This project aims to develop a Business Intelligence platform that analyzes real estate transaction data to identify pricing trends, location-based demand, and property valuation patterns. The system will help investors and developers make informed decisions using interactive dashboards and predictive analytics.
Collect property transaction datasets including location, price, size, and transaction dates.
Clean and standardize location and pricing data.
Design a star schema data warehouse for property analytics.
Implement ETL pipelines to consolidate transaction and demographic data.
Develop dashboards displaying average prices, demand growth, and regional comparisons.
Analyze price trends across time and locality.
Identify high-growth investment zones.
Implement time-series forecasting for future property price predictions.
Enable interactive map-based visualizations for geographic insights.
Compare residential and commercial property trends.
Validate forecasting accuracy using historical comparison methods.
Document findings and provide strategic real estate recommendations.
