DatriseAI-first ETL

Square Microsoft Power BI

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

How Datrise loads Square into Microsoft Power BI

Datrise syncs Square's payments, orders, customers, catalog items, and locations 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

Square: Payments and commerce platform for retail and online sellers.

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

How Square entities map to Microsoft Power BI

Square entityMicrosoft Power BI objectNotes
paymentssquare_paymentsid PK · custom fields → flattened columns (nested fields expanded)
orderssquare_ordersid PK · linked to square_payments
customerssquare_customersid PK · linked to square_payments
catalog itemssquare_catalog_itemsid PK · linked to square_payments

FAQ

How does Datrise handle Square'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 Square 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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