DatriseAI-first ETL

CommCare to Looker Integration

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

How Datrise loads CommCare into Looker

Datrise syncs CommCare's cases, forms, form submissions, users, locations, and case properties 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

CommCare: Mobile data collection for field programs.

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

How CommCare entities map to Looker

CommCare entityLooker objectNotes
casescommcare_casesid PK · custom fields → flattened columns (nested fields expanded for modeling)
formscommcare_formsid PK · linked to commcare_cases
form submissionscommcare_form_submissionsid PK · linked to commcare_cases
userscommcare_usersid PK · linked to commcare_cases

FAQ

How does Datrise handle CommCare'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 CommCare to Looker sync stay up to date?

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

Related pipelines

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