DatriseAI-first ETL

Microsoft Dataverse to ThoughtSpot Integration

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

How Datrise loads Microsoft Dataverse into ThoughtSpot

Datrise syncs Microsoft Dataverse's tables, rows, columns, relationships, choice sets, and change tracking into ThoughtSpot as warehouse tables ThoughtSpot indexes for search. Flexible or custom fields land in flattened columns for searchable fields, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the indexed tables, so re-runs update only what changed. Date-partitioned facts for live-query performance. ThoughtSpot search relies on clear names and relationships, so Datrise lands well-named, joinable tables.

Ideal for natural-language search analytics over a warehouse.

Endpoints

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

ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.

How Microsoft Dataverse entities map to ThoughtSpot

Microsoft Dataverse entityThoughtSpot objectNotes
tablesmicrosoft_dataverse_tablesid PK · custom fields → flattened columns for searchable 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 ThoughtSpot?

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

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

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

Related pipelines

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