DatriseAI-first ETL

Salesforce Service Cloud to Looker Integration

AI-first ETL from Salesforce Service Cloud into Looker. Governed entities, incremental sync, typed landing tables.

How Datrise loads Salesforce Service Cloud into Looker

Datrise syncs Salesforce Service Cloud's cases, contacts, accounts, entitlements, milestones, and case comments 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

Salesforce Service Cloud: Salesforce case management for support and field service.

Looker: Google Cloud BI with LookML semantic models and governed dashboards.

How Salesforce Service Cloud entities map to Looker

Salesforce Service Cloud entityLooker objectNotes
casessalesforce_service_cloud_casesid PK · custom fields → flattened columns (nested fields expanded for modeling)
contactssalesforce_service_cloud_contactsid PK · linked to salesforce_service_cloud_cases
accountssalesforce_service_cloud_accountsid PK · linked to salesforce_service_cloud_cases
entitlementssalesforce_service_cloud_entitlementsid PK · linked to salesforce_service_cloud_cases

FAQ

How does Datrise handle Salesforce Service Cloud'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 Salesforce Service Cloud 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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