DatriseAI-first ETL

Redtail CRM Looker Studio

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

How Datrise loads Redtail CRM into Looker Studio

Datrise syncs Redtail CRM's contacts, accounts, deals, activities, and lifecycle events into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

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

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Redtail CRM entities map to Looker Studio

Redtail CRM entityLooker Studio objectNotes
contactsredtail_contactsid PK · custom fields → flattened columns for chart fields
accountsredtail_accountsid PK · linked to redtail_contacts
dealsredtail_dealsid PK · linked to redtail_contacts
activitiesredtail_activitiesdate dimension columns events

FAQ

How does Datrise handle Redtail CRM's custom fields in Looker Studio?

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

How does the Redtail CRM to Looker Studio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

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