DatriseAI-first ETL

Pivotal Tracker Holistics

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

How Datrise loads Pivotal Tracker into Holistics

Datrise syncs Pivotal Tracker's records, events, and configuration objects into Holistics as warehouse tables modeled in Holistics. Flexible or custom fields land in flattened columns for the modeling layer, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the modeled tables, so re-runs update only what changed. Date-partitioned facts for fast aggregates. Holistics models data as code on top of SQL, so Datrise lands stable column names to keep your models from drifting.

Ideal for as-code BI modeling on a warehouse.

Endpoints

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

Holistics: Self-service BI with modeling layers and scheduled report delivery.

How Pivotal Tracker entities map to Holistics

Pivotal Tracker entityHolistics objectNotes
recordspivotal_tracker_recordsid PK · custom fields → flattened columns for the modeling layer
eventspivotal_tracker_eventsdate/time dimensions events
configuration objectspivotal_tracker_configuration_objectsid PK · linked to pivotal_tracker_records

FAQ

How does Datrise handle Pivotal Tracker's custom fields in Holistics?

Flexible values are stored as flattened columns for the modeling layer, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Holistics types.

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

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

Related pipelines

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