Implementing machine learning models in business analytics: challenges, solutions, and impact on decision-making

Toluwalase Vanessa Iyelolu 1, * and Patience Okpeke Paul 2

1 Financial analyst, Texas USA.
2 Henry Jackson Foundation Medical Research International Ltd/Gte, Nigeria.
Review Article
World Journal of Advanced Research and Reviews, 2024, 22(03), 1906–1916
Article DOI: 10.30574/wjarr.2024.22.3.1959
Publication history: 
Received on 20 May 2024; revised on 26 June 2024; accepted on 28 June 2024
This research paper explores the challenges, solutions, and impact of implementing machine learning (ML) models in business analytics. It delves into the complexities of integrating ML into decision-making processes, addressing data quality, technical infrastructure, organizational dynamics, and ethical considerations. Analyzing emerging trends and strategic recommendations, the paper provides insights for businesses seeking to leverage ML for enhanced decision-making and competitive advantage. Examining case examples and discussing future directions underscores the transformative potential of ML in reshaping industries and unlocking new opportunities for growth and success.
Machine Learning; Business Analytics; Decision-Making
Full text article in PDF: 
Share this