DatriseAI-first ETL

Google Ecommerce to Birst Integration

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

How Datrise loads Google Ecommerce into Birst

Datrise syncs Google Ecommerce's transactions, products, product impressions, checkout steps, revenue, and refunds into Birst as warehouse tables for Birst's automated star schema. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the source tables Birst ingests, so re-runs update only what changed. Date-partitioned facts. Birst builds its own semantic layer, so Datrise lands conformed, well-keyed tables it can automate against.

Ideal for networked, governed enterprise BI.

Endpoints

Google Ecommerce: Ecommerce reporting from Google Analytics.

Birst: Cloud BI with networked analytics and enterprise semantic layers.

How Google Ecommerce entities map to Birst

Google Ecommerce entityBirst 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 Birst?

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 Birst types.

How does the Google Ecommerce to Birst sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.

Related pipelines

Early access

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