Time flies in the world of data analytics and artificial intelligence (AI). Seemingly every day, new technologies rise, new use cases emerge, and new frontiers unfurl themselves before a world that ...

For R&D leaders evaluating AI investments, I’d offer one piece of advice: Before spending more on models, look hard at your ...

IEEE research highlights multi-model databases outperform single-model systems, reducing AI costs, latency, and schema issues ...

The redesign of data pipelines, models, and governance frameworks is integral in facilitating the adoption of automation across asset servicing. Through re-engineering — which usually involves ...

Healthcare organizations are awash in data. But not every health system is able to utilize its data in ways that yield actionable insights or opportunities for performance improvement. Without a clear ...

Why modern observability systems fail during incidents, and how new architectures fix them.

Data integration is a leading priority for enterprise executives, with 82% of senior executives considering scaling AI a top priority. However, this ambition is frustrated by the longstanding practice ...

AI data center security cannot be an afterthought.

Data models are used to represent real-world entities, but they often have limitations. Avoid these common data modeling mistakes to keep data integrity. Data modeling is the process through which we ...