Real-Time Health Data Analytics Platform with Advanced Data Engineering

Our SME company, operating in the Health Technology industry, is looking to develop an advanced real-time health data analytics platform. The platform's primary goal is to integrate disparate health data sources, such as EHRs, IoT health devices, and patient feedback systems, into a cohesive analytics environment. By leveraging technologies like Apache Kafka for event streaming and Spark for processing, we aim to create a system capable of real-time data ingestion and analytics. The solution will also utilize Airflow for orchestration, dbt for data transformation, and Snowflake or BigQuery for storage. The platform must be designed to support MLOps for deploying machine learning models that can predict health outcomes and assist in decision-making. This initiative supports our vision of enabling healthcare providers to respond rapidly to patient needs, ultimately improving patient outcomes and operational efficiency.