Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Most organizations are now well into re-platforming their enterprise data ...

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 ...

Microsoft’s Semantic Kernel SDK makes it easier to manage complex prompts and get focused results from large language models like GPT. At first glance, building a large language model (LLM) like GPT-4 ...

With the vast amount of data that enterprises are generating and storing, leaders are continually reminded to get their data in order so they can generate business insight and prepare for AI ...

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 ...

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 ...

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 ...

Semantic data helps teams understand what their information represents. It gives data a clear meaning so people know how ...