Olorlade/Internal-Displacement-Analysis

This project analyzes internal displacement trends in Nigeria (2013–2023) due to conflicts and natural disasters. Using data-driven insights, it identifies key displacement patterns, demographic impacts, and major causes to support better policy decisions and humanitarian responses. # PROJECT TITLE: INTERNAL DISPLACEMENT UPDATE (IDU)- DISASTER & CONFLICT DISPLACEMENT FLOWS # 📖TABLE OF CONTENT - PROJECT OVERVIEW - OBJECTIVES - DATA SOURCE - TECH TOOLS - DATA PROCESSING AND TRANSFORMATION - DATA CLEANING - DATA ANALYSIS Descriptive Analysis - DISASTER DISPLACEMENT FINDINGS - CONFLICT DISPLACEMENT FINDINGS - INSIGHTS - RECOMMENDATIONS - CONCLUSION # 📌PROJECT OVERVIEW This repository contains an in-depth analysis of internal displacement trends in Nigeria caused by both conflicts and disasters from 2013 to 2023. The study leverages structured datasets to derive actionable insights that can support policymakers, humanitarian organizations, and government agencies in addressing internal displacement challenges. # 🎯OBJECTIVES • Analyze trends in displacement caused by conflicts and disasters over time. • Identify the demographic distribution of displaced individuals by age and gender. • Assess the impact of different hazards (floods, storms, wave action) on displacement. • Investigate major causes and locations of displacement. • Providing actionable insights for policymakers, humanitarian organizations, and government agencies to improve disaster preparedness, conflict resolution, and risk reduction. # 📊DATA SOURCE The datasets used are sourced from the Global Internal Displacement Database (GIDD) and Internal Displacement Monitoring Centre (IDMC). The two main datasets include: 1. Disaster Internal Displacement Data (2013-2023) 2. Conflict Internal Displacement Data (2013-2023) # 🛠TECH TOOLS • Excel → Data cleaning, calculations, and exploratory analysis. • PostgreSQL → Database management and querying. • Power BI → Data transformation, visualization, and dashboard development. # 🔍DATA PROCESSING AND TRANSFORMATION • Cleaned and structured raw data for consistency and accuracy. • Created calculated measures to analyze displacement patterns. • Developed relationships between datasets to enhance comparative insights. • Categorized displa …