DatriseAI-first ETL

Follow Up Boss Looker

AI-first ETL from Follow Up Boss into Looker. Governed entities, incremental sync, typed landing tables.

How Datrise loads Follow Up Boss into Looker

Datrise syncs Follow Up Boss'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

Follow Up Boss: Real estate CRM for leads, listings, and agent follow-up.

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

How Follow Up Boss entities map to Looker

Follow Up Boss entityLooker objectNotes
contactsfollow_up_boss_contactsid PK · custom fields → flattened columns (nested fields expanded for modeling)
accountsfollow_up_boss_accountsid PK · linked to follow_up_boss_contacts
dealsfollow_up_boss_dealsid PK · linked to follow_up_boss_contacts
activitiesfollow_up_boss_activitiesdate/time dimension columns events

FAQ

How does Datrise handle Follow Up Boss'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 Follow Up Boss 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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