DatriseAI-first ETL

UserVoice to Looker Integration

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

How Datrise loads UserVoice into Looker

Datrise syncs UserVoice's suggestions, votes, comments, users, forums, and statuses into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.

Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.

Ideal for governed, version-controlled BI on a warehouse.

Endpoints

UserVoice: Product feedback, ideas, and feature requests.

Looker: Google Cloud BI with LookML semantic models and governed dashboards.

How UserVoice entities map to Looker

UserVoice entityLooker objectNotes
suggestionsuservoice_suggestionsid PK · custom fields → flattened columns (nested fields expanded for modeling)
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?

Flexible values are stored as flattened columns (nested fields expanded for modeling), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker types.

How does the UserVoice to Looker sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.

Related pipelines

Early access

Connect UserVoice to Looker 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.