DatriseAI-first ETL

Bullhorn GoodData

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

How Datrise loads Bullhorn into GoodData

Datrise syncs Bullhorn's contacts, accounts, deals, activities, and lifecycle events 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

Bullhorn: Recruiting CRM/ATS for candidates, pipelines, and placements.

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

How Bullhorn entities map to GoodData

Bullhorn entityGoodData objectNotes
contactsbullhorn_contactsid PK · custom fields → flattened columns
accountsbullhorn_accountsid PK · linked to bullhorn_contacts
dealsbullhorn_dealsid PK · linked to bullhorn_contacts
activitiesbullhorn_activitiesdate dimensions events

FAQ

How does Datrise handle Bullhorn'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 Bullhorn to GoodData sync stay up to date?

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

Related pipelines

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