Nectar CRM to Looker Integration
AI-first ETL from Nectar CRM into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads Nectar CRM into Looker
Datrise syncs Nectar CRM's contacts, companies, opportunities, sales stages, activities, and quotes 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
Nectar CRM: B2B sales CRM with playbooks for Brazilian teams.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How Nectar CRM entities map to Looker
| Nectar CRM entity | Looker object | Notes |
|---|---|---|
| contacts | nectar_crm_contacts | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| companies | nectar_crm_companies | id PK · linked to nectar_crm_contacts |
| opportunities | nectar_crm_opportunities | id PK · linked to nectar_crm_contacts |
| sales stages | nectar_crm_sales_stages | id PK · linked to nectar_crm_contacts |
FAQ
How does Datrise handle Nectar 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 Nectar CRM to Looker sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.
Related pipelines
More destinations for Nectar CRM
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