TIBCO SOFTWARE INC in Anomaly Detection Software

TIBCO’s anomaly detection solution helps business to fight financial crimes, to reduce the likelihood of frauds in healthcare and banking domain, to monitor equipment functioning and detect the defects of manufacturing.

Features:

• Visual Discovery: Run anomaly detection using discovery by a team of data or business analysts visually monitoring dashboards to find unexpected behavior.
• Supervised Learning: Have knowledgeable people label a set of data points as normal or abnormal. An analyst then uses this labeled data to build machine learning models that can predict anomalies on unlabeled new data.
• Unsupervised Learning: Use unlabeled data to build unsupervised machine learning models that predict new data. Because the model is tailored to fit normal data, anomalous data points stand out.
• Time Series Techniques: Detect anomalies through time series analytics by building models that capture trends, seasonality, and levels in time series data. When new data diverges too much from the model, either an anomaly or a model failure is indicated.
• Autoencoders & Machine Learning: Use the latest machine learning techniques and autoencoders to detect and respond to anomalies in real time. Learn how build a neural network in TensorFlow to predict anomalies from transaction and sensor data feeds on the AWS Marketplace.
• Clustering: Have an analyst attempt to classify each data point into one of many pre-defined clusters, then create a separate cluster for all data points that do not look similar to normal data, a.k.a. the anomalies.