When you set up BigQuery export for your GA4 data, you get the option to include a daily export of users data in your BigQuery project:

Once you have successfully connected your GA4 property with BigQuery and more than 24 hrs have elapsed, you should be able to see the imported GA4 data in the dataset named “analytics_<property_id>“:

This dataset can contain the following four data tables, which contain your GA4 data:

1. events_(<number of days>)
2. events_intraday_<current date>
3. pseudonymous_users_(<number of days>)
4. users_(<number of days>)

The ‘events_’ and ‘events_intraday_’ data tables contain event-based and user-based GA4 export data in BigQuery.

Whereas the ‘pseudonymous_users_’ and ‘users _’ data tables contain only user-based GA4 export data in BigQuery.

The advantage of using the ‘pseudonymous_users_’ and ‘users _’ data tables over the ‘events_’ and ‘events_intraday_’ data tables is that you get access to more user data.

The ‘pseudonymous_users_’ and ‘users _’ data tables contain audience and prediction data which is not available in the ‘events_’ and ‘events_intraday_’ data tables.

What is pseudonymous_users_ data table in BigQuery for GA4?

The ‘pseudonymous_users_’ data table contains all the data for every pseudonymous identifier that is not user ID.

The ‘pseudonymous_users_’ data table is updated whenever data for a user is updated.

pseudonymous_users_(1) means all the data for every pseudonymous identifier that is not a user ID from the previous day is available in this data table.

pseudonymous_users_(2) means all the data for every pseudonymous identifier that is not a user ID from the previous two days is available in this data table.

Similarly, 

pseudonymous_users_(5) means all the data for every pseudonymous identifier that is not a user ID from the previous five days is available in this data table.

What are pseudonymous identifiers?

A pseudonymous identifier is a unique identifier created and assigned to each user by Google Analytics to track users across devices and sessions and to create a complete picture of their behaviour. 

There are three main ways to create a pseudonymous identifier in GA4:

#1 User ID – You can create your own unique identifier for each user and send it to Google Analytics. You can use the login id as the user id.

#2 Google Signals – Google Signals is a feature that allows you to track users across devices and platforms, provided they are signed in to their Google accounts across devices and have turned on ad personalization.

#3 Device ID – This is the default method GA4 uses to track users based on the device they’re using. If you aren’t using User ID or Google Signals, the device IDs are used.

The ‘pseudonymous_users_’ data table corresponds to the ‘Daily’ frequency setting under ‘User data’ of ‘BigQuery Links’ in your GA4 property:

Clicking on the ‘pseudonymous_users_’ data table will show you the structure of that table (also known as ‘Schema’):

The ‘pseudonymous_users_’ data tables are named “pseudonymous_users_YYYYMMDD”, where “YYYYMMDD” refers to the date the table was imported to BigQuery.

YYYY denotes a year. 

For example, 2023

MM denotes a month. 

For example, 08 (i.e. August)

DD denotes a day. 

For example, 19

So the data table that was imported to BigQuery on Aug 19, 2023, would be named ‘pseudonymous_users_20230819‘

Click on the ‘Details’ tab to get details (like ‘Table ID’) of the ‘pseudonymous_users_’ data table:

Click on the ‘Preview’ tab to view the data in the ‘pseudonymous_users_’ data table without running a single query:

Click on the ‘QUERY’ drop-down menu if you want to query the ‘pseudonymous_users_ ‘ data table.

Note: The ‘pseudonymous_users_’ data table is not available to you in your BigQuery project if the ‘daily’ export type under ‘User data’ is not enabled when you link your GA4 property with your BigQuery project.

What is ‘users_’ data table in BigQuery for GA4?

The ‘users_’ data table contains all the data for every pseudonymous identifier that is a user ID.

Data for a user is updated when there is a change to one of the fields.

Important points to remember about the ‘users_’ data table

#1 The ‘users_’ data table is not available to you in your BigQuery project if you are not using the user-id tracking in GA4.

#2 The ‘users_’ data table is not available to you in your BigQuery project if the ‘daily’ export type under ‘User data’ is not enabled when you link your GA4 property with your BigQuery project.

#3 Unlike in the ‘pseudonymous_users_’ data table, the data for unconsented users can be exported to the ‘users_’ table if it includes a user ID.