Dixa → ThoughtSpot
AI-first ETL from Dixa into ThoughtSpot. Governed entities, incremental sync, typed landing tables.
How Datrise loads Dixa into ThoughtSpot
Datrise syncs Dixa's conversations, agents, customers, tags, and resolution metrics 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
Dixa: Customer service platform for conversations across channels.
ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.
How Dixa entities map to ThoughtSpot
| Dixa entity | ThoughtSpot object | Notes |
|---|---|---|
| conversations | dixa_conversations | id PK · custom fields → flattened columns for searchable fields |
| agents | dixa_agents | id PK · linked to dixa_conversations |
| customers | dixa_customers | id PK · linked to dixa_conversations |
| tags | dixa_tags | id PK · linked to dixa_conversations |
FAQ
How does Datrise handle Dixa'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 Dixa to ThoughtSpot sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the indexed tables.
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