DatriseAI-first ETL

Aftership to Looker Studio Integration

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

How Datrise loads Aftership into Looker Studio

Datrise syncs Aftership's shipments, trackings, checkpoints, couriers, delivery statuses, and notifications into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

Aftership: Shipment tracking and delivery notifications.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Aftership entities map to Looker Studio

Aftership entityLooker Studio objectNotes
shipmentsaftership_shipmentsid PK · custom fields → flattened columns for chart fields
trackingsaftership_trackingsid PK · linked to aftership_shipments
checkpointsaftership_checkpointsid PK · linked to aftership_shipments
couriersaftership_couriersid PK · linked to aftership_shipments

FAQ

How does Datrise handle Aftership's custom fields in Looker Studio?

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

How does the Aftership to Looker Studio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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