The challenges encountered with multivariate time series data
You can find both single-event and event range anomalies across multivariate time series data. However, the multivariate nature of your problems also gives you more context, and you could start seeing some anomalies because the relationships between the different signals start to diverge from their normal conditions. Let's dive deeper into the following figure (also Figure 8.2):
This signal is actually part of a multivariate dataset with 51 sensors collecting data from a pump in a water treatment facility. Let's plot this same signal along with a second one, as follows:
As you can see, when adding this contextual information, you might not label the highlighted area as an anomaly, as this might be the normal behavior of signal 1 (the one at the bottom), when signal 2...