Odoo CRM → Looker
AI-first ETL from Odoo CRM into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads Odoo CRM into Looker
Datrise syncs Odoo CRM's modular CRM entities, opportunities, and revenue process data into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.
Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.
Ideal for governed, version-controlled BI on a warehouse.
Endpoints
Odoo CRM: Modular CRM in the Odoo suite for leads, opportunities, and revenue.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How Odoo CRM entities map to Looker
| Odoo CRM entity | Looker object | Notes |
|---|---|---|
| modular CRM entities | odoo_crm_modular_crm_entities | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| opportunities | odoo_crm_opportunities | id PK · linked to odoo_crm_modular_crm_entities |
| revenue process data | odoo_crm_revenue_process_data | id PK · linked to odoo_crm_modular_crm_entities |
FAQ
How does Datrise handle Odoo CRM's custom fields in Looker?
Flexible values are stored as flattened columns (nested fields expanded for modeling), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker types.
How does the Odoo CRM to Looker sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.
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