DatriseAI-first ETL

SAP Fieldglass to Mode Integration

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

How Datrise loads SAP Fieldglass into Mode

Datrise syncs SAP Fieldglass's workers, job postings, work orders, time sheets, suppliers, and invoices into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

SAP Fieldglass: External workforce and contingent labor management.

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How SAP Fieldglass entities map to Mode

SAP Fieldglass entityMode objectNotes
workerssap_fieldglass_workersid PK · custom fields → flattened columns for SQL and notebooks
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 Mode?

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

How does the SAP Fieldglass to Mode sync stay up to date?

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

Related pipelines

Early access

Connect SAP Fieldglass to Mode the easy way

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