DatriseAI-first ETL

Braze to Yellowfin Integration

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

How Datrise loads Braze into Yellowfin

Datrise syncs Braze's users, campaigns, canvases, message events, segments, and custom attributes into Yellowfin as warehouse tables Yellowfin builds views on. 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 connected tables, so re-runs update only what changed. Date-partitioned facts. Yellowfin views reference columns by name, so Datrise lands stable, well-typed columns to keep reports valid.

Ideal for dashboards with automated data storytelling.

Endpoints

Braze: Cross-channel customer engagement platform.

Yellowfin: BI suite with dashboards, automated insights, and data storytelling.

How Braze entities map to Yellowfin

Braze entityYellowfin 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 Yellowfin?

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 Yellowfin types.

How does the Braze to Yellowfin sync stay up to date?

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

Related pipelines

Early access

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