DatriseAI-first ETL

Salesforce Commerce Cloud to Spotfire Integration

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

How Datrise loads Salesforce Commerce Cloud into Spotfire

Datrise syncs Salesforce Commerce Cloud's orders, products, customers, baskets, promotions, and inventory records 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 Commerce Cloud: Salesforce storefront, catalog, and order management.

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

How Salesforce Commerce Cloud entities map to Spotfire

Salesforce Commerce Cloud entitySpotfire objectNotes
orderssalesforce_commerce_cloud_ordersid PK · custom fields → flattened columns for visualizations
productssalesforce_commerce_cloud_productsid PK · linked to salesforce_commerce_cloud_orders
customerssalesforce_commerce_cloud_customersid PK · linked to salesforce_commerce_cloud_orders
basketssalesforce_commerce_cloud_basketsid PK · linked to salesforce_commerce_cloud_orders

FAQ

How does Datrise handle Salesforce Commerce Cloud'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 Commerce Cloud 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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