Zoho CRM → Looker
AI-first ETL from Zoho CRM into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads Zoho CRM into Looker
Datrise syncs Zoho CRM's leads, contacts, accounts, deals, and workflow-driven field changes 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
Zoho CRM: Modular CRM with strong automation and telephony.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How Zoho CRM entities map to Looker
| Zoho CRM entity | Looker object | Notes |
|---|---|---|
| leads | zoho_crm_leads | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| contacts | zoho_crm_contacts | id PK · linked to zoho_crm_leads |
| accounts | zoho_crm_accounts | id PK · linked to zoho_crm_leads |
| deals | zoho_crm_deals | id PK · linked to zoho_crm_leads |
FAQ
How does Datrise handle Zoho 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 Zoho 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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