DatriseAI-first ETL

Google Analytics Amazon QuickSight

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

How Datrise loads Google Analytics into Amazon QuickSight

Datrise syncs Google Analytics's sessions, events, channels, conversions, and behavior cohorts into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

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

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Google Analytics entities map to Amazon QuickSight

Google Analytics entityAmazon QuickSight objectNotes
sessionsgoogle_analytics_sessionsid PK · custom fields → flattened columns for analyses
eventsgoogle_analytics_eventsdate/time fields 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 Amazon QuickSight?

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

How does the Google Analytics to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

Early access

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