Zenloop to Spotfire Integration
AI-first ETL from Zenloop into Spotfire. Governed entities, incremental sync, typed landing tables.
How Datrise loads Zenloop into Spotfire
Datrise syncs Zenloop's surveys, answers, NPS scores, respondents, sentiment labels, and feedback topics 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
Zenloop: NPS surveys and customer feedback analysis.
Spotfire: Visual analytics platform for interactive dashboards and data science workflows.
How Zenloop entities map to Spotfire
| Zenloop entity | Spotfire object | Notes |
|---|---|---|
| surveys | zenloop_surveys | id PK · custom fields → flattened columns for visualizations |
| answers | zenloop_answers | id PK · linked to zenloop_surveys |
| NPS scores | zenloop_nps_scores | id PK · linked to zenloop_surveys |
| respondents | zenloop_respondents | id PK · linked to zenloop_surveys |
FAQ
How does Datrise handle Zenloop'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 Zenloop 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 Zenloop
Early access
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