Real-Time Data Pipeline for Enhanced Patient Care in Dental Practices

As a rapidly growing dental care service provider, we face the challenge of optimizing patient outcomes and clinic operations. This project will establish a robust data pipeline that enables real-time data streaming and analysis across our network of clinics. Utilizing technologies such as Apache Kafka for event streaming, Spark for processing, and Airflow for orchestration, the project will integrate data from various sources into a cohesive mesh. The data will be stored in Snowflake and BigQuery for scalable analytics, while dbt will provide transformation capabilities. The insights derived will be pivotal in tailoring patient interactions, improving treatment plans, and enhancing overall clinic efficiency. Moreover, implementing Databricks MLOps will ensure seamless deployment of machine learning models to predict patient needs and optimize resource allocation. This initiative is crucial for maintaining our competitive edge by transforming data into a strategic asset.