DatriseAI-first ETL

Visma E Conomic Microsoft SQL Server

AI-first ETL from Visma E Conomic into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.

How Datrise loads Visma E Conomic into Microsoft SQL Server

Datrise syncs Visma E Conomic's records, events, and configuration objects into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

Visma E Conomic: SaaS or API data source for analytics and warehouse sync.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Visma E Conomic entities map to Microsoft SQL Server

Visma E Conomic entityMicrosoft SQL Server objectNotes
recordsvisma_e_conomic_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
eventsvisma_e_conomic_eventsdatetime2 events
configuration objectsvisma_e_conomic_configuration_objectsid PK · linked to visma_e_conomic_records

FAQ

How does Datrise handle Visma E Conomic's custom fields in Microsoft SQL Server?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.

How does the Visma E Conomic to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

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