Visma e-conomic to Azure Data Lake Storage Integration
AI-first ETL from Visma e-conomic into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.
How Datrise loads Visma e-conomic into Azure Data Lake Storage
Datrise syncs Visma e-conomic's invoices, customers, suppliers, journal entries, accounts, and products into Azure Data Lake Storage as partitioned Parquet in ADLS Gen2 per source entity. Flexible or custom fields land in nested struct/map fields in Parquet, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.
Sync is incremental: Datrise uses writes new date partitions to the container and compacts on a schedule, so re-runs update only what changed. Hive-style partitioning by load date, readable by Synapse and Databricks. ADLS hierarchical namespace makes folder layout matter, so Datrise keeps a predictable entity/date path your Azure engines mount directly.
Ideal for Azure lakehouse storage shared across Synapse and Databricks.
Endpoints
Visma e-conomic: Nordic accounting, invoicing, and ledger records.
Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.
How Visma e-conomic entities map to Azure Data Lake Storage
| Visma e-conomic entity | Azure Data Lake Storage object | Notes |
|---|---|---|
| invoices | visma_e_conomic_invoices | id PK · custom fields → nested struct/map fields in Parquet |
| customers | visma_e_conomic_customers | id PK · linked to visma_e_conomic_invoices |
| suppliers | visma_e_conomic_suppliers | id PK · linked to visma_e_conomic_invoices |
| journal entries | visma_e_conomic_journal_entries | id PK · linked to visma_e_conomic_invoices |
FAQ
How does Datrise handle Visma e-conomic's custom fields in Azure Data Lake Storage?
Flexible values are stored as nested struct/map fields in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Azure Data Lake Storage types.
How does the Visma e-conomic to Azure Data Lake Storage sync stay up to date?
It runs incrementally — Datrise uses writes new date partitions to the container and compacts on a schedule.
Related pipelines
More destinations for Visma e-conomic
- Visma e-conomic → Azure Synapse
- Visma e-conomic → Spreadsheets
- Visma e-conomic → Airtable
- Visma e-conomic → CSV Files
- Visma e-conomic → MongoDB
- Visma e-conomic → Supabase
- Visma e-conomic → Neon
- Visma e-conomic → PlanetScale
- Visma e-conomic → Amazon DynamoDB
- Visma e-conomic → Looker
- Visma e-conomic → Looker Studio
- Visma e-conomic → Microsoft Power BI
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Early access
Connect Visma e-conomic to Azure Data Lake Storage the easy way
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