Linnworks to Looker Integration
AI-first ETL from Linnworks into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads Linnworks into Looker
Datrise syncs Linnworks's orders, stock items, channels, shipments, suppliers, and inventory levels 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
Linnworks: Multichannel order and inventory management.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How Linnworks entities map to Looker
| Linnworks entity | Looker object | Notes |
|---|---|---|
| orders | linnworks_orders | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| stock items | linnworks_stock_items | id PK · linked to linnworks_orders |
| channels | linnworks_channels | id PK · linked to linnworks_orders |
| shipments | linnworks_shipments | id PK · linked to linnworks_orders |
FAQ
How does Datrise handle Linnworks'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 Linnworks to Looker sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.
Related pipelines
More destinations for Linnworks
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