Data centers are crucial for storing, processing, and distributing vast amounts of data in the modern era, as internet-based data-transfer services are essential in our daily work and personal lives.

Most projects benefit from having a data model. This article gives an overview of the most common types. At its heart, data modeling is about understanding how data flows through a system. Just as a ...

Integrating AI into chip workflows is pushing companies to overhaul their data management strategies, shifting from passive storage to active, structured, and machine-readable systems. As training and ...

Model-based systems engineering (MBSE) has been around for a while, but it continues to gain ground in engineering projects ...

The end goal of database design is to be able to transform a logical data model into an actual physical database. A logical data model is required before you can even begin to design a physical ...

A former Snowflake data scientist who refined multi-billion-dollar forecasts is now building AI models that outperform Claude ...

Many engineering teams still rely on architecture optimized for transactional apps, not for AI systems that mix structured and unstructured data and live event streams. This legacy architecture has ...

Stream Data Centers' Eric Closson explains the importance of grounding data center design and development in reality.

In the search for new drugs, artificial intelligence in the form of diffusion models is being used in drug design. What ...