DatriseAI-first ETL

Google Ecommerce GoodData

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

How Datrise loads Google Ecommerce into GoodData

Datrise syncs Google Ecommerce's records, events, and configuration objects 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 Ecommerce: SaaS or API data source for analytics and warehouse sync.

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

How Google Ecommerce entities map to GoodData

Google Ecommerce entityGoodData objectNotes
recordsgoogle_ecommerce_recordsid PK · custom fields → flattened columns
eventsgoogle_ecommerce_eventsdate dimensions events
configuration objectsgoogle_ecommerce_configuration_objectsid PK · linked to google_ecommerce_records

FAQ

How does Datrise handle Google Ecommerce'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 Ecommerce to GoodData sync stay up to date?

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

Related pipelines

Early access

Connect Google Ecommerce to GoodData the easy way

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