DatriseAI-first ETL

Zendesk Support to Looker Studio Integration

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

How Datrise loads Zendesk Support into Looker Studio

Datrise syncs Zendesk Support's tickets, users, organizations, macros, satisfaction ratings, and ticket comments 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

Zendesk Support: Customer support ticketing and agent workflows.

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

How Zendesk Support entities map to Looker Studio

Zendesk Support entityLooker Studio objectNotes
ticketszendesk_support_ticketsid PK · custom fields → flattened columns for chart fields
userszendesk_support_usersid PK · linked to zendesk_support_tickets
organizationszendesk_support_organizationsid PK · linked to zendesk_support_tickets
macroszendesk_support_macrosid PK · linked to zendesk_support_tickets

FAQ

How does Datrise handle Zendesk Support'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 Zendesk Support 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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