Ogundeyi Oluwafemi Ezekiel

Analyzed 19,643 credit card transactions using MySQL to detect fraudulent patterns based on transaction amount and time of day, enhancing risk identification.

Identified that high-value transactions (above $500) exhibited a fraud rate 3x higher than low-value transactions, utilizing SQL CASE statements and GROUP BY aggregations to pinpoint critical risk factors.

Built an interactive Power BI dashboard to visualize fraud distribution by amount bucket and time of day, providing stakeholders with clear, actionable insights for mitigation strategies.

Utilized advanced data cleaning and exploratory data analysis (EDA) techniques to spot anomalies and suspicious patterns within banking data, improving data integrity and insight generation.

Implemented robust data processing workflows to prepare complex datasets for analysis, ensuring accuracy and reliability in fraud detection efforts.

Contributed to the development of a comprehensive fraud detection framework by identifying key indicators and data points crucial for financial security.

Developed a comprehensive, fully interactive sales performance dashboard using Advanced Microsoft Excel to analyze multi-year (2024–2025) revenue and profit datasets, enabling detailed financial review.

Engineered dynamic Pivot Tables, data source models, and customized regional slicers to track quarterly sales distributions across Nigeria, providing granular insights into market performance.

Transformed complex raw corporate metrics into executive-ready data visualizations, highlighting seasonal sales trends and supporting strategic business decisions with clear, actionable intelligence.