DatriseAI-first ETL

Braze to Amazon QuickSight Integration

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

How Datrise loads Braze into Amazon QuickSight

Datrise syncs Braze's users, campaigns, canvases, message events, segments, and custom attributes into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

Braze: Cross-channel customer engagement platform.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How Braze entities map to Amazon QuickSight

Braze entityAmazon QuickSight objectNotes
usersbraze_usersid PK · custom fields → flattened columns for analyses
campaignsbraze_campaignsid PK · linked to braze_users
canvasesbraze_canvasesid PK · linked to braze_users
message eventsbraze_message_eventsdate/time fields events

FAQ

How does Datrise handle Braze's custom fields in Amazon QuickSight?

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

How does the Braze to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

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