oluwadamilolaayomide/nigeria_flood-risk-analysis

SQL and Power BI analysis of Flood Risk Trends across Nigeria (2018–2025). # Nigeria Flood Risk Analysis: SQL & Power BI Analysis (2018–2025) ## Overview Flood-related disasters continue to affect communities across Nigeria through fatalities, population displacement and economic losses. Understanding where flood impacts are most severe can support better disaster preparedness, resource allocation and risk mitigation. This project analyses flood incidents recorded between **2018 and 2025** across **15 Nigerian states** using SQL and Power BI. The analysis identifies flood trends, regional risk patterns and factors associated with severe flood events through an interactive dashboard. --- ## Live Dashboard Interactive Dashboard --- ## Business Questions This project answers the following questions: - Which states recorded the highest flood impact? - Which regions experienced the greatest economic losses? - How have flood incidents changed between 2018 and 2025? - Which year recorded the highest flood fatalities? - Which environmental factors are associated with severe flooding? - Does emergency response time appear related to higher fatality levels? - Which locations should be prioritised for flood mitigation? --- ## Analytics Workflow ### Data Preparation The dataset was prepared in SQL by: - Creating the database and table structure - Assessing data quality - Handling missing values - Removing duplicate records - Validating data consistency ### Exploratory Analysis SQL queries were developed to analyse: - Flood impact by state and region - Annual flood trends - Climate risk patterns - Flood severity drivers - Emergency response performance ### Data Transformation The prepared dataset was imported into Power BI, where Power Query was used to perform additional transformations before building the analytical model. ### Business Analytics DAX measures were created to calculate: - Total Flood Incidents - Total Fatalities - Total Population Displaced - Total Economic Loss - Peak Fatality Year - Average Climate Risk - Hig …