lmiranda 457bb49395 feat: add loaders and dbt models for Toronto housing data
Sprint 4 implementation:

Loaders:
- base.py: Session management, bulk insert, upsert utilities
- dimensions.py: Load time, district, zone, neighbourhood, policy dimensions
- trreb.py: Load TRREB purchase data to fact_purchases
- cmhc.py: Load CMHC rental data to fact_rentals

dbt Project:
- Project configuration (dbt_project.yml, packages.yml)
- Staging models for all fact and dimension tables
- Intermediate models with dimension enrichment
- Marts: purchase analysis, rental analysis, market summary

Closes #16

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-11 16:07:30 -05:00
2026-01-11 19:38:03 +00:00
2026-01-11 13:49:28 -05:00
2026-01-11 18:25:07 +00:00
Description
Analytics portfolio: Toronto Housing Dashboard (choropleth visualization, multi-source ETL, geospatial analysis) + Energy Pricing Analysis (ML prediction). Built with Dash, PostgreSQL/PostGIS, dbt, and Pydantic.​​​​​​​​​​​​​​​​
Readme MIT 30 MiB
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