DatriseAI-first ETL

New York Times to GoodData Integration

AI-first ETL from New York Times into GoodData. Governed entities, incremental sync, typed landing tables.

How Datrise loads New York Times into GoodData

Datrise syncs New York Times's articles, sections, headlines, bylines, publication dates, and keywords 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

New York Times: Article archive and top-stories metadata.

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

How New York Times entities map to GoodData

New York Times entityGoodData objectNotes
articlesnew_york_times_articlesid PK · custom fields → flattened columns
sectionsnew_york_times_sectionsid PK · linked to new_york_times_articles
headlinesnew_york_times_headlinesid PK · linked to new_york_times_articles
bylinesnew_york_times_bylinesid PK · linked to new_york_times_articles

FAQ

How does Datrise handle New York Times'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 New York Times to GoodData sync stay up to date?

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

Related pipelines

Early access

Connect New York Times to GoodData the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.