DatriseAI-first ETL

Aircall to Tableau Integration

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

How Datrise loads Aircall into Tableau

Datrise syncs Aircall's calls, users, teams, phone numbers, tags, and call recordings into Tableau as warehouse tables or a refreshed .hyper extract. Flexible or custom fields land in flattened columns for Tableau fields, and timestamps such as created, updated, and status changes are typed as date/datetime fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind a live connection or extract, so re-runs update only what changed. Date-partitioned facts to keep extract refresh quick. Tableau .hyper extracts snapshot data, so Datrise keeps the source tables incremental and lets you choose live vs extract.

Ideal for visual analytics and dashboards in Tableau.

Endpoints

Aircall: Cloud phone system for sales and support teams.

Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.

How Aircall entities map to Tableau

Aircall entityTableau objectNotes
callsaircall_callsid PK · custom fields → flattened columns for Tableau fields
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 Tableau?

Flexible values are stored as flattened columns for Tableau fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Tableau types.

How does the Aircall to Tableau sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.

Related pipelines

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