Tudor ca351e9d73 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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