A Medallion Architecture-Based Healthcare Patient Analytics Dashboard Using Databricks

Healthcare organizations generate a large volume of patient-related data every day through hospital systems, medical records, laboratory reports, and treatment activities. Analyzing these large datasets is important for improving patient care, hospital performance, and healthcare decision-making. This paper presents a Healthcare Patient Analytics Dashboard developed using the Databricks Lakehouse Platform and Medallion Architecture for scalable healthcare data processing and analysis. The proposed system processes healthcare datasets through Bronze, Silver, and Gold layers to improve data quality, perform transformation, and generate analytical insights. Interactive dashboards are used to visualize patient demographics, disease distribution, admission trends, treatment outcomes, and hospital performance using various charts and analytical reports. The developed system helps healthcare administrators and medical professionals identify healthcare patterns, monitor operational efficiency, and support data-driven decision-making. Furthermore, this work demonstrates how modern big data technologies and visualization tools can be effectively utilized in the healthcare sector for intelligent analytics and healthcare management. Keywords—Healthcare Analytics; Databricks; Medallion Architecture; Big Data Analytics; Patient Dashboard; Data Visualization; Lakehouse Platform; Healthcare Management