7 Data Analyst Portfolio Projects Using Real Nigerian Data (2026)

By Bill Achusim · Aug 14, 2026

Hiring managers in Lagos, Abuja and Port Harcourt skim portfolios in about ninety seconds. Certificates do not survive that skim. A dashboard answering a question their business actually has does.

These seven projects use free, public Nigerian data. Build three well rather than seven poorly.

1. Inflation and food price tracker

Data: National Bureau of Statistics CPI and selected food price releases. Build: A Power BI dashboard tracking staple prices by state over 24 months, with a month-on-month change indicator. Why it works: Every retailer, restaurant and manufacturer in Nigeria is pricing against this data.

2. Bank customer churn analysis

Data: Public churn datasets, relabelled to a Nigerian retail banking context. Build: Cleaning in SQL, exploration in Python, a churn probability model, and a one-page summary of the three drivers management should act on. Why it works: It proves you can move from model output to a business recommendation.

3. Lagos transport and traffic insight

Data: Open transport datasets and route timing you can collect yourself. Build: Peak-hour analysis with a recommendation on dispatch scheduling. Why it works: Logistics is one of the fastest-hiring analytics sectors in Nigeria.

4. Health facility access map

Data: Nigeria health facility registry. Build: A geographic dashboard showing facilities per 100,000 people by local government area. Why it works: Mapping skills are rare, and NGOs and state governments hire for exactly this.

5. E-commerce sales and returns dashboard

Data: Your own sales sheet, a friend's shop, or a synthetic dataset you document as synthetic. Build: Revenue, margin, return rate and repeat-customer cohorts, refreshed automatically. Why it works: It is the most common analyst brief in Nigerian retail.

6. Job market skills analysis

Data: Job listings scraped from public boards, including our own careers board. Build: Which tools appear most in Nigerian tech adverts, trended monthly. Why it works: Self-referential and instantly interesting to any recruiter reading it.

7. Agricultural yield and rainfall correlation

Data: Open agricultural and climate datasets. Build: Correlation analysis by state with a clear caveat section on data quality. Why it works: Agritech funding in Nigeria keeps growing and analysts are scarce.

How to present each project

Every project needs four things: the business question in one sentence, the data source with a link, the deliverable (dashboard screenshot or notebook), and the recommendation. Publish on GitHub with a readable README and, where possible, a live Power BI or Looker Studio link.

Do not skip data quality

Nigerian public data is often incomplete. Say so. A section explaining what you cleaned, what you dropped, and what you could not verify signals more seniority than a flawless-looking chart.

Our Data Science & Analytics department builds these exact projects with review from working analysts, covering Excel, SQL, Power BI, Tableau and Python across 12 to 16 weeks. See the full curriculum and salary bands on the department page.