Zendesk Chat → ThoughtSpot
AI-first ETL from Zendesk Chat into ThoughtSpot. Governed entities, incremental sync, typed landing tables.
How Datrise loads Zendesk Chat into ThoughtSpot
Datrise syncs Zendesk Chat's chats, agents, visitors, departments, and response times into ThoughtSpot as warehouse tables ThoughtSpot indexes for search. Flexible or custom fields land in flattened columns for searchable fields, and timestamps such as created, updated, and status changes are typed as date/time columns.
Sync is incremental: Datrise uses incremental refresh of the indexed tables, so re-runs update only what changed. Date-partitioned facts for live-query performance. ThoughtSpot search relies on clear names and relationships, so Datrise lands well-named, joinable tables.
Ideal for natural-language search analytics over a warehouse.
Endpoints
Zendesk Chat: Live chat conversations and agent performance.
ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.
How Zendesk Chat entities map to ThoughtSpot
| Zendesk Chat entity | ThoughtSpot object | Notes |
|---|---|---|
| chats | zendesk_chat_chats | id PK · custom fields → flattened columns for searchable fields |
| agents | zendesk_chat_agents | id PK · linked to zendesk_chat_chats |
| visitors | zendesk_chat_visitors | id PK · linked to zendesk_chat_chats |
| departments | zendesk_chat_departments | id PK · linked to zendesk_chat_chats |
FAQ
How does Datrise handle Zendesk Chat's custom fields in ThoughtSpot?
Flexible values are stored as flattened columns for searchable fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native ThoughtSpot types.
How does the Zendesk Chat to ThoughtSpot sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the indexed tables.
Related pipelines
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Early access
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