DatriseAI-first ETL

Google Pagespeed Insights Looker Studio

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

How Datrise loads Google Pagespeed Insights into Looker Studio

Datrise syncs Google Pagespeed Insights's records, events, and configuration objects 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

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

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

How Google Pagespeed Insights entities map to Looker Studio

Google Pagespeed Insights entityLooker Studio objectNotes
recordsgoogle_pagespeed_insights_recordsid PK · custom fields → flattened columns for chart fields
eventsgoogle_pagespeed_insights_eventsdate dimension columns events
configuration objectsgoogle_pagespeed_insights_configuration_objectsid PK · linked to google_pagespeed_insights_records

FAQ

How does Datrise handle Google Pagespeed Insights'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 Google Pagespeed Insights 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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