DatriseAI-first ETL

SAP Sisense

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

How Datrise loads SAP into Sisense

Datrise syncs SAP's finance, procurement, operations, and master-data entities into Sisense as modeled tables for a Sisense ElastiCube (or live connection). Flexible or custom fields land in flattened columns for the cube, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental ElastiCube builds on changed rows, so re-runs update only what changed. Date-partitioned facts to speed cube builds. ElastiCube is an in-memory model, so Datrise lands incremental, build-friendly tables rather than forcing full rebuilds.

Ideal for embedded analytics on an in-memory engine.

Endpoints

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

Sisense: Analytics platform with elastic data models and embedded analytics.

How SAP entities map to Sisense

SAP entitySisense objectNotes
financesap_financeid PK · custom fields → flattened columns for the cube
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 Sisense?

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

How does the SAP to Sisense sync stay up to date?

It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.

Related pipelines

Early access

Connect SAP to Sisense the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.