How to stay alert on top of your anomaly data

  • Automated signal classification: One of the key complications in detecting anomaly in a time series data is the large number of signal types present in that data. It is imperative to build a generic framework that can automatically identify the signal type and classify it correctly. Wrong classification can result in the application of suboptimal models and increase false alarms. Signal classification is extremely important to stay alert on top of your anomaly data. While it is debatable that one neural network model would fit all the signal types identifying the signal type and tailoring the model to that specific signal type enables considerable reduction of false positives. This also enables using the right model for the right signal type and deliver a robust anomaly detection system.
  • Autocorrelation: There are some key KPIs that are tracked business wide so that business leaders can effectively steer the company in the right direction. And all these KPIs have leading indicators. Leading indicators are the levers that managers can use to improve business performance. Leading indicators are easier to influence through managerial actions but harder to measure. Because of the advancements in automated data collection and increasing ability to use artificial intelligence in an automated fashion, today, one can measure these leading indicators and help managers make the right decision. Automatically correlating these indicators and delivering actionable business insights is important to stay alert on top of your anomaly data.
  • Deliver alerts in near real time: When artificially intelligent systems are looking at your data round the clock, it is important that anomalies detected are presented to the decision makers in real time. Easy integration of this artificial intelligence into the messaging platforms that business managers already use is important to remain alert. Smart alerts when delivered by an AI that automatically understands the business context would help in outperforming the competition.

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CrunchMetrics is an automated real-time Anomaly Detection system, that leverages the #AI/ML-based techniques to sift through your data to identify incidents.

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CrunchMetrics

CrunchMetrics

CrunchMetrics is an automated real-time Anomaly Detection system, that leverages the #AI/ML-based techniques to sift through your data to identify incidents.

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