DatriseAI-first ETL

Workday Databricks SQL Warehouse

AI-first ETL from Workday into Databricks SQL Warehouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Workday into Databricks SQL Warehouse

Datrise syncs Workday's HR, finance entities, organizational structures, and operational events into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

Workday: Enterprise HR and finance source for operational reporting.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How Workday entities map to Databricks SQL Warehouse

Workday entityDatabricks SQL Warehouse objectNotes
HRworkday_hrid PK · custom fields → VARIANT or STRUCT columns
finance entitiesworkday_finance_entitiesid PK · linked to workday_hr
organizational structuresworkday_organizational_structuresid PK · linked to workday_hr
operational eventsworkday_operational_eventsTIMESTAMP events

FAQ

How does Datrise handle Workday's custom fields in Databricks SQL Warehouse?

Flexible values are stored as VARIANT or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Databricks SQL Warehouse types.

How does the Workday to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

Related pipelines

Early access

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