Braze to Looker Studio Integration
AI-first ETL from Braze into Looker Studio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Braze into Looker Studio
Datrise syncs Braze's users, campaigns, canvases, message events, segments, and custom attributes into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.
Ideal for free, shareable dashboards on Google data sources.
Endpoints
Braze: Cross-channel customer engagement platform.
Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).
How Braze entities map to Looker Studio
| Braze entity | Looker Studio object | Notes |
|---|---|---|
| users | braze_users | id PK · custom fields → flattened columns for chart fields |
| campaigns | braze_campaigns | id PK · linked to braze_users |
| canvases | braze_canvases | id PK · linked to braze_users |
| message events | braze_message_events | date dimension columns events |
FAQ
How does Datrise handle Braze's custom fields in Looker Studio?
Flexible values are stored as flattened columns for chart fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker Studio types.
How does the Braze to Looker Studio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Braze
More sources for Looker Studio
Early access
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