PHILADELPHIA, PA — Qlik has introduced a data management capability designed to standardize business metrics across analytics applications and artificial intelligence systems, expanding its enterprise software platform as companies seek more consistent interpretations of corporate data.
The Philadelphia-based software company said its Semantic Models capability allows organizations to define, govern and reuse business terminology, calculations and relationships within existing data products.
The technology addresses a recurring problem in enterprise analytics: different applications can produce conflicting results when they apply different definitions to the same underlying data.
For example, a company’s reported net revenue can vary depending on how individual systems account for returns, discounts and reporting periods. Standardizing those calculations allows analytics applications and supported AI systems to work from the same business definitions.
“A number can be mathematically correct and still answer the wrong business question,” said Sam Pierson, Qlik’s chief technology officer. “Teams need to understand which definition is being used and apply it consistently.”
Semantic Models builds on Qlik’s existing data-product capabilities, which combine curated datasets with information about ownership, data lineage and quality.
The new functionality connects business terminology from an organization’s glossary with the measures and dimensions used in analytics, allowing developers to reuse established calculations rather than recreate them for individual applications.
Qlik is also introducing tools to extract business definitions from existing Qlik analytics applications and incorporate them into governed data products.
That extraction capability entered public preview October 28, with general availability planned for later in the fourth quarter.
The company is extending semantic model support to Qlik Answers and Model Context Protocol tools, which would allow supported AI applications and agents to interpret enterprise information using the same governed definitions as conventional analytics systems.
Availability of those integrations is targeted for the general release of Semantic Models or shortly afterward. Qlik also plans AI-assisted tools for creating and maintaining semantic models.
The expansion reflects Qlik’s effort to connect its established analytics technology with enterprise AI workflows, where inconsistent business definitions can affect the reliability of automated responses.
Henri Rufin, head of data and analytics at Radiall, described the potential operational benefit of maintaining common definitions across applications.
“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,” Rufin stated.
Qlik is also developing interoperability with Apache Ossie, an incubating open-source project at the Apache Software Foundation. A public preview is planned as development progresses.
Semantic Models was targeted for general availability October 28 across products supporting Qlik Data Products, including Qlik Cloud Analytics, Qlik Talend Cloud Premium and Enterprise editions, and Qlik Sense Enterprise SaaS.
The additions broaden Qlik’s data governance capabilities beyond managing the quality and origin of information to standardizing how that information is interpreted across analytics and AI applications.
Support the local news that supports Chester County. MyChesCo delivers reliable, fact-based reporting and essential community resources—free for everyone. If you value that, click here to become a patron today.