First, institutions must ensure that synthetic datasets are continuously recalibrated against fresh, real-world evidence. The ...

Learn what overfitting is, how it impacts data models, and effective strategies to prevent it, such as cross-validation and simplification.

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

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 ...

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, ...

A resource from the MetroLab Network offers local governments guidance about data governance policy and best practices. The resource, titled Model Data Governance Policy & Practice Guide, offers ...

A guide to the 10 most common data modeling mistakes Your email has been sent Data modeling is the process through which we represent information system objects or entities and the connections between ...

Conversion is usually preceded by several interactions with a website or an app. Attribution determines the role of each touchpoint in driving conversions and assigns credit for sales to interactions ...

Join the audience for a live webinar at 3 p.m. GMT/10 a.m. EST on 21 January 2026 Discover the role of impedance analysis in advancing battery-model development ...