Harnessing machine learning in business analytics for enhanced decision-making
International Institute of Business Analysis, , Trine University, USA.
Research Article
World Journal of Advanced Engineering Technology and Sciences, 2024, 12(02), 674–683.
Article DOI: 10.30574/wjaets.2024.12.2.0341
Publication history:
Received on 02 July 2024; revised on 08 August 2024; accepted on 10 August 2024
Abstract:
In the contemporary business landscape, the integration of machine learning (ML) with business analytics has emerged as a pivotal strategy for enhancing decision-making processes. This research investigates the role of machine learning in refining business analytics, aiming to demonstrate how advanced algorithms can be harnessed to derive actionable insights and improve organizational outcomes. The study explores the theoretical foundations of machine learning and business analytics, evaluates current applications, and identifies gaps in the existing literature. Through a mixed-methods approach, incorporating both quantitative and qualitative data, the research provides a comprehensive analysis of how ML techniques can be effectively employed to address complex business challenges. The findings reveal that machine learning significantly enhances the accuracy and efficiency of business analytics, leading to more informed and strategic decision-making. The study concludes with practical recommendations for businesses seeking to leverage machine learning and outlines directions for future research in this evolving field.
Keywords:
Machine Learning; Business Analytics; Decision-Making; Data-Driven Insights; Predictive Analytics; Prescriptive Analytics; Algorithmic Techniques; Business Strategy; Data Science
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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