DatriseAI-first ETL

Salesloft Looker Studio

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

How Datrise loads Salesloft into Looker Studio

Datrise syncs Salesloft's cadence activity, conversation signals, and revenue workflow execution 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

Salesloft: Revenue workflow platform for cadences, conversations, and coaching signals.

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

How Salesloft entities map to Looker Studio

Salesloft entityLooker Studio objectNotes
cadence activitysalesloft_cadence_activitydate dimension columns events
conversation signalssalesloft_conversation_signalsid PK · linked to salesloft_cadence_activity
revenue workflow executionsalesloft_revenue_workflow_executionid PK · linked to salesloft_cadence_activity

FAQ

How does Datrise handle Salesloft'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 Salesloft 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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