DatriseAI-first ETL

Microsoft Azure Birst

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

How Datrise loads Microsoft Azure into Birst

Datrise syncs Microsoft Azure's records, events, and configuration objects into Birst as warehouse tables for Birst's automated star schema. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the source tables Birst ingests, so re-runs update only what changed. Date-partitioned facts. Birst builds its own semantic layer, so Datrise lands conformed, well-keyed tables it can automate against.

Ideal for networked, governed enterprise BI.

Endpoints

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

Birst: Cloud BI with networked analytics and enterprise semantic layers.

How Microsoft Azure entities map to Birst

Microsoft Azure entityBirst objectNotes
recordsmicrosoft_azure_recordsid PK · custom fields → flattened columns
eventsmicrosoft_azure_eventsdate/time dimensions events
configuration objectsmicrosoft_azure_configuration_objectsid PK · linked to microsoft_azure_records

FAQ

How does Datrise handle Microsoft Azure's custom fields in Birst?

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

How does the Microsoft Azure to Birst sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.

Related pipelines

Early access

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