Abstract :
Abstract This paper explores project management strategies essential for the successful integration of machine learning (ML) and big data analytics (BDA) in business operations. As ML and BDA continue to revolutionize industries across the globe, effective project management becomes paramount to ensure smooth implementation and maximize the benefits. The paper identifies key challenges faced during integration, such as data quality issues, talent acquisition, and cultural resistance, and proposes practical strategies to address them. Drawing from existing literature and real-world case studies, the paper outlines a comprehensive approach encompassing project planning, stakeholder engagement, resource allocation, risk management, and performance evaluation. By adopting these strategies, organizations can navigate the complexities of ML and BDA integration, optimize operational efficiency, and drive sustainable business growth in the era of data-driven decision-making.
Keyword :
Keywords: Project Management, Machine Learning, Big Data Analytics, Integration, Business Operations, Data Quality, Stakeholder Engagement, Resource Allocation, Risk Management, Performance Evaluation