Semantic enterprise data management is not a panacea, but overall, if you're willing to put the effort into growing these systems, it can prove to be one of the most effective ways of managing ...

Today's enterprises need unified semantic layers that seamlessly connect traditional BI, GenBI applications, and emerging AI workloads. As organizations face challenges in making enterprise data truly ...

The semantic layer is still an emerging technology, but it will clearly play an important role in the evolution of the modern data stack.

Agentic AI will transform how work gets done—but only if it runs on trusted, unified real-time data. The leaders are building ...

The patent obtained by Shulian Mingpin focuses on the visualization modeling method based on intelligent semantic understanding. This technology is expected to enhance the efficiency of processing ...

Although a universal semantic layer can’t solve all business problems, it can help organizations use complete, consistent data insights to navigate uncertainty.

Semantic Layer Implementation: The Key Challenges Organizations inevitably develop semantic layers when interacting with data, usually within BI platforms. As different parts of the organizations work ...

Semantics and virtualization, data integration and data governance on the way to the cloud It's official - data analytics is swiftly moving to the cloud.

Last week the annual Semantic Technology Conference wrapped up in San Francisco, leaving attendees with a wealth of information about the use of semantic technologies in healthcare, financial services ...

Leveraging structure in data is key to making progress in AI, says AI prodigy Gary Marcus. A forward-looking view on Software 2.0, AI chips, robotics, and the future of AI ...

Disparate BI, analytics, and data science tools result in discrepancies in data interpretation, business logic, and definitions among user groups. A universal semantic layer resolves those ...