DatriseAI-first ETL

Visma e-conomic to Sisense Integration

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

How Datrise loads Visma e-conomic into Sisense

Datrise syncs Visma e-conomic's invoices, customers, suppliers, journal entries, accounts, and products 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

Visma e-conomic: Nordic accounting, invoicing, and ledger records.

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

How Visma e-conomic entities map to Sisense

Visma e-conomic entitySisense objectNotes
invoicesvisma_e_conomic_invoicesid PK · custom fields → flattened columns for the cube
customersvisma_e_conomic_customersid PK · linked to visma_e_conomic_invoices
suppliersvisma_e_conomic_suppliersid PK · linked to visma_e_conomic_invoices
journal entriesvisma_e_conomic_journal_entriesid PK · linked to visma_e_conomic_invoices

FAQ

How does Datrise handle Visma e-conomic'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 Visma e-conomic to Sisense sync stay up to date?

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

Related pipelines

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