Persistiq to Spotfire Integration
AI-first ETL from Persistiq into Spotfire. Governed entities, incremental sync, typed landing tables.
How Datrise loads Persistiq into Spotfire
Datrise syncs Persistiq's prospects, campaigns, sequences, email events, users, and dispositions 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
Persistiq: Outbound sales sequences and prospect tracking.
Spotfire: Visual analytics platform for interactive dashboards and data science workflows.
How Persistiq entities map to Spotfire
| Persistiq entity | Spotfire object | Notes |
|---|---|---|
| prospects | persistiq_prospects | id PK · custom fields → flattened columns for visualizations |
| campaigns | persistiq_campaigns | id PK · linked to persistiq_prospects |
| sequences | persistiq_sequences | id PK · linked to persistiq_prospects |
| email events | persistiq_email_events | date/time columns events |
FAQ
How does Datrise handle Persistiq'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 Persistiq to Spotfire sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.
Related pipelines
More destinations for Persistiq
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