feat(pipeline): add Meltano + dbt + Airflow ELT pipeline scaffold
Replaces the hand-rolled integrator with a production-grade ELT pipeline
using Meltano (Singer taps), dbt Core (medallion architecture), and
Apache Airflow (orchestration). Adds Typesense for search and PostGIS
for geospatial queries.
- 6 custom Singer taps (GIAS, EES, Ofsted, Parent View, FBIT, IDACI)
- dbt project: 12 staging, 5 intermediate, 12 mart models
- 3 Airflow DAGs (daily/monthly/annual schedules)
- Typesense sync + batch geocoding scripts
- docker-compose: add Airflow, Typesense; upgrade to PostGIS
- Portainer stack definition matching live deployment topology
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-26 08:37:53 +00:00
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-- Mart: School admissions — one row per URN per year
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select
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urn,
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year,
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feat: migrate backend to marts schema, update EES tap for verified datasets
Pipeline:
- EES tap: split KS4 into performance + info streams, fix admissions filename
(SchoolLevel keyword match), fix census filename (yearly suffix), remove
phonics (no school-level data on EES), change endswith → in for matching
- stg_ees_ks4: rewrite to filter long-format data and extract Attainment 8,
Progress 8, EBacc, English/Maths metrics; join KS4 info for context
- stg_ees_admissions: map real CSV columns (total_number_places_offered, etc.)
- stg_ees_census: update source reference, stub with TODO for data columns
- Remove stg_ees_phonics, fact_phonics (no school-level EES data)
- Add ees_ks4_performance + ees_ks4_info sources, remove ees_ks4 + ees_phonics
- Update int_ks4_with_lineage + fact_ks4_performance with new KS4 columns
- Annual EES DAG: remove stg_ees_phonics+ from selector
Backend:
- models.py: replace all models to point at marts.* tables with schema='marts'
(DimSchool, DimLocation, KS2Performance, FactOfstedInspection, etc.)
- data_loader.py: rewrite load_school_data_as_dataframe() using raw SQL joining
dim_school + dim_location + fact_ks2_performance; update get_supplementary_data()
- database.py: remove migration machinery, keep only connection setup
- app.py: remove check_and_migrate_if_needed, remove /api/admin/reimport-ks2
endpoints (pipeline handles all imports)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-27 09:29:27 +00:00
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school_phase,
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feat(pipeline): add Meltano + dbt + Airflow ELT pipeline scaffold
Replaces the hand-rolled integrator with a production-grade ELT pipeline
using Meltano (Singer taps), dbt Core (medallion architecture), and
Apache Airflow (orchestration). Adds Typesense for search and PostGIS
for geospatial queries.
- 6 custom Singer taps (GIAS, EES, Ofsted, Parent View, FBIT, IDACI)
- dbt project: 12 staging, 5 intermediate, 12 mart models
- 3 Airflow DAGs (daily/monthly/annual schedules)
- Typesense sync + batch geocoding scripts
- docker-compose: add Airflow, Typesense; upgrade to PostGIS
- Portainer stack definition matching live deployment topology
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-26 08:37:53 +00:00
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published_admission_number,
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total_applications,
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feat: migrate backend to marts schema, update EES tap for verified datasets
Pipeline:
- EES tap: split KS4 into performance + info streams, fix admissions filename
(SchoolLevel keyword match), fix census filename (yearly suffix), remove
phonics (no school-level data on EES), change endswith → in for matching
- stg_ees_ks4: rewrite to filter long-format data and extract Attainment 8,
Progress 8, EBacc, English/Maths metrics; join KS4 info for context
- stg_ees_admissions: map real CSV columns (total_number_places_offered, etc.)
- stg_ees_census: update source reference, stub with TODO for data columns
- Remove stg_ees_phonics, fact_phonics (no school-level EES data)
- Add ees_ks4_performance + ees_ks4_info sources, remove ees_ks4 + ees_phonics
- Update int_ks4_with_lineage + fact_ks4_performance with new KS4 columns
- Annual EES DAG: remove stg_ees_phonics+ from selector
Backend:
- models.py: replace all models to point at marts.* tables with schema='marts'
(DimSchool, DimLocation, KS2Performance, FactOfstedInspection, etc.)
- data_loader.py: rewrite load_school_data_as_dataframe() using raw SQL joining
dim_school + dim_location + fact_ks2_performance; update get_supplementary_data()
- database.py: remove migration machinery, keep only connection setup
- app.py: remove check_and_migrate_if_needed, remove /api/admin/reimport-ks2
endpoints (pipeline handles all imports)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-27 09:29:27 +00:00
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first_preference_applications,
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first_preference_offers,
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first_preference_offer_pct,
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oversubscribed,
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admissions_policy
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feat(pipeline): add Meltano + dbt + Airflow ELT pipeline scaffold
Replaces the hand-rolled integrator with a production-grade ELT pipeline
using Meltano (Singer taps), dbt Core (medallion architecture), and
Apache Airflow (orchestration). Adds Typesense for search and PostGIS
for geospatial queries.
- 6 custom Singer taps (GIAS, EES, Ofsted, Parent View, FBIT, IDACI)
- dbt project: 12 staging, 5 intermediate, 12 mart models
- 3 Airflow DAGs (daily/monthly/annual schedules)
- Typesense sync + batch geocoding scripts
- docker-compose: add Airflow, Typesense; upgrade to PostGIS
- Portainer stack definition matching live deployment topology
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-26 08:37:53 +00:00
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from {{ ref('stg_ees_admissions') }}
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