DatriseAI-first ETL

Manatal Tableau

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

How Datrise loads Manatal into Tableau

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

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

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

How Manatal entities map to Tableau

Manatal entityTableau objectNotes
contactsmanatal_contactsid PK · custom fields → flattened columns for Tableau fields
accountsmanatal_accountsid PK · linked to manatal_contacts
dealsmanatal_dealsid PK · linked to manatal_contacts
activitiesmanatal_activitiesdate/datetime fields events

FAQ

How does Datrise handle Manatal'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 Manatal 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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