DatriseAI-first ETL

ServiceTitan to Amazon QuickSight Integration

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

How Datrise loads ServiceTitan into Amazon QuickSight

Datrise syncs ServiceTitan's jobs, customers, estimates, invoices, technicians, and service agreements into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

ServiceTitan: Trades platform for dispatch, jobs, and revenue reporting.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How ServiceTitan entities map to Amazon QuickSight

ServiceTitan entityAmazon QuickSight objectNotes
jobsservicetitan_jobsid PK · custom fields → flattened columns for analyses
customersservicetitan_customersid PK · linked to servicetitan_jobs
estimatesservicetitan_estimatesid PK · linked to servicetitan_jobs
invoicesservicetitan_invoicesid PK · linked to servicetitan_jobs

FAQ

How does Datrise handle ServiceTitan's custom fields in Amazon QuickSight?

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

How does the ServiceTitan to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

Early access

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