DatriseAI-first ETL

Salesforce Service Cloud to Domo Integration

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

How Datrise loads Salesforce Service Cloud into Domo

Datrise syncs Salesforce Service Cloud's cases, contacts, accounts, entitlements, milestones, and case comments into Domo as datasets in Domo's cloud store via connector. Flexible or custom fields land in flattened columns for Magic ETL, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses partitioned dataset updates rather than full replaces, so re-runs update only what changed. Domo dataset partitions keyed on load date. Domo stores its own copy of data, so Datrise sends incremental partitions to avoid re-uploading whole datasets.

Ideal for all-in-one cloud BI with built-in ETL.

Endpoints

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

Domo: Cloud BI platform combining data integration and executive dashboards.

How Salesforce Service Cloud entities map to Domo

Salesforce Service Cloud entityDomo objectNotes
casessalesforce_service_cloud_casesid PK · custom fields → flattened columns for Magic ETL
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 Domo?

Flexible values are stored as flattened columns for Magic ETL, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Domo types.

How does the Salesforce Service Cloud to Domo sync stay up to date?

It runs incrementally — Datrise uses partitioned dataset updates rather than full replaces.

Related pipelines

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