BIG DATA ANALYTICS: A PRIMER
DOI:
https://doi.org/10.29121/ijetmr.v5.i9.2018.287Keywords:
Big Data, Big Data Analytics, Advanced AnalyticsAbstract
The use of digital devices and systems such smart phones, computers, the Internet, and social media has resulted in a massive volume of data which is exponentially increasing daily. Such data is processed using multiple techniques, collectively known as big data analytics. Big data analytics is the process of examining large amounts of data (big data) to uncover hidden patterns, correlations, and other insights. Analyzing big data enables organizations and businesses to make better and faster decisions. This paper briefly presents the fundamental concepts of big data analytics and its tools.
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Song, I.Y & Zhu, Y. 2016. Big data and data science: what should we teach?” Expert Systems, 33, no. 4, August 2016, pp. 364-373. DOI: https://doi.org/10.1111/exsy.12130
Sadiku, M.N., Nelatury, S.K & Musa, S.M. 2017. Wireless Big Data. Journal of Scientific and Engineering Research, vol. 4, no. 9, 107-110.
Yaqoob et al. (2016). Big data: from beginning to future. International Journal of Information Management, 36, 1231-1247. DOI: https://doi.org/10.1016/j.ijinfomgt.2016.07.009
Sadiku, M.N.O, Shadare, A.E. & Musa, S.M. 2015. Data mining: a brief introduction. European Scientific Journal, 11, no. 21, 509-513.
Sadiku, M.N.O., Musa, S.M. & Musa, O.M. 2017. Data mining in the chemical industry. International Journal of Trend in Research and Development, 4, no. 6, 295-296.
Gupta, R. (2014) Journey from data mining to web mining to big data. International Journal of Computer Trends and Technology, 10, no. 1,18-20. DOI: https://doi.org/10.14445/22312803/IJCTT-V10P104
Mohata,P.B. (2015). Web data mining techniques and implementation for handling big data. International Journal of Computer Science and Mobile Computing, 4, no. 4, 330-334.
Sadiku, M.N.O, Musa, S.M. and Musa, O.S. (2017). Machine Learning. International Research Journal of Advanced Engineering and Science, 2, no. 4, 2017, 79-81.
L’Heureux, A. et al. 2017. Machine learning with big data: challenges and approaches. IEEE Access, 5, 2017, 7776-7797. DOI: https://doi.org/10.1109/ACCESS.2017.2696365
Sadiku, M.N.O., Tembely, M. and Musa, S.M. (2017). Deep learning. International Research Journal of Advanced Engineering and Science, 2, no. 1, 77-78.
Chen, H., Chian, R.H.L. & Storey, V.C. 2012. Business intelligence and analytics: from big data to big impact. MIS Quarterly,36, no. 4, 1165-1188. DOI: https://doi.org/10.2307/41703503
Raghupathi, W. and Raghupathi, V. (2014). Big data analytics in healthcare: promise and Potential. Health Information Science and Systems, 2, no.3. DOI: https://doi.org/10.1186/2047-2501-2-3
He, Y. (2016). Big data analytics in mobile cellular networks. IEEE Access, 4, 1985-1996. DOI: https://doi.org/10.1109/ACCESS.2016.2540520
SAS. (2017). Big data analytics: What it is and why it matters. https://www.sas.com/en_us/insights/analytics/big-data-analytics.html
Malaka, I. and Brown, I. (2015). Challenges to the organizational adoption of big data analytics: A case study in the South African telecommunications industry. Proceedings of the 2015 Annual Research Conference on South African Institute of Computer Scientists and Information Technologists. DOI: https://doi.org/10.1145/2815782.2815793
Gahi, Y., Guennoun, M. and Mouftah, H.T. (2016). Big Data Analytics: security and Privacy Challenges. Proceeding of IEEE Symposium on Computers and Communication. DOI: https://doi.org/10.1109/ISCC.2016.7543859
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