DatriseAI-first ETL

Google Ecommerce to GoodData Integration

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 transactions, products, product impressions, checkout steps, revenue, and refunds 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: Ecommerce reporting from Google Analytics.

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

How Google Ecommerce entities map to GoodData

Google Ecommerce entityGoodData objectNotes
transactionsgoogle_ecommerce_transactionsid PK · custom fields → flattened columns
productsgoogle_ecommerce_productsid PK · linked to google_ecommerce_transactions
product impressionsgoogle_ecommerce_product_impressionsid PK · linked to google_ecommerce_transactions
checkout stepsgoogle_ecommerce_checkout_stepsid PK · linked to google_ecommerce_transactions

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

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