DatriseAI-first ETL

SAP Looker Studio

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

How Datrise loads SAP into Looker Studio

Datrise syncs SAP's finance, procurement, operations, and master-data entities into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

SAP: ERP source for finance, operations, and procurement entities.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How SAP entities map to Looker Studio

SAP entityLooker Studio objectNotes
financesap_financeid PK · custom fields → flattened columns for chart fields
procurementsap_procurementid PK · linked to sap_finance
operationssap_operationsid PK · linked to sap_finance
master-data entitiessap_master_data_entitiesid PK · linked to sap_finance

FAQ

How does Datrise handle SAP's custom fields in Looker Studio?

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

How does the SAP to Looker Studio sync stay up to date?

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

Related pipelines

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