Freshcaller to Looker Studio Integration

How Datrise loads Freshcaller into Looker Studio

Datrise syncs Freshcaller's calls, agents, queues, phone numbers, call metrics, and recordings 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

Freshcaller: Cloud call center for support and sales.

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

How Freshcaller entities map to Looker Studio

Freshcaller entity	Looker Studio object	Notes
calls	`freshcaller_calls`	id PK · custom fields → flattened columns for chart fields
agents	`freshcaller_agents`	id PK · linked to freshcaller_calls
queues	`freshcaller_queues`	id PK · linked to freshcaller_calls
phone numbers	`freshcaller_phone_numbers`	id PK · linked to freshcaller_calls

FAQ

How does Datrise handle Freshcaller'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 Freshcaller 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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