FastAPI
Data Services
dbt
Fabric Models
MLflow
Experiment Tracking
Semantic
Model Layer
Comprehensive healthcare analytics portfolio demonstrating the full modern data stack for healthcare: FastAPI data services, dbt models on Microsoft Fabric, a semantic model layer, and MLflow for experiment tracking. Built to interview-ready production standard.
Every layer of the modern healthcare data stack — API, transformation, semantic model, ML tracking — in one portfolio.
Tech Stack
PythonFastAPIdbtMicrosoft FabricMLflowPydanticSQLAzure
Features
FastAPI Services
REST APIs for clinical data access with Pydantic validation and OpenAPI docs.
dbt on Fabric
dbt transformation models running on Microsoft Fabric — modern lakehouse pattern.
Semantic Model
Business-logic layer decoupling BI queries from raw SQL. Self-service analytics ready.
MLflow Tracking
Experiment tracking for clinical ML models: params, metrics, artifacts, model registry.
How It Works
01
Ingest
Clinical data → Microsoft Fabric lakehouse via Python pipelines
→
02
Transform
dbt models on Fabric: staging → marts → semantic layer
→
03
Serve
FastAPI services expose semantic model to downstream consumers
→
04
Track
MLflow logs all model experiments, metrics, and artifacts