≈12%
revenue opportunity found
SQL on transaction data surfaced payment-failure and user-spending patterns worth about 12% in potential revenue.
I turn messy data into decisions people can act on. The lab taught me to check the evidence before I tell the story.
1TimeShop · ride-hailing & food delivery · Feb 2025 – Apr 2026
I joined as an intern and was promoted to Data Analyst Associate seven months later. I took ride-hailing and food-delivery data from raw tables to the dashboards and reports stakeholders actually used.
≈12%
SQL on transaction data surfaced payment-failure and user-spending patterns worth about 12% in potential revenue.
≈15%
DAX measures for fulfilment time, cancellations and revenue backed the operational changes behind the speed-up.
≈8%
I turned user-behaviour analysis into decision-ready reporting for non-technical stakeholders while monthly active users grew.
Figures are approximate. Business data stays under NDA.
Live builds · 3 deployed
Not screenshots in a slide deck. All three run on public URLs, and one refreshes itself every 15 minutes.
Health informatics · October 2026
For Breast Cancer Awareness Month I asked a plain question: what does the data actually say? The observatory brings together public attention data, WHO indicators and Nigerian cancer registry studies, and says plainly what each source can and can't prove.
Finance · refreshes every 15 minutes
Most crypto dashboards stop at USD. This one tracks the top 50 coins in naira too. A scheduled GitHub Action snapshots the market every 15 minutes, so it stays current with nobody touching it.
24h change, top coins
Product · for analysts facing a blank canvas
I built this after weeks of creative block: I knew the answer, I just couldn't draw it. Give Draftboard a short NDA-safe brief and it returns a 12-column layout, chart mockups, four colour palettes and a spec you can copy into Power BI, Tableau, Looker Studio or Excel.
Case files · 13
Filter by domain, then open a file for the question, what I did and what the data said. Charts marked “shape only” show the pattern, not exact values.
More on GitHub ↗, including SQL Server retail analysis, a healthcare operations dashboard and a PwC call-centre case study.
About
I studied Applied Microbiology, where a bad interpretation has real consequences. That habit came with me into data. I check the data, question strange results, write down my assumptions, and I don't turn correlation into certainty.
I got into analytics because I like finding out why something happened. When a metric drops, I want the cause, and chasing it feels like detective work. Most of what I build is in SQL and Power BI, with Python and Tableau when the problem calls for them.
Every dashboard I build answers three questions, in this order
Off the clock
Toolkit
Counted across my role at 1TimeShop and my portfolio projects, with tools sorted by use. Hover or focus a row or column to trace it.
Also in the kit: Pandas, Plotly, GitHub Actions, Parquet, REST APIs (CoinGecko, WHO, Wikimedia), Jira and Agile delivery. Currently studying for Microsoft PL-300, the Power BI Data Analyst certification.
Get in touch
I'm open to remote Data Analyst, BI Analyst, Reporting Analyst, Operations Data Analyst and Product Analytics roles.
It's in Nigeria (WAT, UTC+1)