Google PageSpeed Insights to Qlik Integration

How Datrise loads Google PageSpeed Insights into Qlik

Datrise syncs Google PageSpeed Insights's audits, lab metrics, field metrics, opportunities, page URLs, and performance scores into Qlik as tables loaded into Qlik's associative engine (often via QVD). Flexible or custom fields land in flattened columns for the data model, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental QVD loads merged on stable id, so re-runs update only what changed. QVD files per entity and load date. Qlik's associative model joins on identically named fields, so Datrise standardizes key names so associations link correctly.

Ideal for associative, in-memory exploration in Qlik Sense.

Endpoints

Google PageSpeed Insights: Page performance and Core Web Vitals audits.

Qlik: Associative analytics with Qlik Sense apps and governed data models.

How Google PageSpeed Insights entities map to Qlik

Google PageSpeed Insights entity	Qlik object	Notes
audits	`google_pagespeed_insights_audits`	id PK · custom fields → flattened columns for the data model
lab metrics	`google_pagespeed_insights_lab_metrics`	id PK · linked to google_pagespeed_insights_audits
field metrics	`google_pagespeed_insights_field_metrics`	id PK · linked to google_pagespeed_insights_audits
opportunities	`google_pagespeed_insights_opportunities`	id PK · linked to google_pagespeed_insights_audits

FAQ

How does Datrise handle Google PageSpeed Insights's custom fields in Qlik?

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

How does the Google PageSpeed Insights to Qlik sync stay up to date?

It runs incrementally — Datrise uses incremental QVD loads merged on stable id.

Related pipelines

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