thatDot’s real-time Novelty Detector for categorical has updated its data exploration and data transformation capabilities.

ThatDot's platform is a central hub for developers and data engineers, offering insights into real-time data streaming, event processing, and analytics. Through articles, tutorials, and case studies, ThatDot offers insights into building scalable and resilient event-driven architectures. Developers can learn about stream processing frameworks, distributed systems, and anomaly detection techniques to process and analyze large-scale data streams effectively.

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thatDot has added data exploration capabilities and data transformation functions to their Novelty Detector for Categorical data. The new features include Data Distribution Plots for visualizing score distribution and Observation Detail Visualizations for understanding the root cause of a score. Additionally, users can now define data transformations using javascript to experiment and refine their anomaly detection efforts.

New to Quine's Novelty Detector: Visualizations and Enhancements