DatriseAI-first ETL

Microsoft Dataverse Redash

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

How Datrise loads Microsoft Dataverse into Redash

Datrise syncs Microsoft Dataverse's records, events, and configuration objects into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

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

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Microsoft Dataverse entities map to Redash

Microsoft Dataverse entityRedash objectNotes
recordsmicrosoft_dataverse_recordsid PK · custom fields → flattened columns for query results
eventsmicrosoft_dataverse_eventstemporal columns events
configuration objectsmicrosoft_dataverse_configuration_objectsid PK · linked to microsoft_dataverse_records

FAQ

How does Datrise handle Microsoft Dataverse's custom fields in Redash?

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

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

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

Related pipelines

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