Over the years, we've seen a couple of different organizational models for delivering analytics to the business. While both models have their advantages, each model has some severe drawbacks that make ...

A growing number of businesses are embracing data models — abstract models that organize elements of data and standardize how they relate to one another. But as the data analytics and AI boom drives ...

The development of database technology is one of the defining achievements of the information technology era. It not only has been the key to dramatically improved record-keeping and business process ...

Conventional data management systems are fundamentally ill-suited for the world of data as it exists today. These systems, based with few exceptions on the relational data model, are broken because ...

Element Analytics Inc., maker of a semantic data platform for use in industrial settings, today announced the availability of its Unify data management platform on Microsoft Corp.’s Azure Digital ...

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 ...

Sometimes, you can enter into a technology too early. The groundwork for semantics was laid down in the late 1990s and early 2000s, with Tim Berners-Lee's stellar Semantic Web article, debuting in ...

In 2024, the elephant in the room was how generative artificial intelligence seized the conversation. In 2025, the dialog shifted to agents and the question of whether there’s an AI bubble happening ...