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, ...

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 ...

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 ...

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 ...

Just as machine learning, artificial intelligence, data modeling and analytics platforms have transformed manufacturing, drug discovery, health care and operations in a host of other industries, these ...

The tools provide advanced data intelligence, data quality, and data modeling capabilities aimed at helping customers ensure the AI readiness of their data, the company said. Quest Software has ...

To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...

With the new challenges of agentic AI, insurers will increasingly expect evidence of AI-governance maturity, not just ...

Texas A&M AgriLife scientists used data modeling to uncover new insights into how cattle fever ticks survive and spread ...