A large regional health plan accelerated decision-making and business agility by 70% using Snowflake Cloud Data Warehouse.
Health payers are demanding more complex data processing systems to diversify the information they consume, enable analytics and supply downstream feeds. To leverage data insights for effective preventative care of their insureds, health payers need to solve a host of data problems – including capture, cleansing, storage, stewardship, exploration, reporting, visualization, and security – while keeping that data easily shareable.
Tools and Technology
The client – a health payer – developed a pipeline to migrate historical and incremental data loads to Snowflake and perform ELT using SNOWPIPE, Streams, Tasks, and Procedures. The solution uses AWS S3 for storage, Athena and Jupyter Notebooks for data lake and exploration, AWS Glue for metadata cataloging, and AWS Logging, CloudTrail, and QuickSight for auditing and logging.
The key factors for success were building a data validation pipeline inside Snowflake to perform daily data load validations and creating documentation to support the knowledge transfer between the client’s teams. Dividing the project into multiple workstreams and following an agile methodology also drove considerable success for the client.
The client significantly improved its ability to analyze historical data with their cloud-based solution, scaling that data more expansively and efficiently than ever before, while seamlessly connecting with their existing tools and delivering hard, actionable insights from real-time reporting.
[...The] newly-built solution enabled the client to process data 85% faster and improved speed to analytics by 70%.