How uses analytics to improve health outcomes
summary
An insurer with 45 million members and 117 million covered lives processes 700–800 million claims a year and moves core analytics to AWS by building a metadata-driven ETL orchestration that lands data in S3 then routes workloads to Redshift, Snowflake, Glue, Lambda and Elastic. The team migrates petabytes (initial bulk via AWS import devices), publishes a Snowflake-backed enterprise data lake, pushes 50 large applications to cloud in a year, and enforces tokenization and cataloging via Informatica.
AI-written summary · about
chapters (5)
- 0:00Start
- 0:25Anthem introduction
- 8:21The data platform
- 11:12Anthem enterprise data lake
- 15:32ETL orchestration
related talks
29mHow financial services companies derive greater value from data with AWS
21mOptimizing data delivery for faster, better analytical insights
44mBest practices for analytics and generative AI on AWS(ANT302)
26mAccelerating innovation in the healthcare and life sciences industry
22mHow Rocket Companies modernized their data strategy on AWS
52mPreparing data for reporting, ML, and AI on AWS
22mBuilding Predictive Analytics Data Warehouses in Healthcare
36mNew trends in data modernization: Catalysts for AI/ML analytics on AWS