Import API to Looker Studio Integration
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, payloads, batches, schemas, ingest timestamps, and source keys 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: Direct API push of custom records into a pipeline.
Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).
How Import API entities map to Looker Studio
| Import API entity | Looker Studio object | Notes |
|---|---|---|
| records | import_api_records | id PK · custom fields → flattened columns for chart fields |
| payloads | import_api_payloads | id PK · linked to import_api_records |
| batches | import_api_batches | id PK · linked to import_api_records |
| schemas | import_api_schemas | id 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
More destinations for Import API
More sources for Looker Studio
Early access
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