Square → Qlik
AI-first ETL from Square into Qlik. Governed entities, incremental sync, typed landing tables.
How Datrise loads Square into Qlik
Datrise syncs Square's payments, orders, customers, catalog items, and locations into Qlik as tables loaded into Qlik's associative engine (often via QVD). Flexible or custom fields land in flattened columns for the data model, and timestamps such as created, updated, and status changes are typed as date/time fields.
Sync is incremental: Datrise uses incremental QVD loads merged on stable id, so re-runs update only what changed. QVD files per entity and load date. Qlik's associative model joins on identically named fields, so Datrise standardizes key names so associations link correctly.
Ideal for associative, in-memory exploration in Qlik Sense.
Endpoints
Square: Payments and commerce platform for retail and online sellers.
Qlik: Associative analytics with Qlik Sense apps and governed data models.
How Square entities map to Qlik
| Square entity | Qlik object | Notes |
|---|---|---|
| payments | square_payments | id PK · custom fields → flattened columns for the data model |
| 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 Qlik?
Flexible values are stored as flattened columns for the data model, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Qlik types.
How does the Square to Qlik sync stay up to date?
It runs incrementally — Datrise uses incremental QVD loads merged on stable id.
Related pipelines
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