FUNDAMENTAL CONCEPTS AND USES OF BIG DATA ANALYTICS

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Khyati Kathuria

Abstract

In the era of the information explosion decision-makers can access vast amounts of data. Big datarefers to datasets that are difficultto manage using traditional tools and techniques. Given the rapid development of these data, solutionsto manage and extract the value and knowledge from these databases should be explored and available. Only Big Data Analytics, which uses advanced big data analysis techniques, can provide the value. The article aims to analyze the fundamentals in big data.

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How to Cite
[1]
Khyati Kathuria, “FUNDAMENTAL CONCEPTS AND USES OF BIG DATA ANALYTICS”, IEJRD - International Multidisciplinary Journal, vol. 4, no. 1, p. 8, Dec. 2018.

References

  1. Bartosik-Purgat, M., &Ratajczak-Mrożek, M. (2018). Big Data Analysis as a Source of Companies' Competitive Advantage: A Review. Entrepreneurial Business and Economics Review, 6(4), 197–215. https://doi.org/10.15678/EBER.2018.060411
  2. Ciasullo, M. V., Troisi, O., Loia, F., &Maione, G. (2018). Carpooling: travelers’ perceptions from a big data analysis. The TQM Journal, 30(5), 554–571. https://doi.org/10.1108/TQM-11-2017-0156
  3. Duponchel, L. (2018). Exploring hyperspectral imaging data sets with topological data analysis. AnalyticaChimicaActa, 1000, 123–131. https://doi.org/10.1016/j.aca.2017.11.029
  4. Jamshidi, A., Faghih‐Roohi, S., Hajizadeh, S., Núñez, A., Babuska, R., Dollevoet, R., Li, Z., &Schutter, B. (2017). A Big Data Analysis Approach for Rail Failure Risk Assessment. Risk Analysis, 37(8), 1495–1507. https://doi.org/10.1111/risa.12836
  5. JuusoEsko K. (2018). Smart Adaptive Big Data Analysis with Advanced Deep Learning. Open Engineering (Warsaw), 8(1), 403–416. https://doi.org/10.1515/eng-2018-0043
  6. Kamilaris, A., Kartakoullis, &Prenafeta-Boldú (2017). A review on the practice of big data analysis in agriculture. Computers and Electronics in Agriculture, 143(C), 23–37. https://doi.org/10.1016/j.compag.2017.09.037
  7. Rahul Reddy Nadikattu. 2016 THE EMERGING ROLE OF ARTIFICIAL INTELLIGENCE IN MODERN SOCIETY. International Journal of Creative Research Thoughts. 4, 4 ,906-911.
  8. Rahul Reddy Nadikattu. 2017. The Supremacy of Artificial intelligence and Neural Networks. International Journal of Creative Research Thoughts, Volume 5, Issue 1, 950-954.
  9. Kruschke, J., & Liddell, K. (2018). Bayesian data analysis for newcomers. Psychonomic Bulletin & Review, 25(1), 155–177. https://doi.org/10.3758/s13423-017-1272-1
  10. Li, X., Wang, L., Lian, Z., & Qin, X. (2018). Migration-Based Online CPSCN Big Data Analysis in Data Centers. IEEE Access, 6, 19270–19277. https://doi.org/10.1109/ACCESS.2018.2810255
  11. Roh, S. (2017). Big Data Analysis of Public Acceptance of Nuclear Power in Korea. Nuclear Engineering and Technology, 49(4), 850–854. https://doi.org/10.1016/j.net.2016.12.015
  12. Schramm, S. (2017). Data analysis meets quantum physics. Nature, 550(7676), 339–340. https://doi.org/10.1038/550339a
  13. Thorstad, R., & Wolff, P. (2018). A big data analysis of the relationship between future thinking and decision-making. Proceedings of the National Academy of Sciences of the United States of America, 115(8), E1740–E1748. https://doi.org/10.1073/pnas.1706589115
  14. Wang, Kewei, Wang, Wenji, & Li, Mang. (2018). A brief procedure for big data analysis of gene expression. Animal Models and Experimental Medicine, 1(3), 189–193. https://doi.org/10.1002/ame2.12028

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