DatriseAI-first ETL

Day.ai to ThoughtSpot Integration

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

How Datrise loads Day.ai into ThoughtSpot

Datrise syncs Day.ai's contacts, companies, meetings, opportunities, AI summaries, and relationship signals 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

Day.ai: CRM that builds records from meetings and email automatically.

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

How Day.ai entities map to ThoughtSpot

Day.ai entityThoughtSpot objectNotes
contactsday_ai_contactsid PK · custom fields → flattened columns for searchable fields
companiesday_ai_companiesid PK · linked to day_ai_contacts
meetingsday_ai_meetingsid PK · linked to day_ai_contacts
opportunitiesday_ai_opportunitiesid PK · linked to day_ai_contacts

FAQ

How does Datrise handle Day.ai'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 Day.ai to ThoughtSpot sync stay up to date?

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

Related pipelines

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