I transform raw operational data into dashboards and insights that help businesses make faster, better decisions.
Statistics graduate with hands-on experience in Excel, SQL, Power BI and Python — currently building end-to-end analytics projects and transitioning into Data Science.
I am a Statistics graduate from FUOYE who genuinely enjoys working with data — not just the clean, tidy kind, but the messy, real-world kind that takes time to understand before it starts making sense.
I did my Industrial Training at Fan Milk Nigeria, worked as hard as I could, and built a strong enough track record that I was invited back for my NYSC posting. During my NYSC, I worked directly with the Logistics Manager — supporting transport operations, KPI reporting and supply chain performance analysis across the national distribution network.
Right now I process over 700 rows of data every day, monitor Case Fill Rate across 9 Distribution Centres, and produce weekly reports that senior management reads and uses. I am also learning Python and working towards a Master's in Data Science — because I want to move beyond describing what happened to predicting what will happen next.
Tools I work with every day — not just listed, actually used in real projects.
Four end-to-end projects — real data, real findings, real recommendations. Click any image to zoom.
Built an end-to-end KFC Nigeria sales analytics solution — cleaning 500 transaction records in Excel, building 6 pivot table analyses, and developing an interactive dashboard with an executive insight report. The goal was to give management a clear picture of what was driving revenue and what was holding it back.
The business had sales data but no structured view of performance. Which product was making the most money? Which branch was underperforming? Were customers returning? I built a dashboard that answers all of this in one place — with slicers to filter by branch and month.
500 sales transactions from January to December 2023 across 8 KFC Nigeria branches — including product names, categories, branch locations, payment methods, customer ratings, quantities and prices. Total revenue: ₦3.02M.
Built an end-to-end HR analytics solution by cleaning 3,000 employee records in Excel, analysing them with SQL, and developing a 2-page interactive Power BI dashboard — one page for the main dashboard, one dedicated page for key insights and recommendations. Total training budget analysed: $1.68M.
The organisation was spending $1.68M on training without knowing if it was working. Which departments had the best engagement? Were employees actually finishing their training? Was there a relationship between age, performance and satisfaction? I dug into all of it.
3,000 employee records across 6 departments — Production, IT/IS, Sales, Software Engineering, Admin Offices, Executive Office. Fields: performance ratings, engagement scores, satisfaction scores, training costs, training outcomes, work-life balance scores, age, gender and employment type.
A multi-year sales analysis of a global superstore chain covering 2011 to 2014 — across multiple regions, product categories and markets. I cleaned the data in Excel then built an interactive Power BI dashboard with filters for year, region and category. Total sales: $13M.
Four decades of global video game sales — from 1980 to 2022 — analysed across regions, consoles, publishers, developers and genres. I built a Power BI dashboard that makes it easy to see which platforms dominated, which markets spent the most, and how the industry shifted over time.
Two years at the same company — invited back because I earned it.
A few things I am proud of.
Open to data analyst roles, freelance projects, collaborations and conversations about data science. If you think there is something we can work on together — reach out.
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