Modern businesses have become more data-dependent and they use data for various purposes. Finding out anomalies in big data is humanly impossible, so a tool to do the same would be cost-effective. With digital transformation, companies can ensure that their capital invested, manpower and other resources are utilized efficiently. Anomaly detection (outlier analysis) is a technique of finding out unusual patterns or errors that deviates from normal data behavior. The incident management module helps in alerting the respective person about the anomaly detected.
Application of Anomaly Detection
- Fraud detection
- Social media monitoring
- Medical monitoring
- Machine performance
In the process of building software, errors may occur while coding. If the mistake isn’t found right away, it will be a herculean task to pinpoint where it went wrong in the later stages and it takes a lot of time and effort to rectify and revise.
Our platform helps in detecting anomalies from application logs. The platform sends a notification when it finds log entries that are rare and alerts the support team even before the incident happens. This saves time and effort by solving the issue even before the end-user raises a ticket for the same. The early diagnosis of error conditions saves time and influences business decisions.
- Early diagnosis with better accuracy
- Detects anomalies and predicts event occurrences from system logs at runtime
- Scalable and configurable admin dashboard
- Effort and time of error identification can be utilized for other advancements