Time Series Anomaly Detection; Detection of anomalous drops with limited features and sparse examples in noisy highly periodic data

Understand

Google uses continuous streams of data from industry partners in order to deliver accurate results to users.

• Unexpected drops in traffic can be an indication of an underlying issue and may be an early warning that remedial action may be necessary.
• Detecting such drops is non-trivial because streams are variable and noisy, with roughly regular spikes (in many different shapes) in traffic data.
• We investigated the question of whether or not we can predict anomalies in these data streams.