DatriseAI-first ETL

Zendesk Talk to Holistics Integration

AI-first ETL from Zendesk Talk into Holistics. Governed entities, incremental sync, typed landing tables.

How Datrise loads Zendesk Talk into Holistics

Datrise syncs Zendesk Talk's calls, agents, queues, call legs, recordings, and call metrics into Holistics as warehouse tables modeled in Holistics. Flexible or custom fields land in flattened columns for the modeling layer, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the modeled tables, so re-runs update only what changed. Date-partitioned facts for fast aggregates. Holistics models data as code on top of SQL, so Datrise lands stable column names to keep your models from drifting.

Ideal for as-code BI modeling on a warehouse.

Endpoints

Zendesk Talk: Voice support calls and queue performance.

Holistics: Self-service BI with modeling layers and scheduled report delivery.

How Zendesk Talk entities map to Holistics

Zendesk Talk entityHolistics objectNotes
callszendesk_talk_callsid PK · custom fields → flattened columns for the modeling layer
agentszendesk_talk_agentsid PK · linked to zendesk_talk_calls
queueszendesk_talk_queuesid PK · linked to zendesk_talk_calls
call legszendesk_talk_call_legsid PK · linked to zendesk_talk_calls

FAQ

How does Datrise handle Zendesk Talk's custom fields in Holistics?

Flexible values are stored as flattened columns for the modeling layer, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Holistics types.

How does the Zendesk Talk to Holistics sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the modeled tables.

Related pipelines

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