“Emerging applications such as deep neural network demand high off-chip memory bandwidth. However, under stringent physical constraints of chip packages and system boards, it becomes very expensive to ...

An increasingly loud transformation has been reshaping how operations-heavy companies think about data infrastructure. In 2026, I believe it could fundamentally reshape three vendor categories. For ...

Becoming truly data-driven requires more than adopting new tools—it demands clear alignment between business goals and data architecture. The annual Data Summit conference returned to Boston, May 6-7, ...

The so-called modern data stack is getting a facelift and perhaps a complete body makeover. As the point of control shifts from the database management system to the governance layer, we cite three ...

Debate and discussion around data management, analytics, BI and information governance. DeepSeek’s recent developments have ignited significant discussion in the AI community. DeepSeek is very ...

A headless data architecture means no longer having to coordinate multiple copies of data and being free to use whatever processing or query engine is most suitable for the job. Here’s how it works.

Most martech stacks aren’t the real problem. The architecture underneath them is. CMOs and CIOs have spent the last decade building increasingly sophisticated martech ecosystems, answering every new ...

The Software Architecture for Big Data specialization includes a three-course pathway to earn admission to the Online MS in Computer Science (MS-CS). You may complete the three courses below as a ...

The headless data architecture is the formalization of a data access layer at the center of your organization. Encompassing both streams and tables, it provides consistent data access for both ...

As CTO, you know when the current code base is too old: it takes forever to get new features out, response time for end-users is slow, tools are outdated, etc. Yet these issues barely trigger a raised ...