DatriseAI-first ETL

UserVoice to Looker Studio Integration

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

How Datrise loads UserVoice into Looker Studio

Datrise syncs UserVoice's suggestions, votes, comments, users, forums, and statuses 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

UserVoice: Product feedback, ideas, and feature requests.

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

How UserVoice entities map to Looker Studio

UserVoice entityLooker Studio objectNotes
suggestionsuservoice_suggestionsid PK · custom fields → flattened columns for chart fields
votesuservoice_votesid PK · linked to uservoice_suggestions
commentsuservoice_commentsid PK · linked to uservoice_suggestions
usersuservoice_usersid PK · linked to uservoice_suggestions

FAQ

How does Datrise handle UserVoice'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 UserVoice 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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