DatriseAI-first ETL

Google Analytics GoodData

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

How Datrise loads Google Analytics into GoodData

Datrise syncs Google Analytics's sessions, events, channels, conversions, and behavior cohorts into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.

Ideal for embedded, multi-tenant analytics.

Endpoints

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

GoodData: Composable analytics platform with headless BI and embedded dashboards.

How Google Analytics entities map to GoodData

Google Analytics entityGoodData objectNotes
sessionsgoogle_analytics_sessionsid PK · custom fields → flattened columns
eventsgoogle_analytics_eventsdate dimensions 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 GoodData?

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

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

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

Related pipelines

Early access

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