As you explore how to create new opportunities with AI, it’s crucial to first take a close look at your data architecture.

The success of real-time digital systems comes from optimizing processing for the most important tasks rather than speeding up overall execution.

The biggest challenge to AI initiatives is the data they rely on. More powerful computing and higher-capacity storage at lower cost has created a flood of information, and not all of it is clean. It ...

In the evolving landscape of data storage, computational storage devices (CSDs) are revolutionizing how we process and store data. By embedding processing capabilities within storage units, these ...

Did you know that 90% of the world’s data has been created in the last two years alone? With such an overwhelming influx of information, businesses are constantly seeking efficient ways to manage and ...

Real-time data processing is the handling of data as it arrives, so it is available for use almost as immediately as it is created and collected. This term is most often used in the context of a ...

DataPelago says its new technology provides a data processing boost for advanced analytics and AI applications that require huge volumes of complex, structured and unstructured data. Startup ...

The FDAP stack brings enhanced data processing capabilities to large volumes of data. Apache Arrow acts as a cross-language development platform for in-memory data, facilitating efficient data ...

In December, reports suggested that Microsoft had acquired Fungible, a startup fabricating a type of data center hardware known as a data processing unit (DPU), for around $190 million. Today, ...