Observed Signal · May 23, 2026 · Open-source Project · Source: DEV Community · Impact: 2/5 · Sentiment: Positive
Open-source African Economic ETL with DuckDB & Python
AfriData Pipeline is an open-source ETL project that extracts World Bank economic indicators for all 54 African countries, loads them into a DuckDB analytical warehouse, and serves a static interactive dashboard. Built with Python (httpx), DuckDB, and the World Bank API v2, the pipeline processes ~13,500 data points (54 countries × 10 indicators × 25 years) in under 50 seconds, computes year-over-year changes, and applies automated data-quality checks (completeness, validity, freshness) yielding a final score of 95.8/100. The dashboard is a static site (Chart.js, Leaflet.js, Tailwind CSS) that reads precomputed JSON files and is auto-deployed via Vercel. A GitHub Actions workflow runs the pipeline daily at 06:00 UTC. Source code and project assets are available on GitHub (hajirufai/afridata-pipeline).
Demonstrates a production-grade, low-cost analytical pipeline and data-quality framework using free public data and DuckDB; relevant to data engineering and analytics teams but not industry-shifting for AdTech.
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Key Takeaways & Evidence Grounding
- Project: AfriData Pipeline — open-source ETL for African economic data
- Stack: Python (httpx), DuckDB, World Bank API v2; dashboard uses Chart.js, Leaflet.js, Tailwind CSS
- Processes ~13,500 data points (54 countries × 10 indicators × 25 years) in under 50 seconds
- Implements a star schema in DuckDB and computes year-over-year change for each data point
- Automated daily refresh via GitHub Actions (scheduled at 06:00 UTC) and static deployment on Vercel
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