Review Paper on Usage of Data in Cloud Computing Applications
Keywords:
Big Data, Big Data Analytics, Map Reduce, Hadoop, Personal Digital Assistant (PDA), Enterprise Data Warehouse (EDW)Abstract
Cloud computing is a generally ground-breaking innovation which performs enormous scale and complex processing. It takes out the prerequisite to keep up expensive registering equipment, committed space necessity and related programming. Huge development in the size of information or enormous information created through cloud registering has been distinguished. Idea of enormous information is a testing and time-requesting errand that requires a vast computational space to guarantee fruitful information preparing and examination. This paper incorporates definition, qualities, and arrangement of enormous information alongside a few dialogs on distributed computing are presented. The similitude between enormous information and distributed computing, enormous information stockpiling frameworks, a few major information handling methods and Hadoop innovation are additionally talked about. The term 'Huge Data' characterizes inventive strategies and innovations to catch, store, convey, oversee and break down peta byte-or bigger measured datasets with high-speed and extraordinary structures. Huge information might be organized, unstructured or on the other hand semi-organized, bringing about ineptitude of customary information the board strategies. Information can be created from different applicable sources and can store in the framework at different rates. So as to break down these a lot of information in a cheap and effective way, parallelism method is utilized. 2015 was the year that Big Data went from being something that a larger part of associations were either doing or at the least effectively considering. The development of cloud based Enormous Data administrations has made Big Data examination an achievable reality for associations everything being equal.
References
[1] Umasri.M.L,Shyamalagowri.D,SureshKumar.S“Mining Big Data:- Current status and forecast to the future” Volume 4,Issue 1, January 2014 ISSN: 2277 128X.
[2] Albert Bifet,“Mining Big Data in Real Time”, informatica,2013.
[3] James Manyika, Michael Chui, Brad Brown, Jacques Bhuhin,Richard Dobbs, CharlesRoxburgh, Angela Hungh Byers, “BigData: The next frontier for innovation, competition and productivity”, June 2011.
[4] Sameera Siddiqui, Deepa Gupta,” Big Data Process and Analytics : A Survey”, InternationalJournal Of EmergingResearch in Management & Technology, ISSN: 22789359,Volume 3, Issue 7, July 2014.
[5]M.Cooper,P.Mell(2012).TacklingbigData(Online).Http://csrc.nist.gov/groups/SMA/Forum/document/June2012Presentation/f%CSM_june2012_cooper_Neul.pdf.
[6] Han Hu, YongyangNen, Tat Seng Chua, Xuelong Li,”Towards Scalable System for Big Data Analytics: A Technology Tutorial”, IEEE Access, Volume 2, Page No 653, June 2014.
[7] J.Gantz, D. Reinset,” The Digital Universe in 2020: Big Data, Bigger digital shadow, and biggest growth in the far east”, in Proc :IDC iview, IDC Anal, Future, 2012.
[8] www.ebizmba .com/articles/social-networking websites.
[9] Neil Raden,”Big Data Analytics Architecture”, Hired Brains Inc, 2012.
[10] James Manyika, Michael Chui, Brad Brown, Jacques Bhuhin, Richard Dobbs, Charles Roxburgh, Angela Hungh Byers, “Big Data: The next frontier for innovation, competition and productivity”, June 2011.
[11]Wei Fan, Albert Bifet, “Mining Big Data: Current Status and Forecast to the Future”, SIGKDD Explorations, Volume 14, Issue2.
[12] Albert Bifet“Mining Big Data In Real Time” Informatics 37(2013) 15–20 DEC 2012.
[13] Bernice Purcell “The emergence of “big data” technology and analytics” Journal of Technology Research 2013.
[14] Ritu Katara, Hareram Shah “A Novel Integrated Approach for Big Data Mining”, International Journal For Computer treands andTechnology, Volume 18, Number 5, Dec 2014.
[15] K, Chitharanjan, and Kala Karun A. "A review on hadoop, HDFS infrastructure extensions.". JeJu Island: 2013, pp. 132-137, 11-12 Apr. 2013.
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