DatriseAI-first ETL

Microsoft Dataverse to Tableau Integration

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

How Datrise loads Microsoft Dataverse into Tableau

Datrise syncs Microsoft Dataverse's tables, rows, columns, relationships, choice sets, and change tracking into Tableau as warehouse tables or a refreshed .hyper extract. Flexible or custom fields land in flattened columns for Tableau fields, and timestamps such as created, updated, and status changes are typed as date/datetime fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind a live connection or extract, so re-runs update only what changed. Date-partitioned facts to keep extract refresh quick. Tableau .hyper extracts snapshot data, so Datrise keeps the source tables incremental and lets you choose live vs extract.

Ideal for visual analytics and dashboards in Tableau.

Endpoints

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

Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.

How Microsoft Dataverse entities map to Tableau

Microsoft Dataverse entityTableau objectNotes
tablesmicrosoft_dataverse_tablesid PK · custom fields → flattened columns for Tableau fields
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 Tableau?

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

How does the Microsoft Dataverse to Tableau sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.

Related pipelines

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