DatriseAI-first ETL

SAP Fieldglass to Amazon QuickSight Integration

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

How Datrise loads SAP Fieldglass into Amazon QuickSight

Datrise syncs SAP Fieldglass's workers, job postings, work orders, time sheets, suppliers, and invoices into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

SAP Fieldglass: External workforce and contingent labor management.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How SAP Fieldglass entities map to Amazon QuickSight

SAP Fieldglass entityAmazon QuickSight objectNotes
workerssap_fieldglass_workersid PK · custom fields → flattened columns for analyses
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 Amazon QuickSight?

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

How does the SAP Fieldglass to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

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