Interactive dashboard of 8 public-health indicators across 53 African countries (2000–2022), spotlighting Ghana — live World Bank data, star-schema ETL in R, and a Plotly.js front end.
# Ghana & Africa Health Surveillance Dashboard
An end-to-end analytics project tracking key public-health indicators across **53 African countries (2000-2022)**, with a spotlight on **Ghana** and its West-African peers. Built from live **World Bank Open Data**, modelled as a clean star schema, and visualised in an interactive **Power BI / Tableau** dashboard.
> **The story in one line:** between 2000 and 2022 Ghana's under-5 mortality fell from **99.9 → 38.6** per 1,000, maternal mortality halved (**472 → 239**), malaria incidence more than halved, and life expectancy rose **+7 years**, while health spending per capita grew roughly **8×**.
### 🔗 Live interactive dashboard
**▶ View the live dashboard**, pick an indicator, scrub the year, explore the Africa choropleth, Ghana-vs-peers trend, and country ranking.
*(A self-contained static dashboard, Plotly.js, that needs no server, hosted free on GitHub Pages.)*
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## 📸 Preview
| Ghana's progress over time | West Africa benchmark |
|---|---|
| | |
*(These are validation charts produced in R. The interactive dashboard is built in Power BI / Tableau, see DASHBOARD_GUIDE.md.)*
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## 🎯 What this project demonstrates
- **Data engineering / ETL**, pulling live data from a public REST API, cleaning it, and shaping it into an analytics-ready model (R).
- **Dimensional modelling**, a proper star schema (1 fact + 3 dimension tables) that any BI tool can consume.
- **BI & dashboard design**, KPIs, trends, country benchmarking, and a geospatial choropleth map.
- **Domain insight**, framing the numbers as a public-health narrative, not just charts.
- **Reproducibility**, one script rebuilds the entire dataset from scratch.
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## 🗂️ Repository structure
```
ghana-africa-health-dashboard/
├── 01_extract_worldbank.R # ETL: pull from World Bank API -> clean star schema
├── 02_preview.R # validation / README preview charts
├── 03_build_dashboard_data.R # export the data as docs/data.js for th …