Public API → Microsoft Power BI
AI-first ETL from Public API into Microsoft Power BI. Governed entities, incremental sync, typed landing tables.
How Datrise loads Public API into Microsoft Power BI
Datrise syncs Public API'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
Public API: SaaS or API data source for analytics and warehouse sync.
Microsoft Power BI: Microsoft business intelligence with datasets, reports, and semantic models.
How Public API entities map to Microsoft Power BI
| Public API entity | Microsoft Power BI object | Notes |
|---|---|---|
| records | public_api_records | id PK · custom fields → flattened columns (nested fields expanded) |
| events | public_api_events | date/time columns with a date table events |
| configuration objects | public_api_configuration_objects | id PK · linked to public_api_records |
FAQ
How does Datrise handle Public API'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 Public API to Microsoft Power BI sync stay up to date?
It runs incrementally — Datrise uses incremental-refresh windows aligned to Power BI's RangeStart/RangeEnd.
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Early access
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