Zendesk Talk to Looker Studio Integration
AI-first ETL from Zendesk Talk into Looker Studio. Governed entities, incremental sync, typed landing tables.
How Datrise loads Zendesk Talk into Looker Studio
Datrise syncs Zendesk Talk's calls, agents, queues, call legs, recordings, and call metrics 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 Talk: Voice support calls and queue performance.
Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).
How Zendesk Talk entities map to Looker Studio
| Zendesk Talk entity | Looker Studio object | Notes |
|---|---|---|
| calls | zendesk_talk_calls | id PK · custom fields → flattened columns for chart fields |
| agents | zendesk_talk_agents | id PK · linked to zendesk_talk_calls |
| queues | zendesk_talk_queues | id PK · linked to zendesk_talk_calls |
| call legs | zendesk_talk_call_legs | id PK · linked to zendesk_talk_calls |
FAQ
How does Datrise handle Zendesk Talk'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 Talk to Looker Studio sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
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Early access
Connect Zendesk Talk to Looker Studio the easy way
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