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 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.
A full export of data takes place once a day. Data is also exported continuously throughout the day (see Streaming export below).
There are no billing charges associated with exporting data from a Google Analytics 4 property to BigQuery. You can export to a free instance of BigQuery (BigQuery sandbox), but exports that exceed the sandbox limits incur charges.
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 two new tables:
events_intraday_YYYYMMDD: is an internal staging table that includes records of session activity 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: 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.
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