DatriseAI-first ETL

New York Times Tableau

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

How Datrise loads New York Times into Tableau

Datrise syncs New York Times's records, events, and configuration objects into Tableau as warehouse tables or a refreshed .hyper extract. Flexible or custom fields land in flattened columns for Tableau fields, and timestamps such as created, updated, and status changes are typed as date/datetime fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind a live connection or extract, so re-runs update only what changed. Date-partitioned facts to keep extract refresh quick. Tableau .hyper extracts snapshot data, so Datrise keeps the source tables incremental and lets you choose live vs extract.

Ideal for visual analytics and dashboards in Tableau.

Endpoints

New York Times: SaaS or API data source for analytics and warehouse sync.

Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.

How New York Times entities map to Tableau

New York Times entityTableau objectNotes
recordsnew_york_times_recordsid PK · custom fields → flattened columns for Tableau fields
eventsnew_york_times_eventsdate/datetime fields events
configuration objectsnew_york_times_configuration_objectsid PK · linked to new_york_times_records

FAQ

How does Datrise handle New York Times's custom fields in Tableau?

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

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

It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.

Related pipelines

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