Workday RaaS to Google BigQuery Integration
AI-first ETL from Workday RaaS into Google BigQuery. Governed entities, incremental sync, typed landing tables.
How Datrise loads Workday RaaS into Google BigQuery
Datrise syncs Workday RaaS's workers, organizations, job profiles, compensation records, absence records, and report rows into Google BigQuery as a partitioned table per source entity. Flexible or custom fields land in JSON or nested/repeated (STRUCT) columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.
Sync is incremental: Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target, so re-runs update only what changed. Partition by ingestion or event date and cluster by entity id to keep scanned bytes low. BigQuery bills by bytes scanned, so Datrise partitions and clusters every table to keep query costs predictable.
Ideal for Google-stack analytics and ML on serverless infrastructure.
Endpoints
Workday RaaS: Workday HR reports delivered as a service.
Google BigQuery: Serverless analytics warehouse on GCP.
How Workday RaaS entities map to Google BigQuery
| Workday RaaS entity | Google BigQuery object | Notes |
|---|---|---|
| workers | workday_raas_workers | id PK · custom fields → JSON or nested/repeated (STRUCT) columns |
| organizations | workday_raas_organizations | id PK · linked to workday_raas_workers |
| job profiles | workday_raas_job_profiles | id PK · linked to workday_raas_workers |
| compensation records | workday_raas_compensation_records | id PK · linked to workday_raas_workers |
FAQ
How does Datrise handle Workday RaaS's custom fields in Google BigQuery?
Flexible values are stored as JSON or nested/repeated (STRUCT) columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Google BigQuery types.
How does the Workday RaaS to Google BigQuery sync stay up to date?
It runs incrementally — Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target.
Related pipelines
More destinations for Workday RaaS
- Workday RaaS → Amazon Redshift
- Workday RaaS → Databricks SQL Warehouse
- Workday RaaS → ClickHouse
- Workday RaaS → DuckDB
- Workday RaaS → Amazon Athena
- Workday RaaS → Amazon S3 Data Lake
- Workday RaaS → Azure Data Lake Storage
- Workday RaaS → Azure Synapse
- Workday RaaS → Spreadsheets
- Workday RaaS → Airtable
- Workday RaaS → CSV Files
- Workday RaaS → MongoDB
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Early access
Connect Workday RaaS to Google BigQuery the easy way
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