DatriseAI-first ETL

FullStory Yellowfin

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

How Datrise loads FullStory into Yellowfin

Datrise syncs FullStory's sessions, events, funnels, frustration signals, and user properties 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

FullStory: Digital experience analytics with session replay context.

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

How FullStory entities map to Yellowfin

FullStory entityYellowfin objectNotes
sessionsfullstory_sessionsid PK · custom fields → flattened columns
eventsfullstory_eventsdate/time dimensions events
funnelsfullstory_funnelsid PK · linked to fullstory_sessions
frustration signalsfullstory_frustration_signalsid PK · linked to fullstory_sessions

FAQ

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

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

Related pipelines

Early access

Connect FullStory to Yellowfin the easy way

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