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 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 ...

It’s no longer how good your model is, it’s how good your data is. Why privacy-preserving synthetic data is key to scaling AI. The potential of generative AI has captivated both businesses and ...

Vikram is the co-founder and CEO at Galileo, a category leader for ML data quality. Previously, he led product management at Google AI. Few topics get tossed around as objects of intrigue, excitement ...

COMMISSIONED As enterprises increasingly adopt GenAI-powered AI agents, making high-quality data available for these software assistants will come into sharper focus. This is why it’s more important ...

In healthcare, the costs are not merely financial. Incomplete, inconsistent or delayed electronic health records can lead to ...

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 ...

"If you focus on the enterprise segments, then all of the AI solutions that they're building still need to be evaluated, which is just another word for data labeling by humans and even more so by ...

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 ...

Fab operations have wrestled with big data management issues for decades. Standards help, but only if sufficient attention to detail is taken during collection. Semiconductor wafer manufacturing ...