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

December 30, 2018 / insideBIGDATA

You have the data. How do you make sense of it? The Internet of Things (IoT) is no longer a fancy marketing term thrown in to close a critical deal – it’s all around us. In the digital age, everyone has smart, connected machines, which are happily and continuously reeling in their data – by the truckload. In fact, according to Forbes, the global IoT market is estimated to hit US$457 billion by 2020. The question is, what do you do with all this data? Granted, every self-respecting, agile and competitive organization in today’s day and age has already realized the importance of gathering their data. They also know that they need to analyze said data to identify abnormalities, or what we call anomalies. Which is great. But how do you go about selecting the anomaly detection technique that works best for you? Let’s first take a step back and run through each of them to get a better understanding.