DatriseAI-first ETL

Keap Tableau

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

How Datrise loads Keap into Tableau

Datrise syncs Keap's SMB contacts, opportunities, automations, and appointment workflows 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

Keap: SMB CRM with pipeline automation, email, and appointment flows.

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

How Keap entities map to Tableau

Keap entityTableau objectNotes
SMB contactskeap_smb_contactsid PK · custom fields → flattened columns for Tableau fields
opportunitieskeap_opportunitiesid PK · linked to keap_smb_contacts
automationskeap_automationsid PK · linked to keap_smb_contacts
appointment workflowskeap_appointment_workflowsid PK · linked to keap_smb_contacts

FAQ

How does Datrise handle Keap'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 Keap 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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