Capsule CRM → Looker
AI-first ETL from Capsule CRM into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads Capsule CRM into Looker
Datrise syncs Capsule CRM's contacts, opportunities, tracks, and lightweight sales 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
Capsule CRM: SMB CRM for contacts, opportunities, and lightweight workflows.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How Capsule CRM entities map to Looker
| Capsule CRM entity | Looker object | Notes |
|---|---|---|
| contacts | capsule_crm_contacts | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| opportunities | capsule_crm_opportunities | id PK · linked to capsule_crm_contacts |
| tracks | capsule_crm_tracks | id PK · linked to capsule_crm_contacts |
| lightweight sales process data | capsule_crm_lightweight_sales_process_data | id PK · linked to capsule_crm_contacts |
FAQ
How does Datrise handle Capsule 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 Capsule CRM to Looker sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.
Related pipelines
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