DatriseAI-first ETL

Pivotal Tracker to Yellowfin Integration

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

How Datrise loads Pivotal Tracker into Yellowfin

Datrise syncs Pivotal Tracker's stories, projects, iterations, epics, tasks, and story transitions 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

Pivotal Tracker: Agile story tracking and iteration planning.

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

How Pivotal Tracker entities map to Yellowfin

Pivotal Tracker entityYellowfin objectNotes
storiespivotal_tracker_storiesid PK · custom fields → flattened columns
projectspivotal_tracker_projectsid PK · linked to pivotal_tracker_stories
iterationspivotal_tracker_iterationsid PK · linked to pivotal_tracker_stories
epicspivotal_tracker_epicsid PK · linked to pivotal_tracker_stories

FAQ

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

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

Related pipelines

Early access

Connect Pivotal Tracker to Yellowfin the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.