Heap to ThoughtSpot Integration
AI-first ETL from Heap into ThoughtSpot. Governed entities, incremental sync, typed landing tables.
How Datrise loads Heap into ThoughtSpot
Datrise syncs Heap's events, users, sessions, funnels, segments, and user properties 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
Heap: Autocaptured product analytics and funnels.
ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.
How Heap entities map to ThoughtSpot
| Heap entity | ThoughtSpot object | Notes |
|---|---|---|
| events | heap_events | date/time columns events |
| users | heap_users | id PK · linked to heap_events |
| sessions | heap_sessions | id PK · linked to heap_events |
| funnels | heap_funnels | id PK · linked to heap_events |
FAQ
How does Datrise handle Heap'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 Heap to ThoughtSpot sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the indexed tables.
Related pipelines
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