DatriseAI-first ETL

1С:CRM Looker Studio

AI-first ETL from 1С:CRM into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads 1С:CRM into Looker Studio

Datrise syncs 1С:CRM's contacts, accounts, deals, activities, and lifecycle 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

1С:CRM: CRM with strong adoption in CIS markets for sales and operations.

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

How 1С:CRM entities map to Looker Studio

1С:CRM entityLooker Studio objectNotes
contacts1c_crm_contactsid PK · custom fields → flattened columns for chart fields
accounts1c_crm_accountsid PK · linked to 1c_crm_contacts
deals1c_crm_dealsid PK · linked to 1c_crm_contacts
activities1c_crm_activitiesdate dimension columns events

FAQ

How does Datrise handle 1С: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 1С: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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