Google Analytics 4
Google Analytics 4's BigQuery export, read by a dedicated service account. Queries run inside BigQuery and write to your warehouse; rows never pass through pipeline code.
What the connection reaches
- Daily and intraday export tables, found by date
- One query per run, merged into your warehouse by date
- Only SELECT on the configured dataset; everything else is refused
- Status
- Built into the pipeline SDK
- Connection class
- BigQueryConnection
- Credential
- BigQuery Data Viewer on the GA4 export dataset
Connect Google Analytics 4
Three steps, the same for every connection. The credential goes to the platform, never into the repository or pipeline code.
- 1
Declare it in connections/connections.py
connections/connections.py from segmentstream.connections import BigQueryConnection connections = ( BigQueryConnection(key="ga4"),) - 2
Deploy
$ segmentstream deploy - 3
Connect
Set the project and dataset of the GA4 export in the console, or from the terminal. Saving creates a dedicated service account.
$ segmentstream connection configure ga4 --source-project my-project --source-dataset analytics_123456 - 4
Then
Grant that service account BigQuery Data Viewer on the export dataset, then verify access.
$ segmentstream connection verify ga4
Use it
Code asks for the connection by its key. The platform adds the credential on the way out.
@s.model(key="ga4_events", connections=("ga4",), schema=SCHEMA, partitioning=DAILY)def ga4_events(context: s.Context) -> s.Ga4QueryResult: client = s.ga4_bigquery_client("ga4", context=context) client.query(sql_for(client, context.partition_keys)) return client.result()Or ask your agent
“Connect our GA4 BigQuery export and build a daily sessions table.”
Part of these solutions
More in Analytics & social
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