DatriseAI-first ETL

Propertybase Birst

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

How Datrise loads Propertybase into Birst

Datrise syncs Propertybase'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

Propertybase: Real estate CRM for leads, listings, and agent follow-up.

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

How Propertybase entities map to Birst

Propertybase entityBirst objectNotes
contactspropertybase_contactsid PK · custom fields → flattened columns
accountspropertybase_accountsid PK · linked to propertybase_contacts
dealspropertybase_dealsid PK · linked to propertybase_contacts
activitiespropertybase_activitiesdate/time dimensions events

FAQ

How does Datrise handle Propertybase'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 Propertybase 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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