DatriseAI-first ETL

Mailerlite Yellowfin

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

How Datrise loads Mailerlite into Yellowfin

Datrise syncs Mailerlite's records, events, and configuration objects 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

Mailerlite: SaaS or API data source for analytics and warehouse sync.

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

How Mailerlite entities map to Yellowfin

Mailerlite entityYellowfin objectNotes
recordsmailerlite_recordsid PK · custom fields → flattened columns
eventsmailerlite_eventsdate/time dimensions events
configuration objectsmailerlite_configuration_objectsid PK · linked to mailerlite_records

FAQ

How does Datrise handle Mailerlite'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 Mailerlite 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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