DatriseAI-first ETL

Omie CRM to Looker Studio Integration

AI-first ETL from Omie CRM into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Omie CRM into Looker Studio

Datrise syncs Omie CRM's clients, opportunities, sales orders, invoices, products, and accounts receivable 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

Omie CRM: Brazilian ERP and CRM for SMB sales and finance.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Omie CRM entities map to Looker Studio

Omie CRM entityLooker Studio objectNotes
clientsomie_clientsid PK · custom fields → flattened columns for chart fields
opportunitiesomie_opportunitiesid PK · linked to omie_clients
sales ordersomie_sales_ordersid PK · linked to omie_clients
invoicesomie_invoicesid PK · linked to omie_clients

FAQ

How does Datrise handle Omie CRM'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 Omie CRM to Looker Studio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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