DatriseAI-first ETL

Virtuous to Looker Integration

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

How Datrise loads Virtuous into Looker

Datrise syncs Virtuous's contacts, gifts, projects, campaigns, communications, and recurring gifts 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

Virtuous: Responsive fundraising with donor signals and automation.

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

How Virtuous entities map to Looker

Virtuous entityLooker objectNotes
contactsvirtuous_contactsid PK · custom fields → flattened columns (nested fields expanded for modeling)
giftsvirtuous_giftsid PK · linked to virtuous_contacts
projectsvirtuous_projectsid PK · linked to virtuous_contacts
campaignsvirtuous_campaignsid PK · linked to virtuous_contacts

FAQ

How does Datrise handle Virtuous'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 Virtuous 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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