Machine Learning Applications in Database Management Enhancing Performance and Insights

Abstract

The primary objective of this research is to explore the incorporation of machine learning techniques into database management systems to improve performance and foster intelligent insights. The research was conducted using qualitative research methodology. The data was collected through an extensive literature review, case study, and expert interview. Thematic and comparative methods were used to analyze themes such as query optimization, anomaly detection, data cleaning, and predictive analytics. The finding is likely to show that ML has a notably positive impact in improving DBMS performance metrics, and database quality showing the potential of transforming database management.