DatriseAI-first ETL

Front to Tableau Integration

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

How Datrise loads Front into Tableau

Datrise syncs Front's conversations, messages, contacts, inboxes, tags, and teammates 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

Front: Shared inbox for team email and messaging.

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

How Front entities map to Tableau

Front entityTableau objectNotes
conversationsfrontapp_conversationsid PK · custom fields → flattened columns for Tableau fields
messagesfrontapp_messagesid PK · linked to frontapp_conversations
contactsfrontapp_contactsid PK · linked to frontapp_conversations
inboxesfrontapp_inboxesid PK · linked to frontapp_conversations

FAQ

How does Datrise handle Front'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 Front 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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