DatriseAI-first ETL

Klarna to Looker Integration

AI-first ETL from Klarna into Looker. Governed entities, incremental sync, typed landing tables.

How Datrise loads Klarna into Looker

Datrise syncs Klarna's orders, payments, customers, settlements, refunds, and disputes into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.

Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.

Ideal for governed, version-controlled BI on a warehouse.

Endpoints

Klarna: Buy-now-pay-later checkout and settlements.

Looker: Google Cloud BI with LookML semantic models and governed dashboards.

How Klarna entities map to Looker

Klarna entityLooker objectNotes
ordersklarna_ordersid PK · custom fields → flattened columns (nested fields expanded for modeling)
paymentsklarna_paymentsid PK · linked to klarna_orders
customersklarna_customersid PK · linked to klarna_orders
settlementsklarna_settlementsid PK · linked to klarna_orders

FAQ

How does Datrise handle Klarna's custom fields in Looker?

Flexible values are stored as flattened columns (nested fields expanded for modeling), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker types.

How does the Klarna to Looker sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.

Related pipelines

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