Deeman
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ebfdc84a94
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feat(transform): add dim_locations + dual market scoring models
dim_locations (foundation):
- Seeded from stg_population_geonames (all locations, not venue-dependent)
- Grain: (country_code, geoname_id)
- Enriched with: padel venues within 5km, nearest court distance (ST_Distance_Sphere),
tennis courts within 25km, country income
- Covers zero-court Gemeinden for opportunity scoring
location_opportunity_profile (serving) — Padelnomics Marktpotenzial-Score:
- Answers "Where should I build?" — no padel_venue_count filter
- Formula: population (25) + income (20) + supply gap inverted (30) +
catchment gap (15) + tennis culture (10) = 100pts
- Sorted by opportunity_score DESC
city_market_profile (serving) — Padelnomics Marktreife-Score:
- Add saturation discount (×0.85 when venues_per_100k > 8)
- Update header comment to reference Marktreife-Score branding
- Kept WHERE padel_venue_count > 0 (established markets only)
- column name market_score unchanged (avoids downstream breakage)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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2026-02-24 16:28:16 +01:00 |
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