Google Pagespeed Insights → Spotfire

AI-first ETL from Google Pagespeed Insights into Spotfire. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Pagespeed Insights into Spotfire

Datrise syncs Google Pagespeed Insights's records, events, and configuration objects into Spotfire as warehouse tables or in-memory data for Spotfire analyses. Flexible or custom fields land in flattened columns for visualizations, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables or in-memory data, so re-runs update only what changed. Date-partitioned facts. Spotfire can load data in-memory, so Datrise keeps the backing tables incremental so analyses refresh without full reloads.

Ideal for interactive analytical visualization and data science.

Endpoints

Google Pagespeed Insights: SaaS or API data source for analytics and warehouse sync.

Spotfire: Visual analytics platform for interactive dashboards and data science workflows.

How Google Pagespeed Insights entities map to Spotfire

Google Pagespeed Insights entity	Spotfire object	Notes
records	`google_pagespeed_insights_records`	id PK · custom fields → flattened columns for visualizations
events	`google_pagespeed_insights_events`	date/time columns events
configuration objects	`google_pagespeed_insights_configuration_objects`	id PK · linked to google_pagespeed_insights_records

FAQ

How does Datrise handle Google Pagespeed Insights's custom fields in Spotfire?

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

How does the Google Pagespeed Insights to Spotfire sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables or in-memory data.

Related pipelines

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Early access

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