DatriseAI-first ETL

Google Analytics Metabase

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

How Datrise loads Google Analytics into Metabase

Datrise syncs Google Analytics's sessions, events, channels, conversions, and behavior cohorts into Metabase as clean SQL tables Metabase auto-discovers. Flexible or custom fields land in flattened columns for the question builder, and timestamps such as created, updated, and status changes are typed as temporal columns for trends.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for large questions. Metabase auto-scans schemas, so Datrise uses readable table and column names so the no-code UI stays self-explanatory.

Ideal for self-serve questions and dashboards for whole teams.

Endpoints

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

Metabase: Open-source analytics with questions, dashboards, and embedded insights.

How Google Analytics entities map to Metabase

Google Analytics entityMetabase objectNotes
sessionsgoogle_analytics_sessionsid PK · custom fields → flattened columns for the question builder
eventsgoogle_analytics_eventstemporal columns for trends 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 Metabase?

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

How does the Google Analytics to Metabase sync stay up to date?

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

Related pipelines

Early access

Connect Google Analytics to Metabase the easy way

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