DatriseAI-first ETL

Customer.io to Yellowfin Integration

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

How Datrise loads Customer.io into Yellowfin

Datrise syncs Customer.io's people, segments, campaigns, message events, attributes, and broadcasts 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

Customer.io: Behavioral messaging across email, push, and SMS.

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

How Customer.io entities map to Yellowfin

Customer.io entityYellowfin objectNotes
peoplecustomerio_peopleid PK · custom fields → flattened columns
segmentscustomerio_segmentsid PK · linked to customerio_people
campaignscustomerio_campaignsid PK · linked to customerio_people
message eventscustomerio_message_eventsdate/time dimensions events

FAQ

How does Datrise handle Customer.io'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 Customer.io 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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