1 School of Business, Department of Computer Management Information System, Southern Illinois University, Edwardsville, USA.
2 School of Earth, Environment and Sustainability, Georgia Southern University, USA.
3 Independent Researcher, USA.
4 Department of Mathematics, University of Louisiana at Lafayette, USA.
5 Mechanical Engineering Department, Teesside University, United Kingdom.
6 Mathematics and Statistics Department, Washington State University, USA.
7 School of Technology, University of Central Missouri, MO, USA.
World Journal of Advanced Research and Reviews, 2024, 23(01), 472–480
Article DOI: 10.30574/wjarr.2024.23.1.2010
DOI url: https://doi.org/10.30574/wjarr.2024.23.1.2010
Received on 26 May 2024; revised on 02 July 2024; accepted on 04 July 2024
Data-driven decision-making (DDDM) has become a cornerstone in modern IT and business landscapes, leveraging the immense potential of artificial intelligence (AI) and data science to transform raw data into actionable insights. This review paper explores the intersection of these domains, highlighting methodologies, applications, benefits, and challenges associated with integrating AI and data science into business intelligence (BI). Through an extensive review of current literature, this paper elucidates how organizations can harness these technologies to drive strategic decisions, optimize operations, and maintain a competitive edge.
Artificial Intelligence; Business Intelligence; Data Science; Data Analytics
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Comfort Idongesit Michael, Oluwaseun Johnson Ipede, Adejoke Deborah Adejumo, Ibrahim Oyeyemi Adenekan, Damilola Adebayo, Adefisayo Simon Ojo and Praise Ayomide Ayodele. Data-driven decision making in IT: Leveraging AI and data science for business intelligence. World Journal of Advanced Research and Reviews, 2024, 23(01), 472–480. Article DOI: https://doi.org/10.30574/wjarr.2024.23.1.2010
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0