DatriseAI-first ETL

SurveyCTO to Looker Integration

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

How Datrise loads SurveyCTO into Looker

Datrise syncs SurveyCTO's form submissions, forms, fields, answers, enumerators, and submission timestamps 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

SurveyCTO: Offline-capable field survey data collection.

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

How SurveyCTO entities map to Looker

SurveyCTO entityLooker objectNotes
form submissionssurveycto_form_submissionsid PK · custom fields → flattened columns (nested fields expanded for modeling)
formssurveycto_formsid PK · linked to surveycto_form_submissions
fieldssurveycto_fieldsid PK · linked to surveycto_form_submissions
answerssurveycto_answersid PK · linked to surveycto_form_submissions

FAQ

How does Datrise handle SurveyCTO'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 SurveyCTO 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

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