DatriseAI-first ETL

Delighted Looker Studio

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

How Datrise loads Delighted into Looker Studio

Datrise syncs Delighted's surveys, responses, scores, and follow-up workflows 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

Delighted: NPS and micro-survey feedback platform.

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

How Delighted entities map to Looker Studio

Delighted entityLooker Studio objectNotes
surveysdelighted_surveysid PK · custom fields → flattened columns for chart fields
responsesdelighted_responsesid PK · linked to delighted_surveys
scoresdelighted_scoresid PK · linked to delighted_surveys
follow-up workflowsdelighted_follow_up_workflowsid PK · linked to delighted_surveys

FAQ

How does Datrise handle Delighted'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 Delighted 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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