DatriseAI-first ETL

Braze to Birst Integration

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

How Datrise loads Braze into Birst

Datrise syncs Braze's users, campaigns, canvases, message events, segments, and custom attributes 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

Braze: Cross-channel customer engagement platform.

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

How Braze entities map to Birst

Braze entityBirst objectNotes
usersbraze_usersid PK · custom fields → flattened columns
campaignsbraze_campaignsid PK · linked to braze_users
canvasesbraze_canvasesid PK · linked to braze_users
message eventsbraze_message_eventsdate/time dimensions events

FAQ

How does Datrise handle Braze'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 Braze to Birst sync stay up to date?

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

Related pipelines

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