DatriseAI-first ETL

Freshcaller to ThoughtSpot Integration

AI-first ETL from Freshcaller into ThoughtSpot. Governed entities, incremental sync, typed landing tables.

How Datrise loads Freshcaller into ThoughtSpot

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

Freshcaller: Cloud call center for support and sales.

ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.

How Freshcaller entities map to ThoughtSpot

Freshcaller entityThoughtSpot objectNotes
callsfreshcaller_callsid PK · custom fields → flattened columns for searchable fields
agentsfreshcaller_agentsid PK · linked to freshcaller_calls
queuesfreshcaller_queuesid PK · linked to freshcaller_calls
phone numbersfreshcaller_phone_numbersid PK · linked to freshcaller_calls

FAQ

How does Datrise handle Freshcaller'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 Freshcaller to ThoughtSpot sync stay up to date?

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

Related pipelines

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