# Check the GA4 BigQuery export health

> Tier: recipe. Operating recipe: real tool sequence, core rules, known traps.

BigQuery export diagnostics: linkage, freshness, completeness signals.

**Intent.** Whether the raw-data pipeline downstream teams rely on is intact.

## When to use

- Data teams report gaps.
- Scheduled hygiene.

## When not to use

- No specific contraindication beyond the preconditions below.

## Sources

Required: Google Analytics 4

## Preconditions

- The account is ticked in the dashboard, confirmed via list_accounts.

## Inputs

- `window`: Analysis window. Default: last 30 days.

## Procedure

1. Run BigQuery export diagnostics. — tools: `ga4_get_bigquery_export_diagnostics`
2. Date any gap and bound the affected days.

## Decision rules

- **When** Export gaps exist → **conclude** Every downstream model inherits them: publish the affected dates, not just 'there was an issue'.

## Evidence requirements

- Every figure carries its account, metric and window.
- Anything below a readable sample size is reported as unjudged, not as zero.

## Human approval boundary

- The readout changes nothing. Any change it motivates goes through Safe Writes: preview, human confirmation, then apply.

## Failure modes

- Daily vs streaming exports have different completeness semantics: name which one the check read.

## Output

- **Readout**: The figures, with windows and accounts named.
- **Flags**: What deserves a deeper skill or a human decision.