DatriseAI-first ETL

Sap Fieldglass Tableau

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

How Datrise loads Sap Fieldglass into Tableau

Datrise syncs Sap Fieldglass's records, events, and configuration objects into Tableau as warehouse tables or a refreshed .hyper extract. Flexible or custom fields land in flattened columns for Tableau fields, and timestamps such as created, updated, and status changes are typed as date/datetime fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind a live connection or extract, so re-runs update only what changed. Date-partitioned facts to keep extract refresh quick. Tableau .hyper extracts snapshot data, so Datrise keeps the source tables incremental and lets you choose live vs extract.

Ideal for visual analytics and dashboards in Tableau.

Endpoints

Sap Fieldglass: SaaS or API data source for analytics and warehouse sync.

Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.

How Sap Fieldglass entities map to Tableau

Sap Fieldglass entityTableau objectNotes
recordssap_fieldglass_recordsid PK · custom fields → flattened columns for Tableau fields
eventssap_fieldglass_eventsdate/datetime fields events
configuration objectssap_fieldglass_configuration_objectsid PK · linked to sap_fieldglass_records

FAQ

How does Datrise handle Sap Fieldglass's custom fields in Tableau?

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

How does the Sap Fieldglass to Tableau sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.

Related pipelines

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