Real Geeks → Looker
AI-first ETL from Real Geeks into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads Real Geeks into Looker
Datrise syncs Real Geeks'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
Real Geeks: Real estate CRM for leads, listings, and agent follow-up.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How Real Geeks entities map to Looker
| Real Geeks entity | Looker object | Notes |
|---|---|---|
| contacts | real_geeks_contacts | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| accounts | real_geeks_accounts | id PK · linked to real_geeks_contacts |
| deals | real_geeks_deals | id PK · linked to real_geeks_contacts |
| activities | real_geeks_activities | date/time dimension columns events |
FAQ
How does Datrise handle Real Geeks'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 Real Geeks 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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