DatriseAI-first ETL

Lever to Tableau Integration

AI-first ETL from Lever into Tableau. Governed entities, incremental sync, typed landing tables.

How Datrise loads Lever into Tableau

Datrise syncs Lever's candidates, opportunities, postings, interviews, offers, and feedback forms into Tableau as warehouse tables or a refreshed .hyper extract. Flexible or custom fields land in flattened columns for Tableau fields, and timestamps such as created, updated, and status changes are typed as date/datetime fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind a live connection or extract, so re-runs update only what changed. Date-partitioned facts to keep extract refresh quick. Tableau .hyper extracts snapshot data, so Datrise keeps the source tables incremental and lets you choose live vs extract.

Ideal for visual analytics and dashboards in Tableau.

Endpoints

Lever: Applicant tracking and candidate relationship management.

Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.

How Lever entities map to Tableau

Lever entityTableau objectNotes
candidateslever_candidatesid PK · custom fields → flattened columns for Tableau fields
opportunitieslever_opportunitiesid PK · linked to lever_candidates
postingslever_postingsid PK · linked to lever_candidates
interviewslever_interviewsid PK · linked to lever_candidates

FAQ

How does Datrise handle Lever's custom fields in Tableau?

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

How does the Lever to Tableau sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.

Related pipelines

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