Project Management Strategies for Integrating Machine Learning into Business Analytics Initiatives

Abstract

This paper explores project management strategies for effectively integrating machine learning (ML) into business analytics initiatives. As ML continues to revolutionize data analysis and decision-making processes, organizations face challenges in successfully implementing ML projects within their existing frameworks. Drawing on principles of project management, this study examines key strategies for overcoming these challenges and maximizing the value of ML in business analytics. Through a comprehensive review of literature and case studies, we identify best practices, methodologies, and frameworks for managing ML projects, emphasizing the importance of collaboration, communication, and adaptability in achieving project success. This research contributes to the evolving discourse on the intersection of ML and project management, providing practical insights and guidance for organizations navigating the complexities of integrating ML into their analytics strategies.