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I’ve been flying multispectral missions for a few years now, and the biggest surprise of these systems is how much processing ...

The momentous transformation putting data managers and their systems at the helm of modern enterprises has only begun. Industry leaders and experts agree that it’s critical for data managers and team ...

Enterprise AI workloads require infrastructure designed for large-scale data processing and distributed computing. Organizations are modernizing AI data center infrastructure with GPU computing, ...

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 ...

In today’s fast-changing data landscape, having a strong data system and advanced analytical tools is key to getting valuable insights and staying ahead of the competition. The data lakehouse ...

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.

AI has become pervasive across enterprises, and the drive is now on to push this potentially powerful intelligence out to the edge and network, where it can deliver insight and operational performance ...

Data center architectures are becoming increasingly customized and heterogeneous, shifting from processors made by a single vendor to a mix of processors and accelerators made by multiple vendors — ...

Rapid advancements in AI are becoming commonplace, driven by large language models (LLMs) that now exceed 1 trillion parameters. While these AI models are revolutionizing many industries, their ...