DatriseAI-first ETL

Microsoft Dataverse to Spotfire Integration

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

How Datrise loads Microsoft Dataverse into Spotfire

Datrise syncs Microsoft Dataverse's tables, rows, columns, relationships, choice sets, and change tracking 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

Microsoft Dataverse: Business data platform behind Dynamics and Power Apps.

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

How Microsoft Dataverse entities map to Spotfire

Microsoft Dataverse entitySpotfire objectNotes
tablesmicrosoft_dataverse_tablesid PK · custom fields → flattened columns for visualizations
rowsmicrosoft_dataverse_rowsid PK · linked to microsoft_dataverse_tables
columnsmicrosoft_dataverse_columnsid PK · linked to microsoft_dataverse_tables
relationshipsmicrosoft_dataverse_relationshipsid PK · linked to microsoft_dataverse_tables

FAQ

How does Datrise handle Microsoft Dataverse'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 Microsoft Dataverse 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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