Streak → Birst
AI-first ETL from Streak into Birst. Governed entities, incremental sync, typed landing tables.
How Datrise loads Streak into Birst
Datrise syncs Streak's contacts, accounts, deals, activities, and lifecycle events into Birst as warehouse tables for Birst's automated star schema. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the source tables Birst ingests, so re-runs update only what changed. Date-partitioned facts. Birst builds its own semantic layer, so Datrise lands conformed, well-keyed tables it can automate against.
Ideal for networked, governed enterprise BI.
Endpoints
Streak: CRM for SMB teams managing pipeline, contacts, and customer activity.
Birst: Cloud BI with networked analytics and enterprise semantic layers.
How Streak entities map to Birst
| Streak entity | Birst object | Notes |
|---|---|---|
| contacts | streak_contacts | id PK · custom fields → flattened columns |
| accounts | streak_accounts | id PK · linked to streak_contacts |
| deals | streak_deals | id PK · linked to streak_contacts |
| activities | streak_activities | date/time dimensions events |
FAQ
How does Datrise handle Streak's custom fields in Birst?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Birst types.
How does the Streak to Birst sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.
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