OYENIRAN TOBI

Analyzed complex finance datasets to identify a 24.6% income increase, 24.5% expense increase, and a 27% decrease in savings, highlighting critical risks to long-term sustainability.

Leveraged SQL and Power BI with Recency, Frequency, and Monetary (RFM) modeling to analyze customer behavior, resulting in a 50% increase in sales.

Conducted exploratory revenue analysis that influenced 65% of investment decisions through data-driven insights on high-growth sectors and industry potential.

Streamlined data processing by utilizing advanced Excel functions for data cleaning and transformation, reducing analysis time by 30% and enhancing data accuracy.

Executed ELT processes and delivered actionable insights, improving investor decision-making accuracy by 45% and reporting accuracy for sales and marketing teams by 35%.

Reduced equipment downtime by 30% through proactive maintenance scheduling, significantly enhancing operational efficiency.

Digitized over 5,000 confidential company records in Google Sheets, increasing document retrieval speed by 70%.

Improved fuel accountability by 25% by implementing a new trip log system for company vehicle usage and monitoring.

Enhanced internal communication and external partner response time by 35%, fostering smoother cross-departmental operations.

Managed comprehensive procurement processes, ensuring timely acquisition of supplies and services while maintaining strong vendor relationships.

Conducted end-to-end analysis of Superstore's 2014 sales data across U.S. regions, cities, states, and customer segments to identify key market trends.

Cleaned and structured over 7,500 rows of raw transactional data using Excel functions and formulas, increasing data quality and reducing reporting errors by 30%.

Transformed data using Power Query in Power BI, enabling dynamic and scalable data models for advanced business reporting and visualization.