Using Machine Learning Techniques in Business Analytics: Lessons from Agile Project Management

Abstract

A potent technique for drawing conclusions from data and advancing corporate analytics is machine learning (ML). Although successful ML project implementation calls for more than simply academic know-how; it also calls for agile approaches, efficient project management, and strategic planning. This study examines the relationship between agile project management and machine learning adoption, offering suggestions for how to include ML throughout business data analysis projects. In the larger context of business analytics, we point out important factors, obstacles, and tactics for streamlining the value of machine learning initiatives by referencing agile methodology principles and best practices. This paper seeks to provide enterprises with the expertise and resources needed to effectively employ machine learning (ML) for business analysis and gain a competitive edge by outlining efficient implementation methodologies.

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