Distributed Data Analytics Platform for MedTech

This case study outlines the development of a distributed data analytics platform for a leading MedTech company, aimed at creating a unified data consortium for clinical researchers. The platform integrates data from various sources, including EMR systems and medical devices, to facilitate high-fidelity data streams from on-premise systems to the cloud. The project addresses challenges such as fragmented data sources, lack of standardized models, and data silos that hinder clinical research. The solution involves building a Health Lakehouse following OHDSI/OMOP principles, employing real-time data streaming using Kafka, and leveraging a scalable analytics framework with Apache Spark. The results indicate enhanced interoperability, improved patient care, and future-proof scalability, allowing for better clinical decisions and faster insights. The case study emphasizes the importance of data quality, security, and compliance in achieving these objectives.