DatriseAI-first ETL

Housecall Pro to Spotfire Integration

AI-first ETL from Housecall Pro into Spotfire. Governed entities, incremental sync, typed landing tables.

How Datrise loads Housecall Pro into Spotfire

Datrise syncs Housecall Pro's jobs, customers, estimates, invoices, technicians, and service schedules into Spotfire as warehouse tables or in-memory data for Spotfire analyses. Flexible or custom fields land in flattened columns for visualizations, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables or in-memory data, so re-runs update only what changed. Date-partitioned facts. Spotfire can load data in-memory, so Datrise keeps the backing tables incremental so analyses refresh without full reloads.

Ideal for interactive analytical visualization and data science.

Endpoints

Housecall Pro: Home service scheduling, dispatch, and invoicing.

Spotfire: Visual analytics platform for interactive dashboards and data science workflows.

How Housecall Pro entities map to Spotfire

Housecall Pro entitySpotfire objectNotes
jobshousecall_pro_jobsid PK · custom fields → flattened columns for visualizations
customershousecall_pro_customersid PK · linked to housecall_pro_jobs
estimateshousecall_pro_estimatesid PK · linked to housecall_pro_jobs
invoiceshousecall_pro_invoicesid PK · linked to housecall_pro_jobs

FAQ

How does Datrise handle Housecall Pro's custom fields in Spotfire?

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

How does the Housecall Pro to Spotfire sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.

Related pipelines

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