RecipeGoogle Analytics 4
Check the GA4 BigQuery export health
BigQuery export diagnostics: linkage, freshness, completeness signals.
IntentWhether the raw-data pipeline downstream teams rely on is intact.
- 2
- Steps
- 1
- Tools
- 1
- Rules
- 1
- Failure modes
When to use it
Use it when
- Data teams report gaps.
- Scheduled hygiene.
Do not use it when
- No specific contraindication beyond the preconditions below.
What it needs first
Required
Preconditions
- The account is ticked in the dashboard, confirmed via list_accounts.
Inputs
window- Analysis window.Default: last 30 days.
Procedure
In order. Every tool named is one the gateway ships, and links to its reference.
Run BigQuery export diagnostics.
Date any gap and bound the affected days.
Decision rules
The observable condition, what it lets you conclude, and what takes the conclusion back.
When
Export gaps exist
Conclude
Every downstream model inherits them: publish the affected dates, not just 'there was an issue'.
Evidence every conclusion must carry
- Every figure carries its account, metric and window.
- Anything below a readable sample size is reported as unjudged, not as zero.
Where the agent stops
- The readout changes nothing. Any change it motivates goes through Safe Writes: preview, human confirmation, then apply.
How it goes wrong quietly
The cases where the analysis is wrong and still looks right. Read them before trusting a number.
- Daily vs streaming exports have different completeness semantics: name which one the check read.
What the answer contains
- 01Readout
- The figures, with windows and accounts named.
- 02Flags
- What deserves a deeper skill or a human decision.