Advanced data analytics and business intelligence: Building resilience in risk management

Chioma Susan Nwaimo 1, Adetumi Adewumi 1, * and Daniel Ajiga 2

1 Independent Researcher, Illinois, USA.
2 Independent Researcher, Seattle, USA.
 
Review
International Journal of Science and Research Archive, 2022, 06(02), 336–344.
Article DOI: 10.30574/ijsra.2022.6.2.0121
Publication history: 
Received on 18 April 2022; revised on 08 June 2022; accepted on 12 June 2022
 
Abstract: 
This paper explores the transformative role of advanced data analytics, business intelligence (BI), and artificial intelligence (AI) in enhancing risk management strategies for organizations navigating digital transformation and cybersecurity challenges. It examines how predictive analytics enables the early identification and mitigation of risks, empowering businesses to adopt proactive measures. The integration of BI tools is highlighted for their ability to support strategic decision-making under uncertainty through data visualization, scenario planning, and real-time insights. Additionally, the paper underscores the revolutionary impact of AI in cybersecurity frameworks, including automated anomaly detection and rapid response to emerging threats. Future trends such as explainable AI and AI-driven threat intelligence are discussed, emphasizing their potential to reshape risk management practices. The paper concludes with practical recommendations for organizations aiming to build resilience by adopting these technologies and fostering a data-driven culture.
 
Keywords: 
Data Analytics; Business Intelligence; Artificial Intelligence; Risk Management; Cybersecurity; Digital Transformation
 
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Copyright © 2022 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0