Healthcare Data Engineering Pipeline

Healthcare Data Engineering Pipeline

A research-based technical case study exploring how healthcare data can be collected, integrated, cleaned, transformed, validated, and prepared for analytics.

The project demonstrates a complete healthcare data engineering workflow, starting from different healthcare data sources such as EHRs, laboratory systems, pharmacy systems, claims, and other healthcare sources, then moving through an ETL pipeline toward structured and analytics-ready data.

The presentation covers real-world healthcare data challenges, data quality, data integration, ETL processes, data warehouses, healthcare interoperability, and the role of Data Engineering in transforming raw healthcare data into usable information.

It is supported by information and examples from authoritative sources including CDC, NIH, ONC, and HL7, with source references provided throughout the presentation.

Key Topics:

Healthcare Data Sources

ETL / Data Pipelines

Data Cleaning & Transformation

Data Quality

Data Integration

Data Warehousing

Healthcare Interoperability

FHIR

Healthcare Analytics

Tools & Concepts: Python, SQL, ETL, Data Pipelines, Data Warehousing, Healthcare Data, FHIR, Data Quality