DatriseAI-first ETL

SAP Fieldglass to Azure Synapse Integration

AI-first ETL from SAP Fieldglass into Azure Synapse. Governed entities, incremental sync, typed landing tables.

How Datrise loads SAP Fieldglass into Azure Synapse

Datrise syncs SAP Fieldglass's workers, job postings, work orders, time sheets, suppliers, and invoices into Azure Synapse as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses COPY into staging, then a MERGE on stable id, so re-runs update only what changed. Hash distribution on the join id with date partitioning on facts. Synapse dedicated pools reward good hash-distribution choices, so Datrise distributes on entity ids to avoid data-movement-heavy joins.

Ideal for Azure analytics estates feeding Power BI.

Endpoints

SAP Fieldglass: External workforce and contingent labor management.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How SAP Fieldglass entities map to Azure Synapse

SAP Fieldglass entityAzure Synapse objectNotes
workerssap_fieldglass_workersid PK · custom fields → NVARCHAR(MAX) JSON columns
job postingssap_fieldglass_job_postingsid PK · linked to sap_fieldglass_workers
work orderssap_fieldglass_work_ordersid PK · linked to sap_fieldglass_workers
time sheetssap_fieldglass_time_sheetsid PK · linked to sap_fieldglass_workers

FAQ

How does Datrise handle SAP Fieldglass's custom fields in Azure Synapse?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Azure Synapse types.

How does the SAP Fieldglass to Azure Synapse sync stay up to date?

It runs incrementally — Datrise uses COPY into staging, then a MERGE on stable id.

Related pipelines

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