DatriseAI-first ETL

Housecall Pro to Mode Integration

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

How Datrise loads Housecall Pro into Mode

Datrise syncs Housecall Pro's jobs, customers, estimates, invoices, technicians, and service schedules into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.

Ideal for SQL-first analysis with Python and R notebooks.

Endpoints

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

Mode: Collaborative analytics workspace for SQL, Python, and shared reports.

How Housecall Pro entities map to Mode

Housecall Pro entityMode objectNotes
jobshousecall_pro_jobsid PK · custom fields → flattened columns for SQL and notebooks
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 Mode?

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

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

It runs incrementally — Datrise uses incremental refresh of the queried tables.

Related pipelines

Early access

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