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The role of the collection of data and its subsequent analysis in the industry is as big as ever. Specifically, it pertains to the managerial field where the quality and nature of a decision can greatly alter the companys vector of growth and development. The usage of big data helps managers to make better decisions on the basis of evidence rather than intuition (Jeble, 2018, p. 36). With the inception of big data, with its variety of sources, such as the Internet of Things, cloud computing and mobile devices, data analytics came to be a valuable resource for a company in many fields (Davenport, 2014). Thus, its role in managerial decision-making is central, since such a huge asset of information is impossible to ignore.
In addition, all of the top corporations rely on it immensely. Even so, big data is getting bigger (LaValle et al., 2011, p. 29). The possible reasons that smaller companies do not employ data analysis may be associated with the challenges that come with it, difficulty comprehending big data, issues of privacy, as well as ethical considerations relevant to mining Sivarajah, U., et al, 2016, p. 3). Or perhaps, they prefer to rely on the way they have been doing business for years.
My personal experience with data analytics is related to aviation. Despite the fact that big data has entered this field only in recent years, its usage in this industry is quite big. The fact that the aircraft contains a number of sensors that continuously send large datasets all the time, can serve as evidence (Burmester et al., 2018, p. 58). Therefore, I can conclude that the usage of data analytics is already wide in aviation, in spite of remaining a fairly new phenomenon.
Reference List
Burmester, G., Ma, H., Steinmetz, D., & Hartmannn, S (2018) Big Data and Data Analytics in Aviation, Advances in Aeronautical Informatics, pp. 5565
Davenport, T. (2014), Big Data at Work: Dispelling the Myths, Uncovering the Opportunities. Harvard Business Review Press.
Jeble, S., Kumari, S., Patil, Y. (2018) Role of Big Data in Decision Making, Operations and Supply Chain Management, 11(1), pp. 36-44.
LaValle, S., et al. (2011), Big Data, Analytics, and the Path from Insights to Value, MITSloan Management Review, 52(2), pp. 21-31.
Sivarajah, U., Kamal, M., Irani, Z., Weerakkody, V. (2016) Critical analysis of Big Data challenges and analytical methods, Journal of Business Research, pp. 1-24.
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