DatriseAI-first ETL

Google Analytics 4 to Mode Integration

AI-first ETL from Google Analytics 4 into Mode. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Analytics 4 into Mode

Datrise syncs Google Analytics 4's events, users, sessions, traffic sources, conversions, and audiences into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

Google Analytics 4: Event-based web and app analytics from Google.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Google Analytics 4 entities map to Mode

Google Analytics 4 entityMode objectNotes
eventsga4_eventstemporal columns events
usersga4_usersid PK · linked to ga4_events
sessionsga4_sessionsid PK · linked to ga4_events
traffic sourcesga4_traffic_sourcesid PK · linked to ga4_events

FAQ

How does Datrise handle Google Analytics 4's custom fields in Mode?

Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.

How does the Google Analytics 4 to Mode sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

Connect Google Analytics 4 to Mode the easy way

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