DatriseAI-first ETL

Wealthbox Looker

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

How Datrise loads Wealthbox into Looker

Datrise syncs Wealthbox'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

Wealthbox: Financial advisor CRM for clients, households, and compliance workflows.

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

How Wealthbox entities map to Looker

Wealthbox entityLooker objectNotes
contactswealthbox_contactsid PK · custom fields → flattened columns (nested fields expanded for modeling)
accountswealthbox_accountsid PK · linked to wealthbox_contacts
dealswealthbox_dealsid PK · linked to wealthbox_contacts
activitieswealthbox_activitiesdate/time dimension columns events

FAQ

How does Datrise handle Wealthbox'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 Wealthbox 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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