Vero to Yellowfin Integration
AI-first ETL from Vero into Yellowfin. Governed entities, incremental sync, typed landing tables.
How Datrise loads Vero into Yellowfin
Datrise syncs Vero's users, events, campaigns, message events, segments, and user properties 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
Vero: Behavioral email and push messaging.
Yellowfin: BI suite with dashboards, automated insights, and data storytelling.
How Vero entities map to Yellowfin
| Vero entity | Yellowfin object | Notes |
|---|---|---|
| users | vero_users | id PK · custom fields → flattened columns |
| events | vero_events | date/time dimensions events |
| campaigns | vero_campaigns | id PK · linked to vero_users |
| message events | vero_message_events | date/time dimensions events |
FAQ
How does Datrise handle Vero'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 Vero to Yellowfin sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Vero
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