ahmedmajid22/libya-open-data-platform

--- **Star this repo · Download the data · Open the dashboard** --- ## 🇱🇾 The Problem > Open data about Libya is fragmented, inconsistent, and buried across international databases. > A researcher shouldn't need days to get a clean table of GDP and population figures. This project solves that — once, permanently, automatically. --- ## ◈ What Happens Every Monday ``` 06:00 UTC — GitHub Actions wakes up │ ▼ ┌─────────────────────────────────────────────────────┐ │ STEP 1 · EXTRACT │ │ Python calls the World Bank API │ │ 5 indicators × 24 years = 23 data rows │ └──────────────────────┬──────────────────────────────┘ │ ▼ ┌─────────────────────────────────────────────────────┐ │ STEP 2 · LOAD │ │ Raw data lands in BigQuery raw.raw_worldbank │ └──────────────────────┬──────────────────────────────┘ │ ▼ ┌─────────────────────────────────────────────────────┐ │ STEP 3 · TRANSFORM │ │ dbt builds staging.stg_worldbank (view) │ │ dbt builds mart.fact_libya_yearly_metrics (table) │ └──────────────────────┬──────────────────────────────┘ │ ▼ ┌─────────────────────────────────────────────────────┐ │ STEP 4 · TEST │ │ 13 data quality checks run │ │ Any failure = pipeline stops. No bad data ships. │ │ All pass = continue │ └──────────────────────┬──────────────────────────────┘ │ ▼ ┌─────────────────────────────────────────────────────┐ │ STEP 5 · PUBLISH │ │ CSV exported → committed to /data with timestamp │ │ Anyone in the world can now download clean data │ └─────────────────────────────────────────────────────┘ ``` --- ## ◈ Data Warehouse Architecture | Layer | Dataset | Object | Type | Role | |:---:|:---:|:---:|:---:|:---| | Raw | `raw` | `raw_worldbank` | **Table** | …