DatriseAI-first ETL

Chartmogul Spotfire

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

How Datrise loads Chartmogul into Spotfire

Datrise syncs Chartmogul's records, events, and configuration objects 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

Chartmogul: SaaS or API data source for analytics and warehouse sync.

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

How Chartmogul entities map to Spotfire

Chartmogul entitySpotfire objectNotes
recordschartmogul_recordsid PK · custom fields → flattened columns for visualizations
eventschartmogul_eventsdate/time columns events
configuration objectschartmogul_configuration_objectsid PK · linked to chartmogul_records

FAQ

How does Datrise handle Chartmogul'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 Chartmogul to Spotfire sync stay up to date?

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

Related pipelines

Early access

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