A Literature Review on Big Data Analytics
Keywords:
Analytics, Big Data, Data Mining, Decision MakingAbstract
Huge volumes of data have been available to policymakers in the digital world. Big data is a term to collections that are not always huge, but also varied and fast changing, rendering standard tools and procedures inadequate. Due to the quick creation of such data, techniques to organize and retrieve value and knowledge from these sets must be explored and given. Additionally, choice should be able to obtain relevant information from that wide and continuously changing collection of data, which encompasses everything from ordinary activities to customer communication and social data. Analytics, and that is the deployment of advanced analytics methodologies to enormous volumes of data, may deliver such value. It article looks at some of the numerous analytics concepts and methods that may be utilized utilizing massive data, or the prospects that data analytics might provide in many decision domains.
Downloads
References
. Z.-H. Zhou, “Three perspectives of data mining,” Artif. Intell., 2003, doi: 10.1016/s0004-3702(02)00357-0. [2]. J. R. M. Hosking, E. P. D. Pednault, and M. Sudan, “A statistical perspective on data mining,” Futur. Gener. Comput. Syst., 1997, doi: 10.1016/s0167-739x(97)00016-2.
. P. Guleria and M. Sood, “Data Mining in Education : A Review on the Knowledge Discovery Perspective,” Int. J. Data Min. Knowl. Manag. Process, 2014, doi: 10.5121/ijdkp.2014.4504.
. S. Kundu and M. L. Garg, “Web Data Mining and Analysis: An Intelligent Perspective,” Int. J. Adv. Sci. Technol., 2017, doi: 10.14257/ijast.2017.105.03.
. X. Wu, X. Zhu, G. Q. Wu, and W. Ding, “Data mining with big data,” IEEE Trans. Knowl. Data Eng., 2014, doi: 10.1109/TKDE.2013.109.
. R. Kruse, D. Nauck, and C. Borgelt, “Data mining with fuzzy methods : status and perspectives introduction : data mining,” Proc. 7th Eur. Congr. Intell. Tech. Soft Comput. (EUFIT’99)., 1999.
. N. Elgendy and A. Elragal, “Big Data Analytics in Support of the Decision Making Process,” 2016, doi: 10.1016/j.procs.2016.09.251.
. M. Cao, R. Chychyla, and T. Stewart, “Big data analytics in financial statement audits,” Account. Horizons, 2015, doi: 10.2308/acch-51068.
. B. M. Balachandran and S. Prasad, “Challenges and Benefits of Deploying Big Data Analytics in the Cloud for Business Intelligence,” 2017, doi: 10.1016/j.procs.2017.08.138.
. L. D. Roberts, J. A. Howell, K. Seaman, and D. C. Gibson, “Student attitudes toward learning analytics in higher education: ‘The fitbit version of the learning world,’” Front. Psychol., 2016, doi: 10.3389/fpsyg.2016.01959.
