DatriseAI-first ETL

Lofty Looker Studio

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

How Datrise loads Lofty into Looker Studio

Datrise syncs Lofty'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

Lofty: Real estate CRM for leads, listings, and agent follow-up.

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

How Lofty entities map to Looker Studio

Lofty entityLooker Studio objectNotes
contactslofty_contactsid PK · custom fields → flattened columns for chart fields
accountslofty_accountsid PK · linked to lofty_contacts
dealslofty_dealsid PK · linked to lofty_contacts
activitieslofty_activitiesdate dimension columns events

FAQ

How does Datrise handle Lofty'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 Lofty to Looker Studio sync stay up to date?

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

Related pipelines

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