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 ...

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 ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Occasionally one may hear that a data model is “over-normalized,” but just what does that mean? Normalization is intended to analyze the functional dependencies across a set of data. The goal is to ...

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 ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

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 ...

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 ...