DatriseAI-first ETL

Senseforce to Looker Studio Integration

AI-first ETL from Senseforce into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Senseforce into Looker Studio

Datrise syncs Senseforce's assets, sensor readings, events, machines, time series values, and alarms into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

Senseforce: Industrial IoT machine telemetry and analytics.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Senseforce entities map to Looker Studio

Senseforce entityLooker Studio objectNotes
assetssenseforce_assetsid PK · custom fields → flattened columns for chart fields
sensor readingssenseforce_sensor_readingsid PK · linked to senseforce_assets
eventssenseforce_eventsdate dimension columns events
machinessenseforce_machinesid PK · linked to senseforce_assets

FAQ

How does Datrise handle Senseforce's custom fields in Looker Studio?

Flexible values are stored as flattened columns for chart fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker Studio types.

How does the Senseforce to Looker Studio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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