DatriseAI-first ETL

Whisky Hunter Yellowfin

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

How Datrise loads Whisky Hunter into Yellowfin

Datrise syncs Whisky Hunter'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

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

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

How Whisky Hunter entities map to Yellowfin

Whisky Hunter entityYellowfin objectNotes
recordswhisky_hunter_recordsid PK · custom fields → flattened columns
eventswhisky_hunter_eventsdate/time dimensions events
configuration objectswhisky_hunter_configuration_objectsid PK · linked to whisky_hunter_records

FAQ

How does Datrise handle Whisky Hunter'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 Whisky Hunter to Yellowfin sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

Connect Whisky Hunter to Yellowfin the easy way

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