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Mistrust for Results of Big Data and Possible Solutions Essay

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Updated: Sep 16th, 2022

In the contemporary world, the methods of statistical analysis are being continuously improved. Big Data is a relatively new definition of a comprehensive source of information, which is now possible to analyze due to the appearance of modern technical capacities. Despite being potentially beneficial, the use of Big Data causes public and specialists resistance to some extent. This essay will examine what triggers executives negative opinions regarding Big Data and a possible solution for the issue.

Reasons for Mistrust

Big Data is considered a powerful tool for personalizing messages and offers as well as for deciding global difficulties. However, the number of Big Data challenges using leave concrete reasons for executives to mistrust the analysis results. The first issue is Big Data management, which implies collecting, integrating, and storing a tremendous volume of data from distributed sources on the current technological capacity base (Oussous, 2018). The second significant difficulty is imbalanced Big Data, which means complications in classifying imbalanced dataset. The classical learning techniques are not adapted to imbalanced data sets because the model construction is based on global search measures without considering the number of instances (Oussous, 2018). The third problem is Big Data analytics, which is difficult to conduct. This challenge is attributed to the complex nature of Big Data and the need for scalability and performance to analyze data sets with real-time responsiveness. The abovementioned factors are the primary reasons for the mistrust for the results of such analytics among the executives.

Possible Solutions

Several solutions are successfully applied to overcome Big Data’s challenges. The imbalanced Big Data problem may be solved with methods categorized into two groups: those which extend binary classification techniques to make them applicable, and decomposition and ensemble methods. (Oussous, 2018). The other two problems refer more to the system performance and depend on either technical development or simplification of used analysis techniques. Despite the number of difficulties related to Big Data, there are specific solutions, while new improvements are being invited.

Conclusion

To summarize the challenges related to Big Data using, they are concentrated around data capture, storage, searching, sharing, analyzing, managing, and visualization. Like imbalanced Big Data and technical imperfection, the major reasons still raise mistrust to Big Data among the executives. However, in case of the implementation of constant improvements, Big Data can make even skeptics confident in its reliability.

Reference

Oussous, A., Benjelloun, F. Z., Lahcen, A. A., & Belfkih, S. (2018). Journal of King Saud University-Computer and Information Sciences, 30(4), 431-448. Web.

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IvyPanda. 2022. "Mistrust for Results of Big Data and Possible Solutions." September 16, 2022. https://ivypanda.com/essays/mistrust-for-results-of-big-data-and-possible-solutions/.

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IvyPanda. (2022) 'Mistrust for Results of Big Data and Possible Solutions'. 16 September.

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