DatriseAI-first ETL

Salesloft Tableau

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

How Datrise loads Salesloft into Tableau

Datrise syncs Salesloft's cadence activity, conversation signals, and revenue workflow execution into Tableau as warehouse tables or a refreshed .hyper extract. Flexible or custom fields land in flattened columns for Tableau fields, and timestamps such as created, updated, and status changes are typed as date/datetime fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind a live connection or extract, so re-runs update only what changed. Date-partitioned facts to keep extract refresh quick. Tableau .hyper extracts snapshot data, so Datrise keeps the source tables incremental and lets you choose live vs extract.

Ideal for visual analytics and dashboards in Tableau.

Endpoints

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

Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.

How Salesloft entities map to Tableau

Salesloft entityTableau objectNotes
cadence activitysalesloft_cadence_activitydate/datetime fields 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 Tableau?

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

How does the Salesloft to Tableau sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.

Related pipelines

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