DatriseAI-first ETL

Rocket Chat Yellowfin

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

How Datrise loads Rocket Chat into Yellowfin

Datrise syncs Rocket Chat'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

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

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

How Rocket Chat entities map to Yellowfin

Rocket Chat entityYellowfin objectNotes
recordsrocket_chat_recordsid PK · custom fields → flattened columns
eventsrocket_chat_eventsdate/time dimensions events
configuration objectsrocket_chat_configuration_objectsid PK · linked to rocket_chat_records

FAQ

How does Datrise handle Rocket Chat'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 Rocket Chat 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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