Projects

Practise on business-shaped data.

Four fictional businesses, each with its own dataset and a set of questions a manager would actually ask. Download the CSV files and answer them in SQL, Excel or Power BI, then add the work to your portfolio.

SQLExcelPower BI

Logistics Operations Analysis

Review a freight company's year: who ships the most, which routes run late, and what customers still owe.

Questions to answer

Who are the ten highest-volume customers?
How did monthly shipment volume change?
Which routes are busiest, and how reliable are they?
How much revenue is still unpaid, and by whom?

Dataset: Harbourline Freight (logistics)

A freight company's customers, shipments, routes, payments and staff, January 2025 to August 2026.

This data is used throughout SQL for Data Analysis, with guided lessons and a final project.

ExcelPower BI

Sales Performance Analysis

Find out which products, regions and customer channels drive a distributor's sales, and what its discounts really cost.

Questions to answer

What are monthly sales, and how do they trend?
Which product categories and regions sell the most?
How do wholesale, supermarket and kiosk customers differ?
How much revenue is given away in discounts?

Dataset: Kolanut Distribution (sales)

An FMCG distributor's order lines from January 2025 to June 2026, with its 90 customers (shops, supermarkets and wholesalers across six regions) and 16 products. Prices rose in January 2026.

This data is used throughout Excel for Data Analysis, with guided lessons and a final project.

SQLPower BI

Law Firm Operations Analysis

Look at a Lagos law firm's workload and cash: open matters by practice area, how often hearings are adjourned, and overdue invoices.

Questions to answer

How many matters are open per practice area and lawyer?
What share of hearings end in an adjournment?
Which clients have the most outstanding or overdue invoices?
How long do matters take to close?

Dataset: Ashgrove Chambers (legal)

A Lagos law firm's clients, matters, court hearings and invoices from 2024 to August 2026.

This data is used throughout Power BI Fundamentals, with guided lessons and a final project.

ExcelSQL

Employee Analytics

Analyse attendance, lateness and leave across departments, and what staff turnover looks like.

Questions to answer

Which departments have the highest lateness and absence rates?
How much leave is taken, by type and department?
What is the resignation rate by department and job level?
How does pay vary by level?

Dataset: Kolanut Distribution (HR)

The distributor's 80 staff, their June 2026 attendance, and leave records since January 2025.

This data is used throughout Data Analytics Foundations, with guided lessons and a final project.

All four companies and their data are made up for learning. Any resemblance to a real business is a coincidence. You're free to use the datasets and your analysis in a portfolio.

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