Risk Management in IT Service Delivery Using Big Data Analytics
DOI:
https://doi.org/10.36676/urr.v10.i2.1330Keywords:
Big Data analytics, IT service delivery, risk management, cybersecurity, predictive analyticsAbstract
Rapid technological innovation has changed IT service delivery, making risk management more complicated. Big Data analytics improves risk management tactics in this scenario. Big Data analytics in IT service delivery allows real-time risk identification, assessment, and mitigation, improving dependability, security, and efficiency. This article examines how Big Data analytics can forecast dangers, optimize decision-making, and improve IT service delivery risk management.
Risk management in IT service delivery includes cybersecurity, data privacy, operational efficiency, and regulatory compliance. Historical data and static models may not represent the dynamic nature of current IT systems in traditional risk management. Big Data analytics can handle massive volumes of organized and unstructured data in real time, making risk management more flexible and proactive. Predictive analytics, machine learning, and data mining help firms see dangers before they become major difficulties. Big Data analytics in risk management provides full IT infrastructure insights. By examining network logs, user activity patterns, and system performance indicators, enterprises may spot abnormalities and security breaches early. This lets IT teams reduce hazards quickly, reducing service disruption. Big Data analytics also allows firms to monitor IT systems continuously and respond to evolving threat environments.
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