DatriseAI-first ETL

Salesforce Spotfire

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

How Datrise loads Salesforce into Spotfire

Datrise syncs Salesforce's accounts, opportunities, contacts, tasks, and pipeline stage history into Spotfire as warehouse tables or in-memory data for Spotfire analyses. Flexible or custom fields land in flattened columns for visualizations, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables or in-memory data, so re-runs update only what changed. Date-partitioned facts. Spotfire can load data in-memory, so Datrise keeps the backing tables incremental so analyses refresh without full reloads.

Ideal for interactive analytical visualization and data science.

Endpoints

Salesforce: Enterprise CRM and Customer 360 platform.

Spotfire: Visual analytics platform for interactive dashboards and data science workflows.

How Salesforce entities map to Spotfire

Salesforce entitySpotfire objectNotes
accountssalesforce_accountsid PK · custom fields → flattened columns for visualizations
opportunitiessalesforce_opportunitiesid PK · linked to salesforce_accounts
contactssalesforce_contactsid PK · linked to salesforce_accounts
taskssalesforce_tasksid PK · linked to salesforce_accounts

FAQ

How does Datrise handle Salesforce's custom fields in Spotfire?

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

How does the Salesforce to Spotfire sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.

Related pipelines

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