Leveraging Machine Learning for Enhanced Big Data Analysis in Business Markets: A Scrum Master's Perspective


  • Ethan Jack, Joseph Logan Department of Computer Science, Oregon State University


Machine Learning, Big Data Analysis, Business Markets, Scrum Master, Agile Project Management, Decision-Making, Data Insights, Project Execution, Cross-Functional Team, Iterative Development


This study explores the integration of machine learning techniques for enhanced big data analysis within business markets, with a focus on the role of the Scrum Master in orchestrating project execution. Leveraging large-scale datasets inherent to modern business operations, machine learning algorithms offer unprecedented opportunities for extracting actionable insights and driving informed decision-making. The Scrum Master, as a facilitator of agile project management methodologies, plays a pivotal role in ensuring the successful implementation of machine learning solutions. Through effective coordination of cross-functional teams and iterative development cycles, the Scrum Master enables businesses to harness the full potential of machine learning in optimizing operations, enhancing customer experiences, and driving sustainable growth. This paper highlights the key challenges and considerations in leveraging machine learning for big data analysis in business markets from a Scrum Master's perspective, offering insights into best practices and strategies for achieving project success.