[GA4] BigQuery Export

Exporting Data from Google Analytics 4 Properties to BigQuery

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BigQuery is a cloud data warehouse that lets you run highly performant queries of large datasets.

You can export all of your raw events from Google Analytics 4 properties (including subproperties and roll-up properties) to BigQuery, and then use an SQL-like syntax to query that data. In BigQuery, you can choose to export your data to external storage or import external data for the purposes of combining it with 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.

Note: Once you export data from Analytics to BigQuery, you cannot re-export it.

A full export of data takes place once a day. Data is also exported continuously throughout the day (see Streaming export below).

You can export to a free instance of BigQuery (BigQuery sandbox), but exports that exceed the sandbox limits incur charges.

Standard properties have a daily BigQuery Export limit of 1 million events. Learn more about other BigQuery Export limits

BigQuery Export types

Google Analytics offers the following BigQuery export options, each differing in data availability for the current day and should be chosen based on your data needs and budget:

Export types	Best when you require...	Export details	Limits	Caveats
Daily export (Standard, 360)	a complete set of data for the previous day and don't need data fast or aren't a 360 customer	Exports all the raw, unsampled event data once per day from the previous day Specific time not guaranteed Typically exports mid-afternoon in your property's timezone, but can be delayed until later in the day or the next day Last click observed, no modeling	Standard properties: up to 1M events per day, with filtering options to stay under limit 360 properties: up to 20B events per day	Some data, like user attribution, might be delayed by up to 24 hours; we recommend using daily export instead of streaming for user attribution data
Fresh daily (360)	faster, more complete data throughout the day	Data typically arrives by 5am Batched updates throughout the day, typically within 60 minutes Same schema as daily export Export begins based on property's timezone Last click observed, no modeling Much faster than the daily export	SLA is not available for the few XL properties	Only available for "Normal" and "Large" 360 properties.
Streaming (Standard, 360)	near realtime data (within minutes)	A realtime export of the current day's data Best-effort service: operates without a completeness SLO and may contain data gaps	No volume limits	New user and new session traffic source data is excluded from export

Note: Each export will incur costs on the BigQuery side for storage and processing. You will incur additional BigQuery costs for using streaming export at the rate of $0.05 per gigabyte of data. 1 gigabyte equates to approximately 600,000 Google Analytics events, though that number will vary depending on event size. Learn more about BigQuery pricing.

Differences between the Google Analytics interface and BigQuery Export

The BigQuery event export provides access to raw event and user-level data, excluding any value additions that Google Analytics makes to the data found in standard reports and explorations. For this reason, the data from BigQuery event export might differ from the data in the Google Analytics interface.

To understand the differences between BigQuery event export and the Google Analytics interface, and explore ways to mitigate these differences when possible, see Bridging the gap between Google Analytics UI and BigQuery export.

Streaming export

You can choose the streaming export option when you link your Google Analytics 4 property to BigQuery.

BigQuery streaming export makes data for the current day available within a few minutes via BigQuery Export.

When you use this export option, BigQuery has more recent information you can analyze about your users and their traffic on your property.

For each day, streaming export creates one new table:

• events_intraday_YYYYMMDD: An internal staging table that includes records of session activity that took place during the day. Streaming export is a best-effort operation and may not include all data for reasons such as the processing of late events and/or failed uploads. Data is exported continuously throughout the day. This table can include records of a session when that session spans multiple export operations.This table is deleted when events_YYYYMMDD is complete.

If you select the daily option when you set up BigQuery Export, then the following table is also created each day.

• events_YYYYMMDD: The full daily export of events.

You should query events_YYYYMMDD rather than events_intraday_YYYYMMDD so you're querying a stable dataset for the day.

See BigQuery Export schema for more information about the events_YYYYMMDD and events_intraday_YYYYMMDD tables.

BigQuery streaming export does not include the following user-attribution data for new users:

• traffic_source.name (reporting dimension: User campaign)
• traffic_source.source (reporting dimension: User source)
• traffic_source.medium (reporting dimension: User medium)

User-attribution data for existing users is included but that data requires ~24 hours to fully process, so we recommend not relying on that data from the streaming export and instead getting user-attribution data from the full daily export.

You will incur additional BigQuery costs for using streaming export at the rate of $0.05 per gigabyte of data. 1 gigabyte equates to approximately 600,000 Google Analytics events, though that number will vary depending on event size. Learn more about BigQuery pricing.

Fresh Daily export

You can now select Fresh Daily export in addition to Daily and Streaming export options. Fresh Daily export is currently available for Analytics 360 properties, and each of the 3 export options can be enabled independently of one another.

To configure Fresh Daily export, you must have billing set up on Google Cloud Platform. Learn more about the BigQuery Fresh Daily export (GA360).

The schedule for table updates

Updates to the tables that are created as part of BigQuery Export are governed by the time zone of the Analytics property from which data is being exported. If the property time zone is changed, it will impact the BigQuery export, which may lead to data discrepancy or the daily export will be skipped.

Streaming-export tables (events_intraday_YYYYMMDD) are updated continuously throughout the day (e.g., from 12:00:00 am until 11:59:59 pm in the property's time zone). Once a new day starts in the property's time zone, events are written to a new intraday table.

Daily export tables (events_YYYYMMDD) are created after Analytics collects all of the events for the day. Analytics will update daily tables for up to 72 hours beyond the date of the table with events that are timestamped with the date of the table, e.g., event bundles that come in late from Measurement Protocol or the Firebase SDKs. For example, if the table date is 20220101, then Analytics will update the table through 20220104 with events that are timestamped 20220101.

On occasion, Analytics may update the daily tables anytime after the 72-hour window under circumstances that require Analytics to reprocess historical data (e.g., a bug fix that remedies a processing error).

Cookieless pings and customer-provided data

When consent mode is implemented, cookieless pings collected by Analytics will be present in the BigQuery export, along with customer-provided data such as user_id and custom dimensions.

Backfill “Not Available” traffic source dimensions

You can use the following resources to lookup attributed traffic source dimensions for a given GCLID. Note that wBRAID and gBRAID identifiers aren't included in the BigQuery Export.

• Google Ads API
• Google Ads Scripts
• BigQuery Data Transfer Service for Google Ads

To find the GCLID for a "Not Available" record in the "traffic_source" column, query the GCLID field in the “collected_traffic_source” column. For more details on how to lookup campaign information in Google Ads from a given GCLID, see BigQuery Export Service Level Agreement.

GA4 - Firebase Integration and BigQuery

If a GA4 property and a Firebase project are integrated, they cannot be linked to separate BigQuery projects.

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
Fresh Daily export Available on “Normal” and “Large” 360 properties Learn more about processing differences between daily export and fresh daily.	Not applicable
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 GA4 only exports the traffic source that first acquired the user Does not support UA data exported to BigQuery 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 Session-level attribution across multiple touch points 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.

Related resources

Visit the BigQuery Developers Guide to learn more about:

• Google Analytics (GA4) and BigQuery
• Google BigQuery
• BigQuery ACLs
• BigQuery syntax