DatriseAI-first ETL

Housecall Pro Looker

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

How Datrise loads Housecall Pro into Looker

Datrise syncs Housecall Pro's contacts, accounts, deals, activities, and lifecycle events into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.

Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.

Ideal for governed, version-controlled BI on a warehouse.

Endpoints

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

Looker: Google Cloud BI with LookML semantic models and governed dashboards.

How Housecall Pro entities map to Looker

Housecall Pro entityLooker objectNotes
contactshousecall_pro_contactsid PK · custom fields → flattened columns (nested fields expanded for modeling)
accountshousecall_pro_accountsid PK · linked to housecall_pro_contacts
dealshousecall_pro_dealsid PK · linked to housecall_pro_contacts
activitieshousecall_pro_activitiesdate/time dimension columns events

FAQ

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

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

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

It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.

Related pipelines

Early access

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