Abstract: Some embodiments are directed to a federated machine learning, including the inference and training. Inference may be done by applying multiple machine learnable models to a mapped record. The mapped record may be obtained by applying a mapping rule to a local record. The mapping rule may generalize or extend data features in the local record.

Abstract: Computer-readable media, methods, and systems are disclosed for storing and analyzing dynamic data within a semantic data store. The dynamic data comprises one or more types of data having a normalized data schema. A dynamic data manager interfaces with the semantic data store to instruct storage of the data. The data may be received through an event service from either of an external data source or an internal data source.

Abstract: Techniques for implementing a digital assistant that provides proactive notifications to users, summarizes data and relevant situations, forecasts/predicts future outcomes, simulates outcomes under different assumptions, generates recommendations to improve observed or assumed situations, and provides explanations for calculated outcomes are disclosed. In some example embodiments, a computer system is configured to detect a data change in one or more data sources, the data change corresponding to a monitored data object, generate a predicted future value for the monitored data object based on the detected data change, identify a deviation between the predicted future value and a planned future value for the monitored data object, determine that the identified deviation is relevant for a specific user at a specific time and in a specific context, and cause a notification corresponding to the deviation to be displayed on a computing device based on the determination that the deviation is relevant.