DatriseAI-first ETL

BoomTown to ThoughtSpot Integration

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

How Datrise loads BoomTown into ThoughtSpot

Datrise syncs BoomTown's leads, contacts, listings, opportunities, property alerts, and agent interactions 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

BoomTown: Real estate lead generation with predictive agent alerts.

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

How BoomTown entities map to ThoughtSpot

BoomTown entityThoughtSpot objectNotes
leadsboomtown_leadsid PK · custom fields → flattened columns for searchable fields
contactsboomtown_contactsid PK · linked to boomtown_leads
listingsboomtown_listingsid PK · linked to boomtown_leads
opportunitiesboomtown_opportunitiesid PK · linked to boomtown_leads

FAQ

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

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

Related pipelines

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