Keap → Spotfire
AI-first ETL from Keap into Spotfire. Governed entities, incremental sync, typed landing tables.
How Datrise loads Keap into Spotfire
Datrise syncs Keap's SMB contacts, opportunities, automations, and appointment workflows into Spotfire as warehouse tables or in-memory data for Spotfire analyses. Flexible or custom fields land in flattened columns for visualizations, and timestamps such as created, updated, and status changes are typed as date/time columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables or in-memory data, so re-runs update only what changed. Date-partitioned facts. Spotfire can load data in-memory, so Datrise keeps the backing tables incremental so analyses refresh without full reloads.
Ideal for interactive analytical visualization and data science.
Endpoints
Keap: SMB CRM with pipeline automation, email, and appointment flows.
Spotfire: Visual analytics platform for interactive dashboards and data science workflows.
How Keap entities map to Spotfire
| Keap entity | Spotfire object | Notes |
|---|---|---|
| SMB contacts | keap_smb_contacts | id PK · custom fields → flattened columns for visualizations |
| 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 Spotfire?
Flexible values are stored as flattened columns for visualizations, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Spotfire types.
How does the Keap to Spotfire sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.
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