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. Data analysts can help build ...

The following article is an excerpt (Chapter 3) from the book Hands-On Big Data Modeling by James Lee, Tao Wei, and Suresh Kumar Mukhiya published by our friends over at Packt. The article addresses ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

Explore the insights of Andrei Marius Popescu on data modeling and the idea that not every model error is a failure.

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, ...

The Covid-19 pandemic reminded us that everyday life is full of interdependencies. The data models and logic for tracking the progress of the pandemic, understanding its spread in the population, ...

Big data is less predictable than traditional data, and therefore requires special consideration when building models. Here are some things to keep in mind. Most projects benefit from having a data ...