Streak to Tableau Integration
AI-first ETL from Streak into Tableau. Governed entities, incremental sync, typed landing tables.
How Datrise loads Streak into Tableau
Datrise syncs Streak's pipelines, boxes, stages, email threads, contacts, and tasks 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
Streak: CRM that lives inside Gmail as pipelines and boxes.
Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.
How Streak entities map to Tableau
| Streak entity | Tableau object | Notes |
|---|---|---|
| pipelines | streak_pipelines | id PK · custom fields → flattened columns for Tableau fields |
| boxes | streak_boxes | id PK · linked to streak_pipelines |
| stages | streak_stages | id PK · linked to streak_pipelines |
| email threads | streak_email_threads | id PK · linked to streak_pipelines |
FAQ
How does Datrise handle Streak'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 Streak 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 Streak
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