DatriseAI-first ETL

Workable to Birst Integration

AI-first ETL from Workable into Birst. Governed entities, incremental sync, typed landing tables.

How Datrise loads Workable into Birst

Datrise syncs Workable's candidates, jobs, applications, interviews, offers, and pipeline stages into Birst as warehouse tables for Birst's automated star schema. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the source tables Birst ingests, so re-runs update only what changed. Date-partitioned facts. Birst builds its own semantic layer, so Datrise lands conformed, well-keyed tables it can automate against.

Ideal for networked, governed enterprise BI.

Endpoints

Workable: Recruiting pipeline and candidate evaluation.

Birst: Cloud BI with networked analytics and enterprise semantic layers.

How Workable entities map to Birst

Workable entityBirst objectNotes
candidatesworkable_candidatesid PK · custom fields → flattened columns
jobsworkable_jobsid PK · linked to workable_candidates
applicationsworkable_applicationsid PK · linked to workable_candidates
interviewsworkable_interviewsid PK · linked to workable_candidates

FAQ

How does Datrise handle Workable's custom fields in Birst?

Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Birst types.

How does the Workable to Birst sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.

Related pipelines

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