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Detecting Anomalies in Time Series Data: Deciphering the Noise and Zoning in on the Signals

In this contributed article, Pratap Dangeti, Principal Data Scientist at Subex, discusses how anomaly detection in industrial data is by no means a simple process given the scale at which it needs to happen, and also the highly dynamic nature of business in today’s world. However, it’s still imperative to get it right, as no digital business can hope to stay relevant and competitive in an increasingly tough economy without the power of meaningful data analytics to back its growth.