Amollo1/kenya-mobile-money-agent-analytics

Power BI + SQL analytics project analyzing a synthetic Kenyan mobile-money agent network ; 1M transactions, star schema, DAX, geographic profitability insights. # Kenya Mobile Money & Agent Network Analytics **A full-stack data analytics portfolio project**; from synthetic data generation through a dimensional database model to an interactive Power BI dashboard, analyzing the profitability and geographic performance of a simulated Kenyan mobile-money agent network. --- ## Business Problem Kenya's mobile-money agent network has grown rapidly; CBK reported 381,116 active agents in 2024, rising to 473,536 by December 2025, processing roughly KSh 722.5 billion in monthly transaction value. But growth in agent numbers has not translated into growth in agent economics: average annual M-Pesa agent commissions fell to approximately KSh 112,244 for the year ended March 2026. **Central question:** How profitable is the agent network, where is it performing well, and where is it losing money or facing operational risk? *All CBK/industry figures above are public statistics used only to ground realistic assumptions. All transaction-level data in this project is synthetic and does not represent Safaricom, Airtel, or any bank's actual data.* 📄 **Read the full Business Insights write-up →** --- ## What This Project Demonstrates - **Database design:** A dimensional (star schema) model in MySQL; one fact table, five dimension tables - **Data engineering:** A Python pipeline generating 1,000,000 statistically realistic synthetic transactions (log-normal amount distributions, weighted provider/transaction-type probabilities grounded in real Kenyan market share data) - **SQL analysis:** 10 exploratory queries answering specific business questions, with documented findings - **BI development:** A 2-page Power BI dashboard with 15 DAX measures, synced cross-page filters, custom tooltips, a dynamic insight card, and in-app page navigation - **Business communication:** A written insights document translating technical findings into strategic recommendations --- ## Dashboard Preview ### Executive Overview High-level KPIs, revenue tren …