DatriseAI-first ETL

Google Pagespeed Insights GoodData

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

How Datrise loads Google Pagespeed Insights into GoodData

Datrise syncs Google Pagespeed Insights's records, events, and configuration objects into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.

Ideal for embedded, multi-tenant analytics.

Endpoints

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

GoodData: Composable analytics platform with headless BI and embedded dashboards.

How Google Pagespeed Insights entities map to GoodData

Google Pagespeed Insights entityGoodData objectNotes
recordsgoogle_pagespeed_insights_recordsid PK · custom fields → flattened columns
eventsgoogle_pagespeed_insights_eventsdate dimensions 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 GoodData?

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

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

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

Related pipelines

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