DatriseAI-first ETL

Glassfrog Yellowfin

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

How Datrise loads Glassfrog into Yellowfin

Datrise syncs Glassfrog'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

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

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

How Glassfrog entities map to Yellowfin

Glassfrog entityYellowfin objectNotes
recordsglassfrog_recordsid PK · custom fields → flattened columns
eventsglassfrog_eventsdate/time dimensions events
configuration objectsglassfrog_configuration_objectsid PK · linked to glassfrog_records

FAQ

How does Datrise handle Glassfrog'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 Glassfrog 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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