DatriseAI-first ETL

Odoo CRM Looker Studio

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

How Datrise loads Odoo CRM into Looker Studio

Datrise syncs Odoo CRM's modular CRM entities, opportunities, and revenue process data 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

Odoo CRM: Modular CRM in the Odoo suite for leads, opportunities, and revenue.

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

How Odoo CRM entities map to Looker Studio

Odoo CRM entityLooker Studio objectNotes
modular CRM entitiesodoo_crm_modular_crm_entitiesid PK · custom fields → flattened columns for chart fields
opportunitiesodoo_crm_opportunitiesid PK · linked to odoo_crm_modular_crm_entities
revenue process dataodoo_crm_revenue_process_dataid PK · linked to odoo_crm_modular_crm_entities

FAQ

How does Datrise handle Odoo CRM'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 Odoo CRM 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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