Abstract: A system receives a plurality of data streams, including a plurality of data points, associated with properties of a device. The system generates, for each data stream, a data set that includes at least a specified number of data points over a prior time period. The system identifies a first data stream that represents a property to be predicted for a future time period. The system generates a joined data set that includes a subset of the data sets not including a first data set of the first data stream. The joined data set and the first data set are inputted into a trained machine learning model, trained to output a predicted value of the first property for the future time period. The predicted value of the first property indicates an anomaly, and a resolution action for preventing the anomaly from occurring at the future time period is identified.