DatriseAI-first ETL

Selligent to Looker Integration

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

How Datrise loads Selligent into Looker

Datrise syncs Selligent's contacts, journeys, campaigns, message events, lists, and real-time triggers 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

Selligent: Enterprise cross-channel campaigns with real-time triggers.

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

How Selligent entities map to Looker

Selligent entityLooker objectNotes
contactsselligent_contactsid PK · custom fields → flattened columns (nested fields expanded for modeling)
journeysselligent_journeysid PK · linked to selligent_contacts
campaignsselligent_campaignsid PK · linked to selligent_contacts
message eventsselligent_message_eventsdate/time dimension columns events

FAQ

How does Datrise handle Selligent'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 Selligent 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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