Tighter integration of automatic test equipment (ATE) into semiconductor manufacturing, so that data from one process can be seamlessly leveraged by another, holds significant promise to boost ...

In this special technology white paper, Why Machine Intelligence is the Key to Solving the Data Integration Problem for the IIoT, you’ll uncover the reasons why machine intelligence is the key to ...

To examine enabling technologies and best practices for adopting a data fabric architecture, experts from TimeXtender and Acceldata joined DBTA's webinar, Moving to a Data Fabric: Key Challenges and ...

Bit Stew Systems, developer of a platform that solves the data integration challenge in the Industrial Internet of Things (IIoT), today announced the launch of version 10 of their MIx Core™ platform, ...

In the ever-evolving landscape of supercomputing, new cross-field integrations, such as artificial intelligence, are forcing innovations across the stack — from storage to networking and compute. The ...

Data integration is a statistical modeling approach that incorporates multiple data sources within a unified analytical framework. Macrosystems ecology – the study of ecological phenomena at broad ...

As power companies build hybrid projects combining solar, wind, battery storage and hydrogen assets, they face the challenge of integrating dozens of different control systems and data types from ...

More than 400 million terabytes of digital data are generated every day, including data created, captured, copied and consumed worldwide. By 2028 the total amount of global digital data is forecast to ...

Kinil Doshi is a senior VP at Citibank and a fintech expert in banking compliance and risk management with two decades of experience. Advances in technology have played a crucial and welcomed role ...

With artificial intelligence reshaping risk management, the quality of data feeding these sophisticated models has never been more crucial. Why? Because AI risk models offer unprecedented capabilities ...