Industry: HealthTech
Challenge: HealthVerity faced challenges with its legacy data ingestion and processing infrastructure. The existing system, built on Airflow with numerous DAGs, was complex, difficult to maintain, and lacked scalability. This hindered their ability to efficiently ingest and analyze vast amounts of health data from diverse sources, limiting their potential to provide valuable insights to healthcare providers and researchers.
Solution: To address these challenges, HealthVerity partnered with Chariot Solutions to modernize their data infrastructure. The following key steps were taken:
- Migration from Airflow to Serverless Framework: The complex Airflow DAGs were replaced with a more scalable and maintainable serverless architecture using AWS Lambda and Step Functions. This improved the efficiency and flexibility of data ingestion pipelines.
- Development of React Frontend Applications: User-friendly React applications were developed to replace the Airflow Flask Admin plugins, providing Data Engineers and Analysts with intuitive interfaces for submitting and monitoring data tasks.
- Implementation of Data Quality Checks: Great Expectations test suites were integrated into the data pipelines to ensure the accuracy and reliability of incoming data, enabling proactive identification and resolution of data quality issues.
- Transition to Databricks and S3: The data storage and processing infrastructure was migrated from Hive to Databricks, leveraging the power of Spark for large-scale data analysis. Parquet schemas were used for efficient data storage in S3.
Results: The modernization of HealthVerity’s data infrastructure resulted in significant improvements in their ability to ingest, process, and analyze health data:
- Improved Scalability and Performance: The serverless architecture and Databricks infrastructure enabled HealthVerity to handle increasing volumes of data with greater efficiency and scalability.
- Enhanced Data Quality: The implementation of data quality checks using Great Expectations improved the accuracy and reliability of data, leading to more trustworthy insights.
- Increased User Productivity: The intuitive React frontend applications streamlined data submission and monitoring processes, empowering Data Engineers and Analysts to work more efficiently.
- Accelerated Time-to-Insights: The modernized infrastructure enabled HealthVerity to generate insights from health data more quickly, facilitating faster decision-making and innovation.
Conclusion: By modernizing their data infrastructure, HealthVerity overcame the challenges associated with legacy systems and unlocked the full potential of their health data. The improved scalability, data quality, user productivity, and time-to-insights enabled them to deliver more value to their customers and drive innovation in the HealthTech industry. This case study demonstrates the transformative impact of modern data engineering practices in the healthcare sector.