DatriseAI-first ETL

PCRecruiter Looker

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

How Datrise loads PCRecruiter into Looker

Datrise syncs PCRecruiter's contacts, accounts, deals, activities, and lifecycle events 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

PCRecruiter: Recruiting CRM/ATS for candidates, pipelines, and placements.

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

How PCRecruiter entities map to Looker

PCRecruiter entityLooker objectNotes
contactspcrecruiter_contactsid PK · custom fields → flattened columns (nested fields expanded for modeling)
accountspcrecruiter_accountsid PK · linked to pcrecruiter_contacts
dealspcrecruiter_dealsid PK · linked to pcrecruiter_contacts
activitiespcrecruiter_activitiesdate/time dimension columns events

FAQ

How does Datrise handle PCRecruiter'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 PCRecruiter 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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