docs/PRESENTATION_OUTLINE.md

PropertyVision Presentation Outline

Slide 1: Title

PropertyVision BI - Real Estate Decision Intelligence

Slide 2: Problem

• Doanh nghiệp cần chọn khu vực đầu tư, định giá tài sản, kiểm soát ROI và rủi ro.
• Listing rời rạc không đủ để ra quyết định chiến lược.
• Cần MIS/DSS/EIS tích hợp BI, GIS, ETL và AI.

Slide 3: Data

• clean_data.csv: listing đã xử lý.
• SQLite warehouse: dimension, fact listing, mart district monthly.
• Transaction proxy: public listing/time-series datasets.
• Planning/legal docs: HCMGIS, cổng quy hoạch, legal/planning cache.

Slide 4: Architecture

• Frontend: React + Recharts + Leaflet.
• Backend: FastAPI.
• Storage: SQLite.
• ML: Random Forest.
• RAG: sentence-transformers + NearestNeighbors.
• LLM: Ollama local model.

Slide 5: Method

• KPI analytics.
• Slice-and-dice multidimensional analysis.
• Opportunity scoring.
• Legal/planning risk screening.
• Price prediction.
• What-if simulation and payback analysis.
• 5-10 year multi-scenario projection.
• Retrieval + LLM answer with citations.
• ETL manual/scheduled/incremental.

Slide 6: Demo Flow

1. Executive Dashboard.
2. Market Intelligence.
3. Slice & Dice Analysis.
4. Investment Strategy.
5. GIS Map.
6. Data Pipeline.
7. Price Prediction.
8. Legal/Planning RAG.

Slide 7: Results

• Top opportunity districts.
• ROI and price/m² comparison.
• Prediction result with MAE/R².
• What-if future value, ROI, payback period, scenario projection.
• RAG response with sources.

Slide 8: Information Systems Mapping

• MIS: reporting dashboards.
• DSS: prediction and recommendation.
• EIS: executive overview.
• TPS: transaction-proxy fact table.
• KWS: RAG/LLM knowledge assistant.
• OAS: reports, citations, demo documents.

Slide 9: Conclusion

• PropertyVision supports data-driven investment decisions.
• The system integrates market, map, ETL, planning/legal context and AI.
• It is ready to replace public/cached sources with enterprise official data.

Slide 10: Rubric Checklist

• Problem description.
• Method/tool/algorithm description.
• Application demo.
• Visualization and explanation.
• Conclusion.
• Presentation/demo quality.
• Clear delivery.