Anomaly detection is the process of identifying data points, entities or events that fall outside the normal range. An anomaly is anything that deviates from what is standard or expected. Humans and ...

See how anomaly detection catches gray failures — silent, partial outages that slip past green dashboards — in minutes, and ...

Anomaly detection plays an increasingly important role in data and storage management, as admins seek to improve security of systems. Managing data and storage is more complex because of distributed ...

Unlike pattern-matching, which is about spotting connections and relationships, when we detect anomalies we are seeing disconnections—things that do not fit together. Anomalies get much less attention ...

Many data teams focus solely on the "accuracy" of their anomaly detection models. They are satisfied with listing numbers ...

Anomaly detection is the process of identifying events or patterns that differ from expected behavior. Anomaly detection can range from simple outlier detection to complex machine learning algorithms ...

Internet of Things (IoT) devices have become extremely popular in homes and workplaces. However, their abundant and rising usage also makes these products tempting targets for cybercriminals. Anomaly ...

I am the VP of Engineering at Apriorit, a software development company that provides engineering services globally to tech companies. Social media is an indispensable tool for businesses to engage ...

Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...