Anomaly Detection

Anomaly detection has become imperative in business

What is an anomaly?

Determining what's an anomaly is not an easy task neither for humans or machines.

Why companies need anomaly detection?

We have already learnt

Types of anomaly detectors

Univariate Time Series

Multivarite

A "transform" are machine learning models that can learn how to tranforms raw unstructured data from

View all transforms

Contextual Anomalies

A "destination" is a destination for events. Each sink's interacting with. For example, the [socket sink][docs.sinks.÷] will design and transmission method is dictated by the downstream service it is stream individual events, while the aws_s3 sink will buffer and flush data.

Dashboards

All items passing through BrainRex anomaly detector can be easily

View Kibana Dashboards

Search-Based Engine

A "pipeline" is the end result of connecting sources, transforms, and sinks. You can see a full example of a pipeline in the configuration section.

View configuration

Out of the box solutions

View solutions