EspoCRM → Looker Studio
AI-first ETL from EspoCRM into Looker Studio. Governed entities, incremental sync, typed landing tables.
How Datrise loads EspoCRM into Looker Studio
Datrise syncs EspoCRM's pipeline entities, custom objects, and process automation events 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
EspoCRM: Open-source CRM for pipeline management and custom entity modeling.
Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).
How EspoCRM entities map to Looker Studio
| EspoCRM entity | Looker Studio object | Notes |
|---|---|---|
| pipeline entities | espocrm_pipeline_entities | id PK · custom fields → flattened columns for chart fields |
| custom objects | espocrm_custom_objects | id PK · linked to espocrm_pipeline_entities |
| process automation events | espocrm_process_automation_events | date dimension columns events |
FAQ
How does Datrise handle EspoCRM'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 EspoCRM to Looker Studio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for EspoCRM
More sources for Looker Studio
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