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The Role and Impact of Big Data in Organizational Risk Management

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The Effect of Information Technology on Business and Marketing Intelligence Systems

Abstract

Technological advancement has exposed companies to various risks. With the adoption of technological infrastructures in many companies, various processes have been rendered vulnerable to different forms of threats. Evidence from the current empirical studies on organizational management indicates effective risk assessment is a crucial aspect in any organization. Global technological advancement has equally redefined risk assessment and management strategies. Global leading technology companies such as Apple Inc., Amazon Inc., and Google are leveraging modern technology to unlock hidden data to aid in risk assessment and management. As evidenced in this research report, the use of big data has revolutionized risk assessment in many companies across the world. Big data technology has enabled organizations to collect, store, and assess huge information to aid in risk assessment and management. The processes of risk identification, assessment, mitigation, monitoring, and reporting have been redefined due to the adoption of big data analytical technology. As a result, this research reviews the specific roles played by big data in organizational risks management. The research carries out a comparative case study analysis among three companies that utilize big data in risk management. Specifically, the roles of big data technology in risk management at Apple Inc., Amazon Inc., and at Google are identified. Results from this comparative analysis are used in formulating recommendations for various organizations that desire to adopt big data analytical technology in risk management.

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El Khatib, M. et al. (2023). The Role and Impact of Big Data in Organizational Risk Management. In: Alshurideh, M., Al Kurdi , B.H., Masa’deh, R., Alzoubi , H.M., Salloum, S. (eds) The Effect of Information Technology on Business and Marketing Intelligence Systems. Studies in Computational Intelligence, vol 1056. Springer, Cham. https://doi.org/10.1007/978-3-031-12382-5_117

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