Google Analytics Aggregated connector

Beta

This feature is in Beta. To use it, a workspace admin must turn on Lakeflow Connect for Google Analytics Aggregated from the Previews page. See Manage Databricks previews.

The managed Google Analytics Aggregated connector in Lakeflow Connect ingests aggregated Google Analytics 4 (GA4) report data, such as users, sessions, events, acquisition, ecommerce, and demographics metrics, from the Google Analytics Data API into Databricks. It also supports custom reports with the dimensions and metrics that you select.

note

To ingest raw, event-level GA4 data that Google Analytics exports to BigQuery, use the Google Analytics Raw Data connector instead.

Feature availability

Feature	Availability
UI-based pipeline authoring	Not supported
API-based pipeline authoring	Supported
Declarative Automation Bundles	Supported
Incremental ingestion	Supported
Unity Catalog governance	Supported
Orchestration using Lakeflow Jobs	Supported
API-based column selection and deselection	Supported
API-based row filtering	Not supported
Slowly changing dimensions (SCD) type 2	Supported
Automated schema evolution: New and deleted columns	Supported
Automated schema evolution: Data type changes	Not supported
Automated schema evolution: Column renames	Not supported Requires a full refresh.

Feature	Availability
UI-based pipeline authoring	Not supported
API-based pipeline authoring	Supported
Declarative Automation Bundles	Supported
Incremental ingestion	Supported
Unity Catalog governance	Supported
Orchestration using Lakeflow Jobs	Supported
API-based column selection and deselection	Supported
API-based row filtering	Not supported
Slowly changing dimensions (SCD) type 2	Supported
Automated schema evolution: New and deleted columns	Supported
Automated schema evolution: Data type changes	Not supported
Automated schema evolution: Column renames	Not supported Requires a full refresh.

Authentication methods

Authentication method	Availability
Service account (OAuth 2.0 machine-to-machine) (Recommended)	Supported
OAuth 2.0 user-to-machine (U2M)	Supported
Basic authentication (username/password)	Not supported
Basic authentication (API key)	Not supported

Authentication method	Availability
Service account (OAuth 2.0 machine-to-machine) (Recommended)	Supported
OAuth 2.0 user-to-machine (U2M)	Supported
Basic authentication (username/password)	Not supported
Basic authentication (API key)	Not supported

Ingest from Google Analytics in 3 steps

note

Before starting, review the Databricks user persona, supported interfaces, ingestion frequency, and common patterns.

1. Configure Google Analytics for ingestion (Admins): Set up Google Analytics to authenticate with Databricks.
2. Create a Unity Catalog connection (Admins): Create a connection in Catalog Explorer to store credentials for Databricks to authenticate with Google Analytics.
3. Create an ingestion pipeline (Admins or non-admins): Select any supported interface and create a pipeline from an existing connection.