DatriseAI-first ETL

New York Times Microsoft Power BI

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

How Datrise loads New York Times into Microsoft Power BI

Datrise syncs New York Times's records, events, and configuration objects into Microsoft Power BI as star-schema-friendly tables for an Import or DirectQuery dataset. Flexible or custom fields land in flattened columns (nested fields expanded), and timestamps such as created, updated, and status changes are typed as date/time columns with a date table.

Sync is incremental: Datrise uses incremental-refresh windows aligned to Power BI's RangeStart/RangeEnd, so re-runs update only what changed. Date-partitioned fact tables matching incremental-refresh policies. Power BI measures and relationships live in the .pbix model, so Datrise keeps the underlying tables stable and star-schema-shaped.

Ideal for Microsoft-stack self-serve reporting.

Endpoints

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

Microsoft Power BI: Microsoft business intelligence with datasets, reports, and semantic models.

How New York Times entities map to Microsoft Power BI

New York Times entityMicrosoft Power BI objectNotes
recordsnew_york_times_recordsid PK · custom fields → flattened columns (nested fields expanded)
eventsnew_york_times_eventsdate/time columns with a date table 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 Microsoft Power BI?

Flexible values are stored as flattened columns (nested fields expanded), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft Power BI types.

How does the New York Times to Microsoft Power BI sync stay up to date?

It runs incrementally — Datrise uses incremental-refresh windows aligned to Power BI's RangeStart/RangeEnd.

Related pipelines

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