Particle to Yellowfin Integration
AI-first ETL from Particle into Yellowfin. Governed entities, incremental sync, typed landing tables.
How Datrise loads Particle into Yellowfin
Datrise syncs Particle's devices, events, variables, firmware versions, product fleets, and device logs into Yellowfin as warehouse tables Yellowfin builds views on. 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 connected tables, so re-runs update only what changed. Date-partitioned facts. Yellowfin views reference columns by name, so Datrise lands stable, well-typed columns to keep reports valid.
Ideal for dashboards with automated data storytelling.
Endpoints
Particle: IoT device fleet telemetry and events.
Yellowfin: BI suite with dashboards, automated insights, and data storytelling.
How Particle entities map to Yellowfin
| Particle entity | Yellowfin object | Notes |
|---|---|---|
| devices | particle_devices | id PK · custom fields → flattened columns |
| events | particle_events | date/time dimensions events |
| variables | particle_variables | id PK · linked to particle_devices |
| firmware versions | particle_firmware_versions | id PK · linked to particle_devices |
FAQ
How does Datrise handle Particle's custom fields in Yellowfin?
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 Yellowfin types.
How does the Particle to Yellowfin sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Particle
More sources for Yellowfin
Early access
Connect Particle to Yellowfin the easy way
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