DatriseAI-first ETL

Import API Looker Studio

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

How Datrise loads Import API into Looker Studio

Datrise syncs Import API's records, events, and configuration objects 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

Import API: SaaS or API data source for analytics and warehouse sync.

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

How Import API entities map to Looker Studio

Import API entityLooker Studio objectNotes
recordsimport_api_recordsid PK · custom fields → flattened columns for chart fields
eventsimport_api_eventsdate dimension columns events
configuration objectsimport_api_configuration_objectsid PK · linked to import_api_records

FAQ

How does Datrise handle Import API'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 Import API to Looker Studio sync stay up to date?

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

Related pipelines

Early access

Connect Import API to Looker Studio the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.