DatriseAI-first ETL

Weatherstack to Holistics Integration

AI-first ETL from Weatherstack into Holistics. Governed entities, incremental sync, typed landing tables.

How Datrise loads Weatherstack into Holistics

Datrise syncs Weatherstack's current conditions, forecasts, historical readings, locations, temperature readings, and observation times into Holistics as warehouse tables modeled in Holistics. Flexible or custom fields land in flattened columns for the modeling layer, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the modeled tables, so re-runs update only what changed. Date-partitioned facts for fast aggregates. Holistics models data as code on top of SQL, so Datrise lands stable column names to keep your models from drifting.

Ideal for as-code BI modeling on a warehouse.

Endpoints

Weatherstack: Current, historical, and forecast weather lookups.

Holistics: Self-service BI with modeling layers and scheduled report delivery.

How Weatherstack entities map to Holistics

Weatherstack entityHolistics objectNotes
current conditionsweatherstack_current_conditionsid PK · custom fields → flattened columns for the modeling layer
forecastsweatherstack_forecastsid PK · linked to weatherstack_current_conditions
historical readingsweatherstack_historical_readingsdate/time dimensions events
locationsweatherstack_locationsid PK · linked to weatherstack_current_conditions

FAQ

How does Datrise handle Weatherstack's custom fields in Holistics?

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

How does the Weatherstack to Holistics sync stay up to date?

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

Related pipelines

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