DatriseAI-first ETL

Front to Looker Studio Integration

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

How Datrise loads Front into Looker Studio

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

Front: Shared inbox for team email and messaging.

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

How Front entities map to Looker Studio

Front entityLooker Studio objectNotes
conversationsfrontapp_conversationsid PK · custom fields → flattened columns for chart 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 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 Front 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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