Square → GoodData
AI-first ETL from Square into GoodData. Governed entities, incremental sync, typed landing tables.
How Datrise loads Square into GoodData
Datrise syncs Square's payments, orders, customers, catalog items, and locations into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.
Ideal for embedded, multi-tenant analytics.
Endpoints
Square: Payments and commerce platform for retail and online sellers.
GoodData: Composable analytics platform with headless BI and embedded dashboards.
How Square entities map to GoodData
| Square entity | GoodData object | Notes |
|---|---|---|
| payments | square_payments | id PK · custom fields → flattened columns |
| orders | square_orders | id PK · linked to square_payments |
| customers | square_customers | id PK · linked to square_payments |
| catalog items | square_catalog_items | id PK · linked to square_payments |
FAQ
How does Datrise handle Square's custom fields in GoodData?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native GoodData types.
How does the Square to GoodData sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
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