DatriseAI-first ETL

Teradata D Microsoft Power BI

AI-first ETL from Teradata D into Microsoft Power BI. Governed entities, incremental sync, typed landing tables.

How Datrise loads Teradata D into Microsoft Power BI

Datrise syncs Teradata D'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

Teradata D: SaaS or API data source for analytics and warehouse sync.

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

How Teradata D entities map to Microsoft Power BI

Teradata D entityMicrosoft Power BI objectNotes
recordsteradata_d_recordsid PK · custom fields → flattened columns (nested fields expanded)
eventsteradata_d_eventsdate/time columns with a date table events
configuration objectsteradata_d_configuration_objectsid PK · linked to teradata_d_records

FAQ

How does Datrise handle Teradata D'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 Teradata D 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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