Qlik Introduces Semantic Models for Shared Business Context Across Analytics and AI

New capability brings governed definitions, expressions and relationships into reusable data products, helping teams reduce duplicate modeling and deliver more consistent results across analytics and AI

Key takeaways:

• Define business meaning: Analytics, data teams, and business users trust the data they see and act on it faster by giving analytics and data teams a shared, governed definition of each metric.
• Reuse the work: Analytics developers save modeling time by reusing governed business logic across applications, reducing the need to rebuild and reconcile the same definitions.
• Support AI readiness: Teams building AI workflows interpret enterprise data more consistently by giving supported AI experiences shared business definitions and context.

PHILADELPHIA, Oct. 28, 2026 (GLOBE NEWSWIRE) — Qlik^® today introduced Semantic Models, a new capability for defining, governing and reusing business definitions within data products. The capability helps teams reduce duplicated modeling and gives analytics and AI a consistent basis for interpreting enterprise data.

A question about net revenue needs more than access to sales records. It also needs the company’s rules for returns, discounts, and reporting periods. When those rules differ across applications, plausible answers can mean different things. Semantic Models let teams make the intended definitions and relationships explicit and reusable.

Semantic Models add reusable business logic to Qlik’s existing data-product capabilities, which already bring together curated datasets, ownership, lineage and data-quality information. Teams can manage the meaning of their data alongside information about its source and fitness for use.

“A number can be mathematically correct and still answer the wrong business question,” said Sam Pierson, Chief Technology Officer at Qlik. “Teams need to understand which definition is being used and apply it consistently. With Semantic Models, we are making that work reusable within governed data products, so customers can build on the business logic they establish as their use of analytics and AI grows.”

What’s new with Qlik Semantic Models

• Give teams a shared business language: Help business users, data teams and AI systems work from consistent definitions of key business terms and metrics. Semantic Models connects governed business terminology from the business glossary with the measures and dimensions used across analytics and data products.
• Build on existing business logic: Help organizations reuse years of investment in Qlik analytics applications instead of recreating established definitions and calculations. Initially available as a public preview on October 28, a new extraction capability will let teams bring semantic definitions from existing Qlik analytics applications into reusable, governed and discoverable data products, with general availability planned for later in Q4.
• Make trusted business context available to AI agents: Help AI-powered experiences interpret enterprise data using governed definitions and relationships. Qlik is extending semantic model support to Qlik Answers^® and MCP tools, with availability targeted for Semantic Models general availability or shortly thereafter. Qlik is also planning AI assistance to help teams create and maintain semantic models.
• Advance interoperability across the data ecosystem: Help organizations make semantic definitions more useful across technologies and workflows. Qlik is developing interoperability with Apache Ossie (incubating), an open-source initiative at the Apache Software Foundation, with a public preview planned as work progresses.

“AI is only as useful as the data and business context behind it. With Qlik Semantic Models, we can bring our business definitions, metrics and relationships together in a governed, reusable way, giving our teams a consistent foundation for analytics and AI,” shared Henri Rufin, Head of Data & Analytics, Radiall. “Instead of recreating context for every new use case, we can build on a shared understanding of our business and make that context available, wherever it is needed.”

Qlik’s analytics engine applies governed measures and dimensions when analyzing structured data. The new semantic-model workflow is designed to make the definitions feeding analytics reusable through data products, giving teams a shared starting point for applications and the AI experiences built on them.

Availability

Qlik Semantic Models is targeted for general availability on October 28, 2026, wherever Data Products is available: Qlik Cloud Analytics^® and Qlik Talend Cloud^® Premium and Enterprise editions, and Qlik Sense^® Enterprise SaaS.

For more information, visit Qlik.com.

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