DatriseAI-first ETL

Pivotal Tracker to GoodData Integration

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

How Datrise loads Pivotal Tracker into GoodData

Datrise syncs Pivotal Tracker's stories, projects, iterations, epics, tasks, and story transitions into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.

Ideal for embedded, multi-tenant analytics.

Endpoints

Pivotal Tracker: Agile story tracking and iteration planning.

GoodData: Composable analytics platform with headless BI and embedded dashboards.

How Pivotal Tracker entities map to GoodData

Pivotal Tracker entityGoodData 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 GoodData?

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 GoodData types.

How does the Pivotal Tracker to GoodData sync stay up to date?

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

Related pipelines

Early access

Connect Pivotal Tracker to GoodData the easy way

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