CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Big Data Analysis: A Review

by Sanyam Sareen, Shivangi Ahuja
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 23
Year of Publication: 2018
Authors: Sanyam Sareen, Shivangi Ahuja
10.5120/ijca2018917994

Sanyam Sareen, Shivangi Ahuja . Big Data Analysis: A Review. International Journal of Computer Applications. 181, 23 ( Oct 2018), 5-9. DOI=10.5120/ijca2018917994

@article{ 10.5120/ijca2018917994,
author = { Sanyam Sareen, Shivangi Ahuja },
title = { Big Data Analysis: A Review },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2018 },
volume = { 181 },
number = { 23 },
month = { Oct },
year = { 2018 },
issn = { 0975-8887 },
pages = { 5-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number23/30023-2018917994/ },
doi = { 10.5120/ijca2018917994 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:06:46.916740+05:30
%A Sanyam Sareen
%A Shivangi Ahuja
%T Big Data Analysis: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 23
%P 5-9
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The term Big Data accounts for analysis of already procured heterogeneous, structured, unstructured data to find connections between already existing links and predicting the future ones. Big Data finds its use in almost all aspects of society including healthcare, mining, telecom industries etc. It aims at quicker computation of all the humongous data collected from various sources. Big Data and decision making are concomitant so it is influencing IT sectors in present days too. Because Big Data is dependent upon the storage capacity, confidentiality and data complexity come as big loop holes. The sources of this mammoth volume of data include digital pictures and videos, online transactions, GPS signals, sensors etc. Currently hadoop handles big data change but the rate at which the data is increasing new techno logical developments need to made to buttress the already existing system.

References
  1. Huang, Y., Porter, A. L., Cunningham, S. W., Robinson, D. K., Liu, J., & Zhu, D. (2017). A technology delivery system for characterizing the supply side of technology emergence: Illustrated for Big Data & Analytics. Technological Forecasting and Social Change.
  2. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., Byers, A.H., (2011). Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute.
  3. Sushil (2017). Multi-criteria valuation of flexibility initiatives using integrated TISM – IRP with a big data framework. Production Planning & Control
  4. SciencegDaily, https://www.sciencedaily.com/releases/2013/05/130522085217.htm. Big Data, for better or worse: 90% of world's data generated over last two years. Accessed on: 23/06/2018
  5. Zaslavsky, A., Perera, C., Georgakopoulos, D. (2013). Sensing as a service and big data. Retrieved from https://arxiv.org/abs/1301.0159.fAccessedfon:f23/06/2018.
  6. ThegNextgWeb, https://thenextweb.com/space/2010/01/01/avatar-takes-1-petabyte-storage-space-equivalent-32-year-long-mp3/ Believe it or not: Avatar takes 1 petabyte of storage space, equivalent to a 32 YEAR long MP3. Accessed on: 24/06/2018
  7. Abbass , H. A., Leu, G., and Merrick, K. (2016). A Review of Theoretical and Practical Challenges of Trusted Autonomy in Big Data. Theoretical Foundations for Big Data Applications: Challenges and Opportunities.
  8. Bhosale, Harshawardhan S., and Devendra P. Gadekar. "A review paper on Big Data and Hadoop." International Journal of Scientific and Research Publications 4, no. 10 (2014): 1-7
  9. Ammu, N., & Irfanuddin, M. (2013). Big data challenges. International Journal of Advanced Trends in Computer Science and Engineering, 2(1), 613-615.
  10. Jin, J., Liu, Y., Ji, P., & Liu, H. (2016). Understanding big consumer opinion data for market-driven product design. International Journal of Production Research.
  11. Jin, X., Wah, B. W., Cheng, X., & Wang, Y. (2015). Significance and challenges of big data research. Big Data Research.
  12. Rust, R. T., & Huang, M. H. (2014). The service revolution and the transformation of marketing science. Marketing Science.
  13. Xie, K., Wu, Y., Xiao, J., & Hu, Q. (2016). Value co-creation between firms and customers: The role of big data-based cooperative assets. Information & Management.
  14. Bock, S., &Isik, F. (2015). A new two-dimensional performance measure in purchase order sizing. International Journal of Production Research.
  15. France, S. L., & Ghose, S. (2016). An analysis and visualization methodology for identifying and testing market structure. Marketing Science, 35(1), 182-197.
  16. Qi, J., Zhang, Z., Jeon, S., & Zhou, Y. (2016). Mining customer requirements from online reviews: A product improvement perspective. Information & Management.
  17. Yang, Y., Pan, B., & Song, H. (2014). Predicting hotel demand using destination marketing organization’s web traffic data. Journal of Travel Research.
  18. Raun, J., Ahas, R., &Tiru, M. (2016). Measuring tourism destinations using mobile tracking data. Tourism Management.
  19. He, J., Liu, H., &Xiong, H. (2016). SocoTraveler: Travel-package recommendations leveraging social influence of different relationship types. Information & Management.
  20. Dolnicar, S., & Ring, A. (2014). Tourism marketing research: Past, present and future. Annals of Tourism Research.
  21. Fisher, D., DeLine, R., Czerwinski, M., &Drucker, S.
  22. (2012). Interactions with big data analytics.
  23. Wingfield, N. Virtual product, real profits: Players spend on zynga’s games, but quality turns some off. Wall Street Journal
  24. Kuchipudi, S., &Reddy, T. (2015). Application of Big data in Various Fields.
  25. Xindong, W., Xingquan, Z., Gong-Qing, W., &Wei, D.
  26. (2014). Data Mining with Big Data.
  27. IgHealthgTran, http://ihealthtran.com/wordpress/2013/03/iht%C2%B2-releases-big-data-research-report-download-today/ Healthcare data. Accessed on: 26/06/2018
  28. Raghupathi, W., &Raghupathi,V. (2014). Big data
  29. analytics in healthcare: promise and potential.
  30. Apache Hive, http://hive.apache.org Accessed on: ggggg23/06/2018
  31. Mukherjee, S., &Shaw R. (2016). Big Data - Concepts, Applications, Challenges and Future Scope.
  32. Wikipedia, https://en.wikipedia.org/wiki/Google_Cloud_Platform
  33. Google Cloud Platform. Accessed on: 25/06/2018
  34. Idc, http://www.idc.com/getdoc.jsp?containerId=prUS25329114 Big Data Scope. Accessed on: 25/06/2018
  35. Shahriar, A., &Samuel, F.(2016) .Big data analytics in E-commerce: a systematic review and agenda for future research.
Index Terms

Computer Science
Information Sciences

Keywords

Hadoop Big Data analytics Hadoop Ecosystem

Powered by PhDFocusTM