Sellsy to Birst Integration
AI-first ETL from Sellsy into Birst. Governed entities, incremental sync, typed landing tables.
How Datrise loads Sellsy into Birst
Datrise syncs Sellsy's prospects, opportunities, estimates, invoices, tickets, and timeline events into Birst as warehouse tables for Birst's automated star schema. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the source tables Birst ingests, so re-runs update only what changed. Date-partitioned facts. Birst builds its own semantic layer, so Datrise lands conformed, well-keyed tables it can automate against.
Ideal for networked, governed enterprise BI.
Endpoints
Sellsy: French CRM with quoting, invoicing, and support tickets.
Birst: Cloud BI with networked analytics and enterprise semantic layers.
How Sellsy entities map to Birst
| Sellsy entity | Birst object | Notes |
|---|---|---|
| prospects | sellsy_prospects | id PK · custom fields → flattened columns |
| opportunities | sellsy_opportunities | id PK · linked to sellsy_prospects |
| estimates | sellsy_estimates | id PK · linked to sellsy_prospects |
| invoices | sellsy_invoices | id PK · linked to sellsy_prospects |
FAQ
How does Datrise handle Sellsy's custom fields in Birst?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Birst types.
How does the Sellsy to Birst sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.
Related pipelines
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