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Streaming Anomaly Detector For Categorical Data

Streaming Anomaly Detector For Categorical Data

By: thatDot, Inc. Latest Version: v0.9
Linux/Unix
Linux/Unix

Product Overview

Ingest any kind of categorical data through a REST API for a real-time score of its novelty. Immediately find anomalies that are hiding in a high-volume stream of data. Each observation is evaluated for novelty, using context to reducing false positives, and providing an explanation of what makes the observation so unusual.

- Real-time ingestion of streaming or batch data-even combined batch and streaming.
- Categorical data: strings, names, numbers, file paths, etc. No need to convert to numbers.
- Get more than just the anomaly score, get an explanantion why it's anomalous!
- Visualize your dataset to understand common trends and outliers.
- Great for small data of dozens of observatons, all the way up to large data streams in the trillions.
- Run many different anomaly detection streams through the same container, each separated into their own context.
- Deployed as a container for easy integration into applications.
- Choose how sensitive the anomaly detection should be using well-distributed scores.
- Simple operation and management.
- Complete and interactive API documentation is included in the container.

Turn high-volume data into high-value data in real-time with thatDot Streaming Anomaly Detector.

Version

v0.9

Operating System

Linux

Delivery Methods

  • Container

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