Particle to GoodData Integration
AI-first ETL from Particle into GoodData. Governed entities, incremental sync, typed landing tables.
How Datrise loads Particle into GoodData
Datrise syncs Particle's devices, events, variables, firmware versions, product fleets, and device logs into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.
Ideal for embedded, multi-tenant analytics.
Endpoints
Particle: IoT device fleet telemetry and events.
GoodData: Composable analytics platform with headless BI and embedded dashboards.
How Particle entities map to GoodData
| Particle entity | GoodData object | Notes |
|---|---|---|
| devices | particle_devices | id PK · custom fields → flattened columns |
| events | particle_events | date 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 GoodData?
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 GoodData types.
How does the Particle to GoodData sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
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