Unlock Different V`s of Big Data for Analytics
Keywords:
Big Data, V’s, Variety, Volume, Velocity, Business analyticsAbstract
This paper aims to review the purpose of the Big Data characteristics, to identify Big Data solutions in different perspective. In 2001, the first three ‘V’ (Volume, Velocity, and Variety) dimensions of Big Data are addressed. Later, V’s like Variability, Veracity, Virality, Visualization and Value were compiled from several sources including IBM, Data Science Central, National Institute of Standards and Technology (NIST) etc.,. Recently, characteristics of Big Data increased to understand and analyze the big data efficiently and effectively. The big data and big data policy can be better revealed by adding more V’s. Addition of more V’s was providential, in the sense that big data first act in response were meet these additional challenges with this massive data. The new V’s are added to the list will provide valuable and most excellent observation over the data. Therefore, this study tries to summarize the available characteristics in the literature to get the better picture about Big Data further. From this, it has been observed that there are more than 54 V’s dimensions (characteristics) like Venue, Vocabulary, Vendible, Validity, Volatility, Verbosity, Vagueness, Vanity, Voracity and so on. These characteristics were emerged to suit different applications and domains. This review results in finding the impacts of V’s on Big data analytics.
References
Retrieved from http://www.sas.com/offices/NA/canada/lp/Big- Data/Extreme-Information-Management.pdf
Retrieved from http://www.ibmbigdatahub.com/infographic/extracting-business-value-4-vs-big-data
Retrieved from http://blogs.gartner.com/doug-laney/deja-vvvue-others-claiming-gartners-volume-velocity-variety-construct- for-big-data/
Retrieved from http://hmchen.shidler.hawaii.edu/Chen_big_data_MISQ_2012.pdf
Retrieved from https://hbr.org/2012/10/making-advanced-analytics-work-for-you/ar/1
013, July 31). Retrieved from HTTPS://BREAKTHROUGHANALYSIS.COM/2013/07/31/4-VS-FOR-BIG-DATA-ANALYTICS/
(2013, November 11). Retrieved from http://www.infoivy.com/2013/11/comparison-table-for-big-data-system.html
(2013, November 25). Retrieved from http://www.infoivy.com/2013/11/comparison-table-of-hive-pig-shark.html
(2013, November 18). Retrieved from http://www.infoivy.com/2013/11/comparison-table-of-hdfs-mapreduce-yarn.html
(2013, October 10). Retrieved from http://avnetmex.blogspot.in/search/label/Valor
(2013). Retrieved from http://www.sigmetrics.org/sigmetrics2013/bigdataanalyt ics/abstracts2013/bdaw2013_submission_4.pdf
(2014). Retrieved from http://www3.weforum.org/docs/WEF_GlobalInformationTechnology_Report_2014.pdf
(2015, August 18). Retrieved from www.optimusinfo.com: http://www.optimusinfo.com/understanding-the-7-vs-of-big-data/
Baunach, S. (2012, March 8). Retrieved from http://www.datacenterknowledge.com/archives/2012/03/08/three-vs-of-big-data-volume-velocity-variety/
Borne, D. (2014, April 11). Retrieved from https://www.mapr.com/blog/top-10-big-data-challenges-serious-look-10-big-data-vs
Bowden, J. (2014, June 15). Retrieved from http://www.business2community.com/digital-marketing/4-vs-big-data-digital-marketing-0914845#7G4uDZDcpTo5q1c2.97
Caesar Wu, R. B. (n.d.). Big Data Analytics = Machine Learning + Cloud Computing. BDA=ML+CC , 1-25.
DeVan, A. (2016, April 7). Retrieved from https://www.impactradius.com/blog/7-vs-big-data/
Dr.Darrin. (2016, May 2). Retrieved from https://educationalresearchtechniques.wordpress.com/2016/05/02/characteristics-of-big-data/
Gartner. (2013, March 27). Retrieved from http://www.forbes.com/sites/gartnergroup/2013/03/27/gartners-big-data-definition-consists-of-three-parts-not-to-be-confused-with-three-vs/#5040d1cc3bf6
Gewirtz, D. (2016, April 20). Retrieved from http://www.zdnet.com/article/volume-velocity-and-variety-understanding-the-three-vs-of-big-data/
GoodStratTweet. (2015, Feb 22). Retrieved from http://www.informationweek.com/big-data/big-data-analytics/big-data-avoid-wanna-v-confusion/d/d-id/1111077?page_number=1
Grimes, S. (2013, July 8). Retrieved from http://www.informationweek.com/big-data/big-data-analytics/big-data-avoid-wanna-v-confusion/d/d-id/1111077?page_number=1
Guoru Ding, Q. W.-D. (2014, May 4). Retrieved from http://www.infoivy.com/2014/05/how-to-use-big-data-to-predict.html
Laney, D. (2012, January 14). Retrieved from http://blogs.gartner.com/doug-laney/deja-vvvue-others-claiming-gartners-volume-velocity-variety-construct-for-big-data/
Maheshwari, R. (2015, June 22). Retrieved from https://www.linkedin.com/pulse/3-vs-7-whats-value-big-data-rajiv-maheshwari
Marr, B. (2015, March 19). Retrieved from http://www.ibmbigdatahub.com/blog/why-only-one-5-vs-big-data-really-matters
Mcnulty, E. (2014, May 22). Retrieved from http://dataconomy.com/seven-vs-big-data/
Mohanty, S. (2015, June 10). Retrieved from HTTP://DATACONOMY.COM/THE-FOUR-ESSENTIALS-VS-FOR-A-BIG-DATA-ANALYTICS-PLATFORM/
Mullah, R. (2018). Retrieved from https://bigdata.cioreview.com/cxoinsight/the-other-five-v-s-of-big-data-an-updated-paradigm-nid-10287-cid-15.html
Munoz, M. (2013, April 27). Retrieved from http://blog.thanxmedia.com/blog/2013/08/27/big-data-integration/
Neil Biehn, P. (2013, May). Retrieved from • https://www.wired.com/insights/2013/05/the-missing-vs-in-big-data-viability-and-value/
Normandeau, K. (2013, September 12). Retrieved from http://insidebigdata.com/2013/09/12/beyond-volume-variety-velocity-issue-big-data-veracity/
Rijmenam, M. v. (n.d.). Retrieved from https://datafloq.com/read/3vs-sufficient-describe-big-data/166
Rowe, S. D. (2016, June). Retrieved from http://www.destinationcrm.com/Articles/Editorial/Magazine-Features/Beyond-the-Three-Vs-of-Big-Data--111420.aspx
Self, R. J. (2014). Retrieved from http://computing.derby.ac.uk/c/big-data-analytics-analytics-12-vs/
Svetlana. (2015, July 27). Retrieved from http://svetlana.dbsdataprojects.com/2015/07/27/3-vs-and-beyond-the-missing-vs-in-big-data/
Tee, J. (2013, August). Retrieved from http://www.theserverside.com/feature/Handling-the-four-Vs-of-big-data-volume-velocity-variety-and-veracity
Wang, R. R. (2012, February 27). Retrieved from http://blog.softwareinsider.org/2012/02/27/mondays-musings-beyond-the-three-vs-of-big-data-viscosity-and-virality/
Williamson, J. Retrieved from http://www.dummies.com/careers/find-a-job/the-4-vs-of-big-data/
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