DatriseAI-first ETL

Openweather to Looker Studio Integration

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

How Datrise loads Openweather into Looker Studio

Datrise syncs Openweather's current conditions, forecasts, locations, temperature readings, precipitation, and observation times 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

Openweather: Current conditions and weather forecast data.

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

How Openweather entities map to Looker Studio

Openweather entityLooker Studio objectNotes
current conditionsopenweather_current_conditionsid PK · custom fields → flattened columns for chart fields
forecastsopenweather_forecastsid PK · linked to openweather_current_conditions
locationsopenweather_locationsid PK · linked to openweather_current_conditions
temperature readingsopenweather_temperature_readingsid PK · linked to openweather_current_conditions

FAQ

How does Datrise handle Openweather'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 Openweather to Looker Studio sync stay up to date?

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

Related pipelines

Early access

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