DatriseAI-first ETL

Github Webhook Yellowfin

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

How Datrise loads Github Webhook into Yellowfin

Datrise syncs Github Webhook'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

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

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

How Github Webhook entities map to Yellowfin

Github Webhook entityYellowfin objectNotes
recordsgithub_webhook_recordsid PK · custom fields → flattened columns
eventsgithub_webhook_eventsdate/time dimensions events
configuration objectsgithub_webhook_configuration_objectsid PK · linked to github_webhook_records

FAQ

How does Datrise handle Github Webhook'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 Github Webhook to Yellowfin sync stay up to date?

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

Related pipelines

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