DatriseAI-first ETL

Propertybase Looker Studio

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

How Datrise loads Propertybase into Looker Studio

Datrise syncs Propertybase's contacts, accounts, deals, activities, and lifecycle events into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

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

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Propertybase entities map to Looker Studio

Propertybase entityLooker Studio objectNotes
contactspropertybase_contactsid PK · custom fields → flattened columns for chart fields
accountspropertybase_accountsid PK · linked to propertybase_contacts
dealspropertybase_dealsid PK · linked to propertybase_contacts
activitiespropertybase_activitiesdate dimension columns events

FAQ

How does Datrise handle Propertybase's custom fields in Looker Studio?

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

How does the Propertybase to Looker Studio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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