Generating insight from log data traditionally requires writing a search. But that means you need to know which questions to ask. How do you get insight from data you know nothing about? Sumo ...

Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...

In today’s increasingly complex software environments, the automatic detection and analysis of anomalies within system logs has become indispensable. Log anomaly detection encompasses a range of ...

Big data analytics first evolved for use in marketing: by understanding the relationships between customers and actions, better marketing can be developed. Now the practice is being applied to ...

The main advantage of using PCA for anomaly detection, compared to alternative techniques such as a neural autoencoder, is simplicity -- assuming you have a function that computes eigenvalues and ...

Log Anomaly Detection automatically understands and baselines normal patterns in logs, and proactively discovers abnormalities such as new text patterns, meaningful changes in data volumes of ...