DatriseAI-first ETL

Google Ecommerce to Qlik Integration

AI-first ETL from Google Ecommerce into Qlik. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Ecommerce into Qlik

Datrise syncs Google Ecommerce's transactions, products, product impressions, checkout steps, revenue, and refunds 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

Google Ecommerce: Ecommerce reporting from Google Analytics.

Qlik: Associative analytics with Qlik Sense apps and governed data models.

How Google Ecommerce entities map to Qlik

Google Ecommerce entityQlik objectNotes
transactionsgoogle_ecommerce_transactionsid PK · custom fields → flattened columns for the data model
productsgoogle_ecommerce_productsid PK · linked to google_ecommerce_transactions
product impressionsgoogle_ecommerce_product_impressionsid PK · linked to google_ecommerce_transactions
checkout stepsgoogle_ecommerce_checkout_stepsid PK · linked to google_ecommerce_transactions

FAQ

How does Datrise handle Google Ecommerce'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 Google Ecommerce 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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