Projects
A collection of data analysis projects showcasing real business impact through strategic insights and actionable recommendations.
Three product categories drive ~70% of total revenue
Goal: Optimize a USD 137.1 Million global portfolio by prioritizing high-performing national markets and managing a 69% regional concentration risk.
Process: Conducted a diagnostic analysis on 100 country-level aggregates to identify revenue drivers versus volume traps.
Key Insight: Sub-Saharan Africa and Europe serve as the primary revenue anchors (>50%), while the Online distribution model achieves a peak profit margin of 33.04%.
Fall and Trauma occurred up to 16-times more than other HAC measures
Goal: Identify which preventable conditions posed the greatest patient safety risk in 2025.
Process: Cleaned and analyzed CMS HAC data in MySQL, then exported results to Excel for stakeholder-ready visuals.
Key Insight: Falls and Trauma accounted for the overwhelming majority of HAC variation in 2025, with rates up to 16 per 1,000 discharges, far exceeding other measures.
Cut my monthly supermarket bill by 5.16% without buying less
Problem: My monthly supermarket purchases hit KSh. 14,408, likely overpaying by shopping out of habit at Naivas.
Findings: Carrefour alone cut costs by 3.3%, while a mixed-store basket saved KSh 743 (5.16%), with 5 items driving 77.65% of savings.
Fix: Used Excel, Power BI (DAX + dashboards) to compare store-level prices and recommend an optimal shopping strategy.
A one-day look at new Zillow listings in 10 of the largest U.S. cities, visualized through Power BI.
What I Did: Extracted & analyzed 380 Zillow listings with Python and Power BI to reveal pricing and property trends.
Findings:Median price $439.5K, 74% single-family homes; condos led in value ($1,660/sqft). LA & NY skewed averages; Chicago & San Antonio affordable.
Outcome: An interactive dashboard providing actionable market insights.
Uncovered $2M revenue leakage from customer churn
Problem: StaffWise’s revenue growth stalled despite strong signups—nearly $2M at risk from churn & failed payments.
Findings: 84% churn for monthly-plan customers; long-term clients drove 70%+ of revenue loss.
Fix: Leveraged Power Query, DAX, and interactive dashboards to pinpoint leaks and prioritize retention strategies.