DatriseAI-first ETL

Workday Looker

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

How Datrise loads Workday into Looker

Datrise syncs Workday's HR, finance entities, organizational structures, and operational 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

Workday: Enterprise HR and finance source for operational reporting.

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

How Workday entities map to Looker

Workday entityLooker objectNotes
HRworkday_hrid PK · custom fields → flattened columns (nested fields expanded for modeling)
finance entitiesworkday_finance_entitiesid PK · linked to workday_hr
organizational structuresworkday_organizational_structuresid PK · linked to workday_hr
operational eventsworkday_operational_eventsdate/time dimension columns events

FAQ

How does Datrise handle Workday'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 Workday 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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