DatriseAI-first ETL

Google Analytics Looker Studio

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

How Datrise loads Google Analytics into Looker Studio

Datrise syncs Google Analytics's sessions, events, channels, conversions, and behavior cohorts 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

Google Analytics: Web and product analytics for behavior and traffic insights.

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

How Google Analytics entities map to Looker Studio

Google Analytics entityLooker Studio objectNotes
sessionsgoogle_analytics_sessionsid PK · custom fields → flattened columns for chart fields
eventsgoogle_analytics_eventsdate dimension columns events
channelsgoogle_analytics_channelsid PK · linked to google_analytics_sessions
conversionsgoogle_analytics_conversionsid PK · linked to google_analytics_sessions

FAQ

How does Datrise handle Google Analytics'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 Google Analytics 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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