DatriseAI-first ETL

Ga4 Looker Studio

AI-first ETL from Ga4 into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Ga4 into Looker Studio

Datrise syncs Ga4's records, events, and configuration objects into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

Ga4: SaaS or API data source for analytics and warehouse sync.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Ga4 entities map to Looker Studio

Ga4 entityLooker Studio objectNotes
recordsga4_recordsid PK · custom fields → flattened columns for chart fields
eventsga4_eventsdate dimension columns events
configuration objectsga4_configuration_objectsid PK · linked to ga4_records

FAQ

How does Datrise handle Ga4's custom fields in Looker Studio?

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

How does the Ga4 to Looker Studio sync stay up to date?

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

Related pipelines

Early access

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