1. Project Overview
The Real Estate Intelligence Dashboard is a data-driven platform designed to provide market insights, predictive analytics, and investment intelligence for the Mexican real estate sector.
Data Consolidation
Aggregates data from public, private, and institutional sources
Actionable Insights
Delivers valuable intelligence for strategic decision-making
Target Audience
Investors, developers, brokers, and financial institutions
2. Objectives
- Centralize real estate data from multiple Mexican sources (portals, INEGI, SHF, Banxico)
- Provide real-time market trends (prices, demand, rental yields)
- Enable comparative and predictive analytics for decision-making
- Support investment evaluations (ROI, plusvalía, rentabilidad)
- Deliver a visual, interactive dashboard accessible via web and BI tools
3. Scope
In-Scope
- Collection of listings and market data (venta/renta)
- Geospatial analysis (colonias, municipios, zonas metropolitanas)
- Economic indicators (tasas de interés, inflación, permisos de construcción)
- Predictive models for price and demand
- Web dashboard with role-based access
Out of Scope (Phase 1)
- Direct property transactions (marketplace)
- Blockchain land registry
- International property data
4. Stakeholders
Primary Users
- Real estate investors
- Brokers
- Developers
- Financial institutions
Data Providers
- INEGI
- SHF
- Banxico
- Real estate portals
Internal Team
- Data engineering team
- Data science team
- Development team
- UI/UX designers
5. Functional Requirements
Market Overview
Heatmaps, trends, KPIs
Supply & Demand
Analytics by region
Economic Indicators
Interactive dashboard
Zone Analysis
Comparative tools
Predictive Insights
Price forecast models
Investment Tools
ROI calculators
8. Technology Stack
Data Ingestion
- Python Scrapy, BeautifulSoup
- Airflow Workflow management
Storage
- PostgreSQL + PostGIS
- BigQuery Analytics
Processing
- Pandas Data manipulation
- GeoPandas Geospatial
- PySpark Large datasets
Visualization
- React Frontend
- Mapbox Geospatial viz
- Power BI Optional BI
10. Timeline (High-Level)
Phase 1
0-2 months
Data ingestion & storage setup
Phase 2
2-4 months
Dashboard MVP (market trends + KPIs)
Phase 3
4-6 months
Predictive models & investment tools
Phase 4
6-9 months
Advanced alerts, CRM integration, production deployment
12. Success Metrics
Active users within first 3 months
Model accuracy vs benchmarks
Reduction in decision time
Reports generated monthly
