A Covid-19 restrictions sign hangs outside a supermarket in Austin, Texas. Lauren Ancel Meyers at the University of Texas at Austin has shared her team’s modeling results with city officials who make ...

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, ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

Data assimilation integrates observational data with numerical ocean models to produce accurate estimates and forecasts of the ocean state. Techniques range from variational methods, which adjust ...

Data modeling best practices help define a formal process that gives structure and direction to an organization’s data. Read more about data modeling now. Data modeling, at its core, is the process of ...

Most projects benefit from having a data model. This article gives an overview of the most common types. At its heart, data modeling is about understanding how data flows through a system. Just as a ...

Statistical modeling lies at the heart of data science. Well-crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In ...

As more organizations embrace big data and analytics to gain insight from extremely large datasets, the tools and systems used to manage data have grown, changed, and mul­tiplied. Instead of just ...

Uncertainty quantification (UQ) is a field of study that focuses on understanding, modeling, and reducing uncertainties in computational models and real-world systems. It is widely used in engineering ...