DatriseAI-first ETL

Shippo to Looker Integration

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

How Datrise loads Shippo into Looker

Datrise syncs Shippo's shipments, rates, labels, carriers, tracking statuses, and addresses 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

Shippo: Multi-carrier shipping labels and rates.

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

How Shippo entities map to Looker

Shippo entityLooker objectNotes
shipmentsshippo_shipmentsid PK · custom fields → flattened columns (nested fields expanded for modeling)
ratesshippo_ratesid PK · linked to shippo_shipments
labelsshippo_labelsid PK · linked to shippo_shipments
carriersshippo_carriersid PK · linked to shippo_shipments

FAQ

How does Datrise handle Shippo'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 Shippo 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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