Abstract :
Abstract This paper explores the utilization of machine learning (ML) techniques in business analytics from the perspective of a Scrum Master. By leveraging agile methodologies and ML algorithms, organizations can enhance their data-driven decision-making processes. The Scrum Master, as a facilitator of agile practices, plays a crucial role in orchestrating cross-functional teams to extract actionable insights from data and drive business value. Through a combination of case studies and theoretical insights, this paper elucidates the integration of ML into agile frameworks, highlighting best practices and challenges encountered in real-world scenarios. The study underscores the importance of collaboration, adaptability, and continuous improvement in harnessing the power of ML for business analytics in dynamic and competitive environments.
Keyword :
Keywords: Machine Learning, Business Analytics, Scrum Master, Agile Methodologies, Data-Driven Decision Making, Cross-Functional Teams