DatriseAI-first ETL

Delighted Amazon QuickSight

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

How Datrise loads Delighted into Amazon QuickSight

Datrise syncs Delighted's surveys, responses, scores, and follow-up workflows into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

Delighted: NPS and micro-survey feedback platform.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Delighted entities map to Amazon QuickSight

Delighted entityAmazon QuickSight objectNotes
surveysdelighted_surveysid PK · custom fields → flattened columns for analyses
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 Amazon QuickSight?

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

How does the Delighted to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

Early access

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