Finding and exporting your Google Analytics data

What it holds

GA4 records website and app interactions with traffic-source, session and device context. Aggregated reports and retained event-level data have different lifetimes and cannot be treated as interchangeable archives.

Where Google Analytics shows the size

1. Check Admin > Product links > BigQuery links for an existing destination.
2. Query the destination region INFORMATION_SCHEMA.TABLE_STORAGE and sum total_logical_bytes for the Analytics dataset; divide by 1073741824 for binary GB.
3. Without a linked dataset, open Reports > Engagement > Events and inspect Event count over the widest available range. Review Data Retention under Admin for event-level availability.

Plan and admin role. Changing retention or linking BigQuery requires property Editor or higher; linking also requires Owner access on the destination project. Reading storage metadata needs suitable Google Cloud permissions.

Exporting the full history

1. Under Admin > Product links > BigQuery links, choose Link, select the project and enable daily export; consider streaming for high-volume requirements.
2. Enable project billing for a durable archive rather than relying on sandbox tables.
3. Allow about 24 hours for initial delivery. Export accumulated BigQuery tables to Cloud Storage using table extract jobs when a separate copy is needed.

BigQuery linking does not backfill earlier GA4 events. Standard daily export is capped at one million events per day; repeated excess can pause it. Streaming has no event-count cap but adds cost; Analytics 360 daily export supports up to 20 billion events.

Sandbox tables expire after 60 days and sandbox storage is limited to 10 GiB. Standard event-level retention options are two or 14 months, versus up to 50 months on 360; ordinary aggregated reports are unaffected.

Universal Analytics access and deletion began ending in July 2024. Only independently saved exports remain available.

You don't need to run an export to talk to us, and there's no need to clean it first — removing personal data is part of our work.