One of the best use of time in improving models is feature engineering. The ecosystem of IoT has many tools that can make it easier. Devices can be geographically connected or hierarchically connected with digital twins, graph frames, and GraphX. This can add features such as showing the degree of contentedness to other failing devices. Windowing can show how the current reading differs over a period of time. Streaming tools such as Kafka can combine different data streams allowing you to combine data from other sources. Machines that are outdoor may be negatively affected by high temperatures or moisture as opposed to machines that are in a climate-controlled building.

In this recipe, we are going to look at enhancing our data by looking at time-series data such as deltas, seasonality, and windowing. One of the most valuable uses of time for a data scientist is feature engineering. Being able to slice the data into meaningful features can...