NHTSA Vehicle Data Platform

API-driven vehicle safety data project focused on turning NHTSA public recall data into repeatable, dashboard-ready analytical outputs.

The project is scoped around practical data engineering work: ingesting recall records from the public API, shaping them into medallion-style analytical tables, and preparing relational outputs for trend, manufacturer, component, and campaign-level reporting.

Current focus areas:

• NHTSA public recall API ingestion
• Repeatable cleaning and normalization of recall records
• Medallion-style modeling for analytical datasets
• PostgreSQL/Supabase-ready relational structures
• Dashboard-ready outputs for recall, manufacturer, component, and campaign analysis
• Documentation of data design decisions during the 100DayDash challenge

Design notes:

• API ingestion and transformation are separated so raw records can be preserved while modeled tables evolve.
• Medallion-style layers provide a clear path from raw recall data to curated analytical outputs.
• Relational structures support dashboard tools without locking the project to one BI platform.
• Documentation captures tradeoffs and implementation decisions as the project matures.