Heap to Tableau Integration
AI-first ETL from Heap into Tableau. Governed entities, incremental sync, typed landing tables.
How Datrise loads Heap into Tableau
Datrise syncs Heap's events, users, sessions, funnels, segments, and user properties into Tableau as warehouse tables or a refreshed .hyper extract. Flexible or custom fields land in flattened columns for Tableau fields, and timestamps such as created, updated, and status changes are typed as date/datetime fields.
Sync is incremental: Datrise uses incremental refresh of the tables behind a live connection or extract, so re-runs update only what changed. Date-partitioned facts to keep extract refresh quick. Tableau .hyper extracts snapshot data, so Datrise keeps the source tables incremental and lets you choose live vs extract.
Ideal for visual analytics and dashboards in Tableau.
Endpoints
Heap: Autocaptured product analytics and funnels.
Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.
How Heap entities map to Tableau
| Heap entity | Tableau object | Notes |
|---|---|---|
| events | heap_events | date/datetime fields 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 Tableau?
Flexible values are stored as flattened columns for Tableau fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Tableau types.
How does the Heap to Tableau sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.
Related pipelines
More destinations for Heap
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