DatriseAI-first ETL

Looker to Qlik Integration

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

How Datrise loads Looker into Qlik

Datrise syncs Looker's looks, dashboards, explores, queries, users, and scheduled plans 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

Looker: BI platform with a modeled semantic layer.

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

How Looker entities map to Qlik

Looker entityQlik objectNotes
lookslooker_looksid PK · custom fields → flattened columns for the data model
dashboardslooker_dashboardsid PK · linked to looker_looks
exploreslooker_exploresid PK · linked to looker_looks
querieslooker_queriesid PK · linked to looker_looks

FAQ

How does Datrise handle Looker'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 Looker 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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