lmiranda
457bb49395
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>
63 lines
1.4 KiB
SQL
63 lines
1.4 KiB
SQL
-- Intermediate: Monthly purchase data enriched with dimensions
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-- Joins purchases with time and district dimensions for analysis
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with purchases as (
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select * from {{ ref('stg_trreb__purchases') }}
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),
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time_dim as (
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select * from {{ ref('stg_dimensions__time') }}
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),
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district_dim as (
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select * from {{ ref('stg_dimensions__trreb_districts') }}
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),
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enriched as (
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select
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p.purchase_id,
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-- Time attributes
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t.date_key,
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t.full_date,
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t.year,
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t.month,
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t.quarter,
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t.month_name,
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-- District attributes
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d.district_key,
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d.district_code,
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d.district_name,
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d.area_type,
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-- Metrics
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p.sales_count,
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p.dollar_volume,
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p.avg_price,
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p.median_price,
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p.new_listings,
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p.active_listings,
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p.days_on_market,
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p.sale_to_list_ratio,
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-- Calculated metrics
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case
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when p.active_listings > 0
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then round(p.sales_count::numeric / p.active_listings, 3)
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else null
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end as absorption_rate,
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case
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when p.sales_count > 0
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then round(p.active_listings::numeric / p.sales_count, 1)
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else null
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end as months_of_inventory
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from purchases p
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inner join time_dim t on p.date_key = t.date_key
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inner join district_dim d on p.district_key = d.district_key
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)
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select * from enriched
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