DatriseAI-first ETL

Microsoft Sharepoint Redash

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

How Datrise loads Microsoft Sharepoint into Redash

Datrise syncs Microsoft Sharepoint'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 Sharepoint: SaaS or API data source for analytics and warehouse sync.

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

How Microsoft Sharepoint entities map to Redash

Microsoft Sharepoint entityRedash objectNotes
recordsmicrosoft_sharepoint_recordsid PK · custom fields → flattened columns for query results
eventsmicrosoft_sharepoint_eventstemporal columns events
configuration objectsmicrosoft_sharepoint_configuration_objectsid PK · linked to microsoft_sharepoint_records

FAQ

How does Datrise handle Microsoft Sharepoint'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 Sharepoint to Redash sync stay up to date?

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

Related pipelines

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