DatriseAI-first ETL

ServiceTitan Tableau

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

How Datrise loads ServiceTitan into Tableau

Datrise syncs ServiceTitan's contacts, accounts, deals, activities, and lifecycle events 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

ServiceTitan: Field service CRM for scheduling, jobs, and customer history.

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

How ServiceTitan entities map to Tableau

ServiceTitan entityTableau objectNotes
contactsservicetitan_contactsid PK · custom fields → flattened columns for Tableau fields
accountsservicetitan_accountsid PK · linked to servicetitan_contacts
dealsservicetitan_dealsid PK · linked to servicetitan_contacts
activitiesservicetitan_activitiesdate/datetime fields events

FAQ

How does Datrise handle ServiceTitan'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 ServiceTitan 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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