DatriseAI-first ETL

Onesignal to Spotfire Integration

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

How Datrise loads Onesignal into Spotfire

Datrise syncs Onesignal's notifications, subscribers, segments, apps, delivery events, and outcomes 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

Onesignal: Push, in-app, and email message delivery.

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

How Onesignal entities map to Spotfire

Onesignal entitySpotfire objectNotes
notificationsonesignal_notificationsid PK · custom fields → flattened columns for visualizations
subscribersonesignal_subscribersid PK · linked to onesignal_notifications
segmentsonesignal_segmentsid PK · linked to onesignal_notifications
appsonesignal_appsid PK · linked to onesignal_notifications

FAQ

How does Datrise handle Onesignal'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 Onesignal 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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