for Big Data”, by Jinbao Zhu, Principal Software Engineer, and Allen Wang, Manager,Software Engineering, CA Technologies

“Big Data Standardisation in Industry and Research” , EuroCloud Symposium ICS Track: Standards for Big Data in the Cloud 15 October 2013, Luxembourg Yuri Demchenko System and Network Engineering Group, University of Amsterdam

“An Overview of Big Data Technology and Security Implications”, Michael Cooper & Peter Mell NIST Information Technology Laboratory Computer Security Division.


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