Keap → Birst
AI-first ETL from Keap into Birst. Governed entities, incremental sync, typed landing tables.
How Datrise loads Keap into Birst
Datrise syncs Keap's SMB contacts, opportunities, automations, and appointment workflows 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
Keap: SMB CRM with pipeline automation, email, and appointment flows.
Birst: Cloud BI with networked analytics and enterprise semantic layers.
How Keap entities map to Birst
| Keap entity | Birst object | Notes |
|---|---|---|
| SMB contacts | keap_smb_contacts | id PK · custom fields → flattened columns |
| opportunities | keap_opportunities | id PK · linked to keap_smb_contacts |
| automations | keap_automations | id PK · linked to keap_smb_contacts |
| appointment workflows | keap_appointment_workflows | id PK · linked to keap_smb_contacts |
FAQ
How does Datrise handle Keap'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 Keap to Birst sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the source tables Birst ingests.
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