Retently to Spotfire Integration
AI-first ETL from Retently into Spotfire. Governed entities, incremental sync, typed landing tables.
How Datrise loads Retently into Spotfire
Datrise syncs Retently's surveys, responses, customers, NPS scores, campaigns, and feedback comments 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
Retently: NPS and customer satisfaction survey tracking.
Spotfire: Visual analytics platform for interactive dashboards and data science workflows.
How Retently entities map to Spotfire
| Retently entity | Spotfire object | Notes |
|---|---|---|
| surveys | retently_surveys | id PK · custom fields → flattened columns for visualizations |
| responses | retently_responses | id PK · linked to retently_surveys |
| customers | retently_customers | id PK · linked to retently_surveys |
| NPS scores | retently_nps_scores | id PK · linked to retently_surveys |
FAQ
How does Datrise handle Retently'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 Retently to Spotfire sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.
Related pipelines
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