DatriseAI-first ETL

Manatal Birst

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

How Datrise loads Manatal into Birst

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

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

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

How Manatal entities map to Birst

Manatal entityBirst objectNotes
contactsmanatal_contactsid PK · custom fields → flattened columns
accountsmanatal_accountsid PK · linked to manatal_contacts
dealsmanatal_dealsid PK · linked to manatal_contacts
activitiesmanatal_activitiesdate/time dimensions events

FAQ

How does Datrise handle Manatal'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 Manatal 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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