DatriseAI-first ETL

New York Times to ThoughtSpot Integration

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

How Datrise loads New York Times into ThoughtSpot

Datrise syncs New York Times's articles, sections, headlines, bylines, publication dates, and keywords into ThoughtSpot as warehouse tables ThoughtSpot indexes for search. Flexible or custom fields land in flattened columns for searchable fields, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the indexed tables, so re-runs update only what changed. Date-partitioned facts for live-query performance. ThoughtSpot search relies on clear names and relationships, so Datrise lands well-named, joinable tables.

Ideal for natural-language search analytics over a warehouse.

Endpoints

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

ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.

How New York Times entities map to ThoughtSpot

New York Times entityThoughtSpot objectNotes
articlesnew_york_times_articlesid PK · custom fields → flattened columns for searchable fields
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 ThoughtSpot?

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

How does the New York Times to ThoughtSpot sync stay up to date?

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

Related pipelines

Early access

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