HighLevel → Looker
AI-first ETL from HighLevel into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads HighLevel into Looker
Datrise syncs HighLevel's agency CRM records, funnels, opportunities, and messaging workflows 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
HighLevel: Agency-focused CRM for leads, funnels, and customer messaging.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How HighLevel entities map to Looker
| HighLevel entity | Looker object | Notes |
|---|---|---|
| agency CRM records | highlevel_agency_crm_records | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| funnels | highlevel_funnels | id PK · linked to highlevel_agency_crm_records |
| opportunities | highlevel_opportunities | id PK · linked to highlevel_agency_crm_records |
| messaging workflows | highlevel_messaging_workflows | id PK · linked to highlevel_agency_crm_records |
FAQ
How does Datrise handle HighLevel'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 HighLevel to Looker sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.
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