The advancement of Internet of Things (IoT), economic globalization, consumer satisfaction and competitive advancements have stimulated companies to transform significantly. In that regard, competitive rivalry among various firms is being replaced by the existing rivalry among businesses and their various enterprises. In the present competitive environments, enterprise experts are focusing on dealing with Big Data (BD) to reach agile, effective, efficient and integrated enterprises. Therefore, explosive development in volume and several data types in the business have presented the need to establish technological advancements that can quickly and intelligently assess large sets of data. The concept of Data Analytics (DA) is one of the most effective remedies that can assist firms to overcome challenges. DA provides an instrument for retrieving insightful data and patterns in massive volumes of information. In that case, this study explores the usage of DA.
Keywords
Big Data (BD), Data Analytics (DA), Internet of Things (IoT)
J. Walters and J. Kleijnen, "Statistical Techniques in Simulation", Operational Research Quarterly (1970-1977), vol. 27, no. 2, p. 518, 1976. Available: 10.2307/3008825.
P. Mabry, X. Yan, V. Pentchev, R. Van Rennes, S. McGavin and J. Wittenberg, "CADRE: A Collaborative, Cloud-Based Solution for Big Bibliographic Data Research in Academic Libraries", Frontiers in Big Data, vol. 3, 2020. Available: 10.3389/fdata.2020.556282.
V. Gudipati and E. Cha, "Target reliability index optimization framework for multiple building classes based on community-level objectives", Structural Safety, vol. 91, p. 102097, 2021. Available: 10.1016/j.strusafe.2021.102097.
J. YENSEN, "Complete Report of Descriptive and Inferential Statistics Requested", Nursing Research, vol. 28, no. 2, p. 80, 1979. Available: 10.1097/00006199-197903000-00004.
D. Fournii, "A Self-Contained Framework for Replication with Funded Assets", SSRN Electronic Journal, 2016. Available: 10.2139/ssrn.2755746.
H. Anandakumar and K. Umamaheswari, “Supervised machine learning techniques in cognitive radio networks during cooperative spectrum handovers,” Cluster Computing, vol. 20, no. 2, pp. 1505–1515, Mar. 2017.
H. Anandakumar and K. Umamaheswari, “A bio-inspired swarm intelligence technique for social aware cognitive radio handovers,” Computers & Electrical Engineering, vol. 71, pp. 925–937, Oct. 2018. doi:10.1016/j.compeleceng.2017.09.016
D. Yu and L. Deng, "Deep Learning and Its Applications to Signal and Information Processing [Exploratory DSP", IEEE Signal Processing Magazine, vol. 28, no. 1, pp. 145-154, 2011. Available: 10.1109/msp.2010.939038.
R. Ohta, "Selection Of Industrial Maintenance Strategy: Classical Ahp And Fuzzy Ahp Applications", International Journal of the Analytic Hierarchy Process, vol. 10, no. 2, 2018. Available: 10.13033/ijahp.v10i2.551.
S. Salahi and S. Bahramara, "Modeling Operation Problem of Micro-grids Considering Economical, Technical and Environmental issues as Mixed-Integer Non-Linear Programming", International Journal of Renewable Energy Development, vol. 5, no. 2, pp. 139-149, 2016. Available: 10.14710/ijred.5.2.139-149.
R. Lee and S. Brown, "Evaluating the Role of Behaviour and Social Class in Electric Vehicle Adoption and Charging Demands", SSRN Electronic Journal, 2020. Available: 10.2139/ssrn.3724667.
S. Mathrani and X. Lai, "Big Data Analytic Framework for Organizational Leverage", Applied Sciences, vol. 11, no. 5, p. 2340, 2021. Available: 10.3390/app11052340.
Z. Azough, A. Benomar and M. Bellafkih, "Data Analytics Applied to Scholarly Data Moroccan Research Trends", SSRN Electronic Journal, 2018. Available: 10.2139/ssrn.3187031.
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Zlatan Stojkovic
Zlatan Stojkovic
School of Electrical Engineering, University of Belgrade, Address: 1 Studentski trg, 1000 Belgrade.
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Zlatan Stojkovic, “Big Data Analytics and Natural Data Design for Enterprise Management”, Journal of Computing and Natural Science, vol.1, no.3, pp. 093-099, July 2021. doi: 10.53759/181X/JCNS202101014.
