DatriseAI-first ETL

Housecall Pro to Domo Integration

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

How Datrise loads Housecall Pro into Domo

Datrise syncs Housecall Pro's jobs, customers, estimates, invoices, technicians, and service schedules into Domo as datasets in Domo's cloud store via connector. Flexible or custom fields land in flattened columns for Magic ETL, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses partitioned dataset updates rather than full replaces, so re-runs update only what changed. Domo dataset partitions keyed on load date. Domo stores its own copy of data, so Datrise sends incremental partitions to avoid re-uploading whole datasets.

Ideal for all-in-one cloud BI with built-in ETL.

Endpoints

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

Domo: Cloud BI platform combining data integration and executive dashboards.

How Housecall Pro entities map to Domo

Housecall Pro entityDomo objectNotes
jobshousecall_pro_jobsid PK · custom fields → flattened columns for Magic ETL
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 Domo?

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

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

It runs incrementally — Datrise uses partitioned dataset updates rather than full replaces.

Related pipelines

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