Interactive Power BI dashboard analysing internet and mobile adoption across South Africa and Sub-Saharan Africa using World Bank data (2000–2024). Final capstone project.
# Bridging the Digital Divide : Power BI Capstone
An interactive Power BI dashboard analysing internet and mobile adoption across South Africa, five African peers, and three global benchmarks, using 24 years of World Bank data.
Final capstone project for the AnalystLab Africa data analytics internship (Week 8).
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## Problem Statement
Mobile phone ownership across Africa has grown explosively, but internet usage has not kept pace. This project examines that disconnect — why mobile adoption leapfrogged while internet access lagged and identifies what separates the more-connected countries from the less-connected ones.
It answers four questions:
- How wide is the gap between mobile subscriptions and actual internet usage?
- How does South Africa compare to its peers and to global benchmarks?
- What factors : wealth, electricity, infrastructure — explain the differences?
- How many people, in absolute terms, remain offline?
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## Repository Contents
| File | Description |
|---|---|
| `Capstone_Project.pbix` | The interactive Power BI dashboard |
| `Capstone_Report.pdf` | Full written report (objective, methodology, findings, recommendations) |
| `README.md` | This file |
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## Dataset
**Source:** World Bank World Development Indicators (bulk CSV download)
**Scope after cleaning:** 1,264 records — 9 entities × 6 indicators × 25 years (2000–2024).
**Indicators used:**
| Indicator | Code | Role |
|---|---|---|
| Individuals using the internet (%) | `IT.NET.USER.ZS` | Primary connectivity measure |
| Mobile cellular subscriptions (per 100) | `IT.CEL.SETS.P2` | The mobile leapfrog |
| Fixed broadband subscriptions (per 100) | `IT.NET.BBND.P2` | Infrastructure that didn't leapfrog |
| Access to electricity (%) | `EG.ELC.ACCS.ZS` | Physical precondition |
| GDP per capita (US$) | `NY.GDP.PCAP.CD` | Tests wealth as a driver |
| Population, total | `SP.POP.TOTL` | Converts % into people |
**Entities:** South Africa, Nigeria, Kenya, Egypt, Ghana, Rwanda, plus …