Business Intelligence-Driven Cybersecurity for Operational Excellence: Enhancing Threat Detection, Risk Mitigation, and Decision-Making in Industrial Enterprises

Abstract

The world of Industry 4.0 is becoming more interconnected, relying increasingly on data-driven processes and making more innovative use of automation by industrial enterprises. Even though these innovations boost productivity and operational visibility, they present vulnerable infrastructures with intricate and emerging cybersecurity threats. This paper examines the integration of business intelligence (BI) systems within cybersecurity activities with the aim of operational excellence. Using the power of BI to analyze and visualize raw security data, organizations can transform it into tangible insights, enabling them to detect threats proactively, mitigate them effectively, and make decisions based on data. The study adopts a mixed-method design that integrates quantitative research of industrial cybersecurity data sets with qualitative information from security experts. The research results show that BI-based cybersecurity systems enhance the speed and accuracy of incident detection, minimize exposure to vulnerabilities, and increase the accuracy of decisions on the managerial and operational levels. Moreover, the analysis presents an idea scheme that shows the synergistic interaction between BI instruments, predictive analytics, and industrial cybersecurity controls. This framework facilitates the creation of stronger and more adaptive defense mechanisms in the industry. Finally, this paper will have scholarly and practical implications on the industry by showing how BI can help transform cybersecurity management into proactive defense instead of reactive defense, guaranteeing operational excellence and sustainability in the digital age.