DatriseAI-first ETL

Aircall to Birst Integration

AI-first ETL from Aircall into Birst. Governed entities, incremental sync, typed landing tables.

How Datrise loads Aircall into Birst

Datrise syncs Aircall's calls, users, teams, phone numbers, tags, and call recordings 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

Aircall: Cloud phone system for sales and support teams.

Birst: Cloud BI with networked analytics and enterprise semantic layers.

How Aircall entities map to Birst

Aircall entityBirst objectNotes
callsaircall_callsid PK · custom fields → flattened columns
usersaircall_usersid PK · linked to aircall_calls
teamsaircall_teamsid PK · linked to aircall_calls
phone numbersaircall_phone_numbersid PK · linked to aircall_calls

FAQ

How does Datrise handle Aircall'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 Aircall 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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