Aderonke101/PowerBI_Precision-Mapping-of-Nigeria-s-Food-Inflation

A Power BI project analyzing Nigeria's food inflation using real market data. Includes seasonal price trends, market volatility, and PowerBI inbuilt based forecasting with actionable insights and policy recommendations. # Grains Of Truth: Precision Mapping of Nigeria’s Food Inflation **A socially-driven analysis of food affordability for sustainable impact.** ## 📌 Overview Food inflation remains one of the most pressing challenges facing Nigeria today. With millions affected by rising prices, limited access to affordable food, and regional disparities in market costs, understanding the dynamics of food pricing has never been more critical. This Power BI dashboard project, **Grains of Truth**, takes a deep dive into Nigeria's food inflation trends, providing granular insight into food price volatility across states, markets, historical periods, and commodity types. It blends descriptive analytics with predictive modeling to help governments, researchers, and NGOs make informed decisions. > **Interactive Pop-out Feature** > A pop-out feature embedded in the home dashboard acts like a search bar, allowing users to explore: > - **14 Major Markets across Nigeria** > - **Price Volatility by State** > - **Price Volatility by Market** --- ## Key Insights 1. **Staple Crops Drive Market Spend** Commodities like **cowpeas**, **local rice**, and **garri** dominate food spending, while **tomatoes**, **spinach**, and **wheat** show the least price influence. 2. **Seasonal Price Surges** Food prices significantly rise from **July to September**, aligning with seasonal harvest gaps and transport challenges. 3. **Retail Buyers Pay More** Retail-level buyers consistently pay more than wholesale buyers in both **Naira (NGN)** and **USD**, often by wide margins. 4. **Post-COVID Price Spike** The **COVID-19 era** saw the steepest increase in food costs in over a decade, impacting affordability nationwide. 5. **Urban Market Strain** Cities like **Maiduguri** and **Ibadan** top the list of expensive food markets, often driven by insecurity, logistics costs, and urban demand. --- ## 📈 Predictive Modeling To anticipate future food pricing, I …