Even as large language models have been making a splash with ChatGPT and its competitors, another incoming AI wave has been quietly emerging: large database models. Even as large language models have ...

AI systems fail because of a context gap—when decisions rely on incomplete, inconsistent and outdated data across systems.

Anthropic is testing a new AI model that has exhibited an unusual behavior during safety evaluations: it told testers it ...

At its heart, data modeling is about understanding how data flows through a system. Just as a map can help us understand a city’s layout, data modeling can help us understand the complexities of a ...

The healthcare system is faced with a tsunami of incoming data. In fact, the average hospital produces roughly 50 petabytes of data every year. That’s more than twice the amount of data housed in the ...

In the simplest terms, a logical data model is a visual representation of the business rules and requirements covering the universe-of-discourse for a given solution or enterprise, along with some ...

In the rapidly evolving landscape of modern manufacturing and engineering, a new technology is emerging as a crucial enabler-Data-Model Fusion (DMF). A recent review paper published in Engineering ...

Distributed database consistency models form the backbone of reliable and high-performance systems in today’s interconnected digital landscape. These models define the guarantees provided by a ...

How to Improve Cancer Patients ENrollment in Clinical Trials From rEal-Life Databases Using the Observational Medical Outcomes Partnership Oncology Extension: Results of the PENELOPE Initiative in ...

Data modeling tools play an important role in business, representing how data flows through an organization. It’s important for businesses to understand what the best data modeling tools are across ...