DatriseAI-first ETL

Zendesk Chat Holistics

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

How Datrise loads Zendesk Chat into Holistics

Datrise syncs Zendesk Chat's chats, agents, visitors, departments, and response times 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 Chat: Live chat conversations and agent performance.

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

How Zendesk Chat entities map to Holistics

Zendesk Chat entityHolistics objectNotes
chatszendesk_chat_chatsid PK · custom fields → flattened columns for the modeling layer
agentszendesk_chat_agentsid PK · linked to zendesk_chat_chats
visitorszendesk_chat_visitorsid PK · linked to zendesk_chat_chats
departmentszendesk_chat_departmentsid PK · linked to zendesk_chat_chats

FAQ

How does Datrise handle Zendesk Chat'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 Chat to Holistics sync stay up to date?

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

Related pipelines

Early access

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