Time-series data represents one of the most challenging data types for businesses and data scientists. The data sets are often very big, change continuously, and are time-sensitive by nature. One ...

Tim Keary looks at anomaly detection in this first of a series of articles. Unmanageable datasets have become a problem as organizations are needing to make faster decision in real-time. Machine ...

Anomaly detection is an important AI tool, analyzing time-series data for items that are outside normal operating characteristics for the data source. That makes it an extremely flexible tool ...

IBM accepted the challenge of building ransomware threat detection ... in time to find good data to restore. IBM's approach closes that gap, alerting the user nearly instantly when an anomaly ...

With LLMs, these time-intensive steps can be skipped completely. A second, perhaps more challenging part of current anomaly detection methods ... to be used with time series.

Acceldata’s autonomous data solution unlocks a range of agentic data management use cases, offering a robust foundation for AI agents to take real-time action based on multi-variate anomaly detection.

A fast-growing SIEM (security incident event managment) company called Vigilant is using entropy in an innovative way that warrants a closer look: Its anomaly-detection service identifies ...