Data modeling, at its core, is the process of transforming raw data into meaningful insights. It involves creating representations of a database’s structure and organization. These models are often ...

Dr. Chris Hillman, Global AI Lead at Teradata, joins eSpeaks to explore why open data ecosystems are becoming essential for enterprise AI success. In this episode, he breaks down how openness — in ...

Japan is facing the urgent challenge of aging infrastructure, amidst ineffective linking of on-site experience and expertise with vast amounts of digital data in maintenance operations. This is ...

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 ...

Alexandra Twin has 15+ years of experience as an editor and writer, covering financial news for public and private companies. Investopedia / Zoe Hansen Overfitting occurs when a model is too closely ...

Data Matching to Support Analysis of Cancer Epidemiology Among Veterans Compared With Non-Veteran Populations—An Exemplar in Brain Tumors Real world data (RWD) were from the Flatiron Health advanced ...

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, ...