These schools are still operating and publish results; they drop out
automatically when GIAS flips them to Closed since marts fully rebuild
each run.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Matches the phase derivation's guard against casing/whitespace variants in
raw GIAS data; an unmatched variant previously fell through silently to the
statutory-age fallback.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
int_ofsted_latest is only ref()'d inside a conditional block, so dbt
couldn't infer the edge and failed to compile dim_school. Add the
-- depends_on hint dbt recommends. No runtime behaviour change: the
adapter.get_relation guard still handles the pre-Ofsted-pipeline case.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Ungraded (Section 8) inspections don't assign a fresh grade — the export
only gives free text like "School remains Good". Parse that text into a
grade (remains Outstanding -> 1, remains Good -> 2, else null) and use it
as a last-resort fallback when no graded overall effectiveness exists.
Also retain schools that have only an ungraded inspection (no graded date)
by coalescing the inspection date, so ~8.5k previously-dropped schools now
carry a grade.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
dim_school.sql was checking for int_ofsted_latest in target.schema (wrong schema)
due to the custom generate_schema_name macro using literal schema names. The
model lives in 'intermediate', so ofsted_grade/date/framework were always NULL
in dim_school, causing all list cards to show 'Not yet inspected'.
Fix 1: data_loader.py joins marts.fact_ofsted_inspection with DISTINCT ON to
get latest inspection per school — no pipeline re-run needed.
Fix 2: dim_school.sql uses schema='intermediate' so future dbt runs correctly
denormalise the Ofsted summary into dim_school.
The case-insensitive "Not Applicable" fix caught schools where GIAS publishes
statutory ages, but some independent schools leave those blank too — they fall
through every branch and end up with null phase and no pill in the UI.
Add a third tier that infers phase from the school name
(Primary/Infant/Junior/Prep vs Secondary/High/Grammar/Senior/Upper) and also
normalise "Not Applicable" handling with trim() + "unknown"/"" exclusion, so
the final else branch can safely return null instead of the catch-all string.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
GIAS provides 'Not Applicable' (capital A) but the check used 'Not applicable',
so the case-sensitive != matched true and skipped the age-range inference.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Independent schools have phase='Not applicable' in GIAS. Now infer
phase from statutory age range: <=11 → Primary, >=11 → Secondary,
spans both → All-through. Falls back to original value if no age data.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Declare all 34 columns needed by dbt in GIAS tap schema (target-postgres
only persists columns present in the Singer schema message)
- Use nullif() for empty-string-to-integer/date casts in staging models
- Scope daily DAG dbt build to GIAS models only (stg_gias_establishments+
stg_gias_links+) to avoid errors on unloaded sources
- Scope annual EES DAG similarly; remove redundant dbt test steps
- Make dim_school gracefully handle missing int_ofsted_latest table
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
tudorandClaude Opus 4.6