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Issues and Challenges in Convergence of Big Data, Cloud and Data Science

by Neha Mathur, Rajesh Purohit
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 160 - Number 9
Year of Publication: 2017
Authors: Neha Mathur, Rajesh Purohit
10.5120/ijca2017913082

Neha Mathur, Rajesh Purohit . Issues and Challenges in Convergence of Big Data, Cloud and Data Science. International Journal of Computer Applications. 160, 9 ( Feb 2017), 7-12. DOI=10.5120/ijca2017913082

@article{ 10.5120/ijca2017913082,
author = { Neha Mathur, Rajesh Purohit },
title = { Issues and Challenges in Convergence of Big Data, Cloud and Data Science },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2017 },
volume = { 160 },
number = { 9 },
month = { Feb },
year = { 2017 },
issn = { 0975-8887 },
pages = { 7-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume160/number9/27099-2017913082/ },
doi = { 10.5120/ijca2017913082 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:06:13.770517+05:30
%A Neha Mathur
%A Rajesh Purohit
%T Issues and Challenges in Convergence of Big Data, Cloud and Data Science
%J International Journal of Computer Applications
%@ 0975-8887
%V 160
%N 9
%P 7-12
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Big data, Cloud Computing and Data Science are currently trending in organizations across the globe. Big Data refers to technologies and techniques that involve data that is massive, heterogeneous and fast-changing for conventional technologies, skills and infra-structure to address efficiently. Cloud Computing is a paradigm that provides dynamically scalable and virtualized resource as a service over the Internet. The need to store, process, and analyze large amounts of data is making enterprise customers adopt cloud computing at scale. Cloud enables users to perform advanced analytics with big data. Data Science is a field that comprises of everything that related to data cleansing, preparation, and analysis. It is the umbrella of techniques used when trying to extract insights and information from data. Big Data Analytics the science of examining big data with the purpose of drawing conclusions and inferences. It is a subset of data science. Big data analytics is unimaginable without cloud in the current scenario. This paper discusses the convergence of big data, cloud and data science. It also identifies various issues in Big Data, Cloud, Data Science and their convergence.

References
  1. H. Kisker, “Big Data Meets Cloud”, August 15, 2012, http://blogs.forrester.com/holger_kisker/12-08-15-big_data_meets_cloud [Last Accessed On: 2-Jan-2017]
  2. W. Tian and Y. Zhao “Big Data technologies and Cloud Computing”, Optimized Cloud Resource Management and Scheduling, DOI: http://dx.doi.org/10.1016/B978-0-12-801476-9.00002-1, 2015 Elsevier Inc.
  3. S. Kaisler et al, " Big Data: Issues and Challenges Moving Forward ", in 2013 46th Hawaii International Conference on System Sciences, 2012 IEEE, DOI 10.1109/HICSS.2013.645
  4. Gens, F. "New IDC IT Cloud Services Survey: Top Benefits And Challenges". IDC eXchange., 2009. [Online]. [Last Accessed:17 December 2016].
  5. I.A.T. Hashem et al.,"The Rise of “Big Data” On Cloud Computing: Review and Open Research Issues", Information Systems, vol 47, pp 98–115, 2016
Index Terms

Computer Science
Information Sciences

Keywords

Big Data Cloud Data Science Convergence Issues

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