Harvard Art Museums Data Engineering Pipeline

This is a reference implementation for building a complete data pipeline around the Harvard Art Museums API. You get the full stack: paginated API extraction with rate limiting, ETL transforms that normalize nested JSON into a proper relational schema (separate tables for metadata, media, and color data), and a Streamlit dashboard with 20+ analytical queries and Plotly visualizations. It's overkill if you just want to pull some museum data, but if you're learning data engineering patterns or need to pitch pipeline architecture to stakeholders, having a working example with real API integration, foreign keys, and batch loading is genuinely useful. The code samples are thorough enough to fork and adapt to other APIs.

Install to Claude Code

npx -y skills add aradotso/data-skills --skill harvard-art-museums-data-engineering-pipeline --agent claude-code