DatriseAI-first ETL

Vincle to Microsoft Power BI Integration

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

How Datrise loads Vincle into Microsoft Power BI

Datrise syncs Vincle's customers, visits, orders, product assortments, promotions, and sales routes 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

Vincle: Field sales and trade execution for consumer goods.

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

How Vincle entities map to Microsoft Power BI

Vincle entityMicrosoft Power BI objectNotes
customersvincle_customersid PK · custom fields → flattened columns (nested fields expanded)
visitsvincle_visitsid PK · linked to vincle_customers
ordersvincle_ordersid PK · linked to vincle_customers
product assortmentsvincle_product_assortmentsid PK · linked to vincle_customers

FAQ

How does Datrise handle Vincle'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 Vincle 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

Early access

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