Abstract: Methods, system, and apparatus for pre-computing data metrics. A method can include receiving, by one or more computers, (i) data from a user including a plurality of data metrics, and (ii) historical data associated with the user; generating, by the one or more computers and based at least on the historical data associated with the user, a forecast for the user using an artificial neural network, the forecast indicating a prediction of future user behaviors; determining, by the one or more computers and based at least on the forecast for the user, a subset of data metrics, from among the plurality of data metrics, that are likely to be used by the user; performing, by the one or more computers, one or more automatic data operations on the subset of data metrics; and providing, by the one or more computers, the processed subset of data metrics for output.

Abstract: A computer-implemented includes a computing system receiving one or more queries. The computing system includes one or more compute nodes that perform computations for determining a response to at least one query. The system stores, in a storage device, domain data that includes at least one of: a dataset, a metric associated with the domain data, a query time, or a usage pattern that is based, in part, on the one or more queries. The method includes the system generating a distribution model based on analysis of the domain data. The distribution model is generated using machine learning logic executed by the system. The method further includes the system using the distribution model to distribute data to the one or more compute nodes. The distributed data is used to determine, within a threshold response time, the response to the at least one query.

Abstract: Methods, system, and apparatus for pre-computing data metrics. A method can include receiving, by one or more computers, (i) data from a user including a plurality of data metrics, and (ii) historical data associated with the user; generating, by the one or more computers and based at least on the historical data associated with the user, a forecast for the user using an artificial neural network, the forecast indicating a prediction of future user behaviors; determining, by the one or more computers and based at least on the forecast for the user, a subset of data metrics, from among the plurality of data metrics, that are likely to be used by the user; performing, by the one or more computers, one or more automatic data operations on the subset of data metrics; and providing, by the one or more computers, the processed subset of data metrics for output.