Inaccurate or overlooked alerts on manufacturing data can be reduced with proper data handling when developing and deploying predictive models. Data analytics, and specifically predictive analytics, ...

Predictive maintenance is emerging as a necessity for aerospace and defense (A&D) systems. By leveraging advanced analytics to monitor equipment health and anticipate failures, operators can ...

Michael Johnson, a decision support data scientist at Bend, Oregon-based St. Charles Health System, has only worked in healthcare for a couple years. Before that, he'd spent most of his career doing ...

The fact that predictive analytics has been a technology practiced by many organizations for years doesn’t necessarily mean it is has had strong roots in the security industry. But as more and more ...

The world is digitizing with increasing speed, and global interconnectivity is rising right along with it, generating abundant data. This data can facilitate more intelligent business decisions and ...

From Reaction to Anticipation: Predictive analytics empower security teams to transition from reactive responses to proactive strategies by leveraging data to anticipate risks before they escalate.

A trucking company’s success and reputation depend directly on its drivers’ safety performance, but it’s not so easy to determine which drivers are most likely to be involved in a crash or incur a ...

In today’s fast-paced industrial landscape, the effective use of data has become a game-changer for facility management. Data-driven insights are not just about improving efficiency. They’re pivotal ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

This is the first article of our three-part series on the state and development of predictive analytics in the legal market. Our second article will look at why predictive analytics' growing accuracy ...

UPMC is on the forefront of using big data to improve patient outcomes. The system started collecting patient data more than 30 years ago and now has a robust platform to support predictive analytics ...