DatriseAI-first ETL

Microsoft Dataverse to Mode Integration

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

How Datrise loads Microsoft Dataverse into Mode

Datrise syncs Microsoft Dataverse's tables, rows, columns, relationships, choice sets, and change tracking into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

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

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Microsoft Dataverse entities map to Mode

Microsoft Dataverse entityMode objectNotes
tablesmicrosoft_dataverse_tablesid PK · custom fields → flattened columns for SQL and notebooks
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 Mode?

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

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

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

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