Semantic Layer
Creating a unified data abstraction layer that simplifies access to complex healthcare datasets across analytics platforms.
BIG DATA ANALYTICS
DATA PLATFORMS
CLIENT
Blue Health Intelligence (Internal Analytics Platform)
INDUSTRY
Healthcare Analytics
DURATION
18 Months
SERVICES
Data Integration, Stakeholder & Plan Coordination, Data governance and Standardization
The Enterprise Healthcare Analytics Semantic Layer was developed to simplify access to complex healthcare datasets and provide a consistent analytics foundation across the organization’s data ecosystem. By translating raw claims, cost, and utilization data into standardized business definitions, the platform enabled analysts and data scientists to quickly generate insights without navigating complex underlying data structures.
​
Built on a modern cloud data stack including AWS, Databricks, Snowflake, and Airflow, the semantic layer created a unified data abstraction layer supporting multiple analytics platforms and reporting tools. This foundation improved data governance, accelerated analytics development, and enabled more consistent insights across healthcare analytics initiatives.
CLOUD
MODERN DATA ARCHITECTURE
Built on a scalable cloud data stack leveraging AWS, Databricks, Snowflake, and Airflow.
110M
Members represented
The semantic layer standardized access to datasets representing over 110 million insured members across the BCBS network.
BILLIONS
CLAIMS DATA POINTS
Provided a structured abstraction layer over billions of medical and pharmacy claims records within the national data repository.
50%+
FASTER ANALYTICS DEVELOPMENT
Standardized data models significantly reduced the time required for analysts to build reports and dashboards.