Google Analytics Raw Data connector

The managed Google Analytics Raw Data connector in Lakeflow Connect allows you to ingest event-level data from Google Analytics 4 (GA4) into Azure Databricks using BigQuery export.

Feature availability

Feature	Availability
UI-based pipeline authoring	Yes
API-based pipeline authoring	Yes
Declarative Automation Bundles	Yes
Incremental ingestion	Yes
Unity Catalog governance	Yes
Orchestration using Databricks Workflows	Yes
SCD type 2	Yes
API-based column selection and deselection	Yes
API-based row filtering	Yes
Automated schema evolution: New and deleted columns	Yes
Automated schema evolution: Data type changes	No
Automated schema evolution: Column renames	Yes - Treated as a new column (new name) and deleted column (old name).
Automated schema evolution: New tables	Yes - If you ingest the entire schema. See the limitations on the number of tables per pipeline.
Maximum number of tables per pipeline	250

Authentication methods

Authentication method	Availability
OAuth U2M	Supported
OAuth M2M	Not supported
OAuth (manual refresh token)	Not supported
Basic authentication (username/password)	Not supported
Basic authentication (API key)	Supported (API-only)
Basic authentication (service account JSON key)	Not supported

What to know before you start

Topic	Why it matters
Azure Databricks user persona	The workflow depends on your Azure Databricks user persona: Single-user: An admin user creates a Unity Catalog connection and an ingestion pipeline. Multi-user: An admin user creates a connection for non-admin users to create pipelines with.
Authentication method	The steps to create a connection depend on the authentication method you choose.
Interface	The steps to create a pipeline depend on the interface.
Ingestion frequency	The pipeline schedule depends on your latency and cost requirements.
Common patterns	Depending on your ingestion needs, the pipeline might use configurations like history tracking, column selection, and row filtering. Supported configurations vary by connector. See Feature availability.

Start ingesting from Google Analytics

The following table provides an overview of the end-to-end Google Analytics Raw Data ingestion flow, based on user type:

User	Steps
Admin	Export your GA4 data to BigQuery. See Set up Google Analytics 4 and Google BigQuery for Azure Databricks ingestion. Either: Use Catalog Explorer to create a connection to Google Analytics Raw Data so that non-admins can create pipelines. See Google Analytics Raw Data. Use the data ingestion UI to create a connection and a pipeline at the same time. See Ingest data from Google Analytics 4.
Non-admin	Use any supported interface to create a pipeline from an existing connection. See Ingest data from Google Analytics 4.