We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Big Data Technologies: Brief Overview

by Yojna Arora, Dinesh Goyal
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 131 - Number 9
Year of Publication: 2015
Authors: Yojna Arora, Dinesh Goyal
10.5120/ijca2015906262

Yojna Arora, Dinesh Goyal . Big Data Technologies: Brief Overview. International Journal of Computer Applications. 131, 9 ( December 2015), 1-6. DOI=10.5120/ijca2015906262

@article{ 10.5120/ijca2015906262,
author = { Yojna Arora, Dinesh Goyal },
title = { Big Data Technologies: Brief Overview },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 131 },
number = { 9 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume131/number9/23474-2015906262/ },
doi = { 10.5120/ijca2015906262 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:26:46.483099+05:30
%A Yojna Arora
%A Dinesh Goyal
%T Big Data Technologies: Brief Overview
%J International Journal of Computer Applications
%@ 0975-8887
%V 131
%N 9
%P 1-6
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the current scenario, big data is the biggest challenge for the industries to deal with. It is characterized by Huge Volume, Heterogeneous unidentified sources, High rate of data generation, inability to extract value information from irrelevant data. There are many approaches been put forward for dealing with this Big Data, some of them are RDBMS, Hadoop, Cloud Computing etc. This review article includes an elicitation of definitions of Big Data from some previous work, its characteristics, applications, various implementation techniques proposed for dealing with Big Data. It also discusses about some of the benchmarks which are proposed by companies.

References
  1. Stephen Kaisler, Frank Arrmour, J. Alberto,” Big Data: Issues and Challenges Moving Forward”,46th Hawaii International Conference on System Science, IEEE,2012
  2. Sam Padden, “From database to Big Data,”, in IEEE Computer Society, 2012
  3. Dan Garlasu, “Data Implementation Based on Grid Computing”,
  4. Avita Katal, Mohammad Wazid and R H Goudar, “Big Data : Issues, Challenges, Tools and good Practices”, in IEEE 2013
  5. Seref Sagiroglu and Duygu Sinang, “Big Data : A Review”,IEEE, 2013
  6. Yuri Demchenko, Paolo Grosso andCees de Laat, “Addressing Big Data Issues in Scientific Data Infrastructure”, in IEEE 2013
  7. Parth Chandarana and M Vijayalakshmi, “Big Data Analytics Framework”, in International Conference on Circuits, System, Communication and Information Technology Applications”,IEEE, 2014
  8. Rich Adduci, Dave Blue and Guy Chiarello, “Big Data : Big Opportunities to create Business value”, in EMC2
  9. Doug Laney, “3 D Data Management : Controlling Data Volume, Velocity and Variety”, in Application Delivery Stratergies, Meta Group, 2001
  10. First Tekiner and John A keane, “Big Data Framework”, in IEEE international conference on Systems, Man and cybernetics, IEEE, 2013
  11. Janusz Weilki, “Implementation of Big Data Concept in organizations- possibilities, impediments and challenges”, proceeding of 2013 Federated conference on computer science and information systems, pp985-989, IEEE, 2013
  12. Edmund Kohlwey, Abel Sussman, Jason Trost and Amber Maurer, “Leveraging the cloud for Big data Biometrics”, in World Congress in Services, IEEE,2011
  13. Youseef M Essa, “Mobile Agent Based New Framework for improving Big Data Analysis”, in International Conference on Cloud Computing and Big Data, IEEE, 2013
  14. Katharina Ebner, Thilo Buhnen and Nils Urbach, “Think Big with Big Data: Identifying Suitable Big Data Strategies in Corporate Environment”, 47th Hawaii International Conference on System Science”, IEEE, 2014
  15. Dr Daniel Fasel, “ Potentials of Big Data for Governmental Services”,
  16. Sung Hwan Kim, Nam UK Kim and Tai Myoung Chung, “Attribute Relationship Evaluation Methodology for Big Data Security”, in IEEE, 2013
  17. Zibin Zheng, Jiemming Zhu and Michael R Lyu, “Service generated big data and big data as a service : An Overview”, in IEEE International Congress on Big Data, 2013
  18. Wen Xiong, Zibin Yu, and Zhendong Bei, “A characterization of Big Data Benchmarks”, in IEEE international conference on Big Data”, IEEE,2013
  19. Xindong Wu, Xingquan Zhu, Gong Qing Wu and Wei Ding, “Data Mining with Big Data”, in IEEE transactions in knowledge and data engineering, Vol 26, Number 1, January 2014
  20. Lei Wang, Jainfeng Zhan and Chunjie Luo, “Big Data Bench: A Big Data Benchmark suite from Internet Services”, in IEEE, 2014
  21. Xueli Huang and Xiaojiang Du, “Achieving Big Data Privacy via Hybrid Cloud”, in Infocom workshop on Security and Privacy on Big Data, IEEE, 2014
  22. Barna Saha and Divesh Srivastava, “Data Quality : The other face of Big Data”, in IEEE, 2014
  23. Carol J Romanowski and Rajender K Raj, “ Catching the wave : Big Data in the classroom”, in IEEE 2013
  24. Du Zhang, “ Inconsistencies in Big Data”, in Proceeding of IEEE international conference on Cognitive Informatics and Cognitive Computing” IEEE, 2013
  25. Marcus R. Wigan and Roger Clarke. “Big Data’s big unintended consequences”, in IEEE Computer Society, 2013
  26. Jinsong Zhang, Yan Chen and Taoying Li, “Opportunities of Innovation under challenges of Big Data”, in 10th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), IEEE, 2013
  27. Lin Gu, Deze Zeng and Peng Li, “Cost Minimization for Big data Processing in Geo Distribeuted Data Centers”, in IEEE transactions on Emerging topics in Computing, 2014
  28. J Han, M Kamber and J Pei, “Data Mining Concepts and techniques”, Morgan Kaufmann, 2006
  29. B.Gerhardt, K. Griffin and R. Klemann, "Unlocking Value in the Fragmented World of Big Data Analytics", Cisco Internet Business Solutions Group, June 2012,
  30. M. Schroeck, R. Shockley, J. Smart, D. Romero-Morales, and P. Tufano, Analytics: the real-world use of big data: how innovative enterprises extract value from uncertain data, Executive Report, IBM Institute for Business Value and Said Business School at the University of Oxford, 2012.
  31. W. GAO, et al. “BigDataBench: a Big Data Benchmark Suite from Web Search Engines”. The Third Workshop on Architectures andSystems for Big Data (ASBD 2013) in conjunction with ISCA 2013.
  32. Morgan, T., Ibm Global Technology Outlook 2012, Warwick, 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Big Data Hadoop Map Reduce

Powered by PhDFocusTM