As a Certified Data Analyst, I turn raw data into insightful decisions. With expertise in SQL, Python, Excel, Figma and Power BI, I build end-to-end analytical pipelines from data cleaning and EDA to machine learning models and interactive dashboards. My work focuses on exploring datasets, identifying patterns and communicating findings in a clear and impactful way.
I enjoy approaching problems analytically, breaking them down into structured steps, and uncovering the story behind the data. Beyond data analysis, I am building predictive modelling and advanced analytics. I am also an ALX Certified Virtual Assistant and hold a Microsoft Professional Certificate in Project Management, where I apply my organisational skills, attention to detail, and ability to manage tasks efficiently. I am committed to continuous learning, building real-world projects and developing solutions that create value.
Let's work together and build something great for humankind.
End-to-end churn investigation across 974 MTN Nigeria customers in Q1 2025. SQL for baseline queries, Python for EDA and feature engineering, Power BI for a 4-page interactive dashboard covering customer overview, churn analysis, revenue performance, and risk intelligence.
Standalone ML project training three classification models — Logistic Regression, Decision Tree, and Random Forest — to predict which customers are most likely to churn. Full model comparison with confusion matrix analysis and feature importance evaluation.
Profitability analysis of 51,290 orders across 7 global markets and 4 years. Identified loss-making products, failing markets, and seasonal patterns using a relational 3-table data model and a 4-page Power BI dashboard.
Weekly sales analysis across 45 Walmart stores over 3 years. Investigated the impact of holidays, seasons, fuel prices, unemployment, and temperature on consumer spending behaviour using dual-axis Power BI visuals.
Global study of water pollution and waterborne disease burden across 10 countries spanning 26 years. Excel feature engineering combined with Python EDA to analyse disease trends, pollution patterns, and public health risk classification.
Cost analysis of 622 universities across 71 countries revealing the true financial burden of studying abroad. Identified the Tuition Trap — where low advertised fees mask significantly higher living costs that most students fail to plan for.