This article is about Universal Analytics properties, which will stop processing data on July 1, 2023 (October 1, 2023 for Analytics 360 properties). If you haven't already, start using a Google Analytics 4 property.

BigQuery Export for Analytics

Use BigQuery to quickly query all of your Analytics data.
This feature is only available in Analytics 360, part of Google Marketing Platform.
Learn more about Google Marketing Platform.

BigQuery is a cloud data warehouse that lets you run super-fast queries of large datasets.

You can export session and hit data from a Google Analytics 360 account to BigQuery, and then use a SQL-like syntax to query all of your Analytics data.

When you export data to BigQuery, you own that data, and you can use BigQuery ACLs to manage permissions on projects and datasets.

 

Compare BigQuery Export in Google Analytics 4 and Universal Analytics

Google Analytics 4 Universal Analytics

Available to Standard (free) and 360 (paid)

Standard limit: 1M events per day

360 limit: Billions of events per day

Available to 360 (paid)

Cost

Free export to BigQuery Sandbox within Sandbox limits

Exported data that exceeds Sandbox limits incurs charges per contract terms

Cost

Free export to BigQuery Sandbox within Sandbox limits

Exported data that exceeds Sandbox limits incurs charges per contract terms

Setup

Can include specific data streams and exclude specific events for each property

(lets you control export volume and cost)

Setup

Can link 1 view per property

(exports all data in that view)

Streaming export

$0.05 per GB (learn more about BigQuery pricing)

Table created:

events_intraday_YYYYMMDD

Table is deleted each day:

  • if you also use the daily-export option in addition to streaming
  • when the daily table is complete

Does not include User campaign, User source, or User medium data for new users

Streaming export

$0.05 per GB (learn more about BigQuery pricing)

Table created:

ga_realtime_sessions_YYYYMMDD

BigQuery view created:

ga_realtime_sessions_view_YYYYMMDD

Daily export

Table created:

events_YYYYMMDD

Daily export

Tables created

ga_sessions_intraday_YYYYMMDD

  • Updated at least 3 times per day
  • Each updated overwrites previous data
  • Deleted when full import from next day is complete

ga_sessions_YYYYMMDD

  • Full daily import

Export, general

Backfill: no backfill

Dataset: for each linked property, 1 dataset named analytics_<property id>

If you've implemented consent mode, export includes:

  • cookieless pings
  • customer-provided data (user_id, custom dimensions)

Export, general

Backfill: upon linking, backfill of 13 months of data or 10B hits, whichever is smaller

(Backfill to BigQuery Sandbox can fail)

Dataset: for each linked view, 1 dataset named the same as the view

Export schema

Each row in a BigQuery table represents an event

Event data that is unique to Google Analytics 4

While there are some Google Analytics 4 fields that are essentially the same as Universal Analytics fields (e.g., device.category and device.deviceCategory), there are more differences than similarities between GA4 event data and UA hit data

Export schema

Each row in a BigQuery table represents a session

Hit data that is unique to Universal Analytics

While there are some Universal Analytics fields that are essentially the same as Google Analytics 4 fields (e.g., device.deviceCategory and device.category), there are more differences than similarities between UA hit data and GA4 event data.

 

Next step

Set up BigQuery Export.

Related resources

Visit the following guides to learn more about:

If you already have BigQuery set up, you can get acquainted with it by using our sample dataset.

Was this helpful?
How can we improve it?

Need more help?

Sign in for additional support options to quickly solve your issue

Search
Clear search
Close search
Google apps
Main menu
Search Help Center
true
69256
false
false