With the rise in globalization rates, the amount of information needed to be processed has increased exponentially. As a result, the concept of Big Data has emerged in the Business context. By definition, Big Data denotes data sets that come in tremendous volumes and reveal essential trends in the target area when analyzed (Mittal et al., 2018). Specifically, information concerning the patterns of behaviors and changes in attitudes is covered by the concept of Big Data, suggesting that the latter provides the Basis for market research.
As a rule, Big Data is opposed to the concept of traditional data due to the differences in their structures. While the traditional data is arranged using the centralized principle of information architecture, the Big Data arrangement is based on the notion of distributed architecture. The latter suggests that information flow is managed based on a logical and physical structure that defines the key stages of information processing and its further distribution (Sedkaoui et al., 2021). The specified method allows for managing extraordinarily high data volumes.
Implementing Big Data suggests having several advantages readily available. The possibility of managing tremendous amounts of information is the most obvious benefit that the Big Data framework provides. As a result, key trends within the target set are identified with higher precision, which leads to improved and more accurate decision-making. As a result, fewer resources are wasted, which causes the level of expense to drop (Sedkaoui et al., 2021). However, the existing strategies for collecting Big Data may conflict with the concepts of privacy and personal data security (Mittal et al., 2018). Therefore, Big Data must be collected with due caution.
Using Big Data requires the presence of a specific cause; otherwise, the resources spent on the process may not return the expected profits. Typically, the adjustment of e-commerce processes, automation of the recruitment process, and enhanced scanning for the threat of insurance fraud are seen as the justifications for applying the Big Data analysis to the corporate context.
References
Mittal, M., Balas, V. E., & Hemanth, D. J. (Eds.). (2018). Data intensive computing applications for The Big Data (vol. 29). IOS Press.
Sedkaoui, S., Khelfaoui, M., & Kadi, N. (Eds.). (2021). Big Data analytics: Harnessing data for new business models. CRC Press.