Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for engineering a data analytics platform using machine learning are disclosed. In one aspect, a method includes the actions of receiving data indicating characteristics of data for analysis, analysis techniques to apply to the data, and requirements of users accessing the analyzed data. The actions further include accessing provider information that indicates computing capabilities of a respective data analysis provider, analysis techniques provided by the respective data analysis provider, and real-time data analysis loads of the respective data analysis provider. The actions further include applying the characteristics of the data, the analysis techniques, the requirements of the users, and the provider information, the analysis techniques, and the real-time data analysis loads to a model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for a system to create and employ associative memory maps for analysis of security file and/or logs are disclosed. In one aspect, a method includes the actions of receiving, from an external application, a request for a recommended action; extracting information regarding the entities and relationships between the entities from a data source; constructing an associative memory map from the extracted information; selecting a subgraph from the associative memory map based on a result of employing a vector to search nodes in the associative memory map; identifying the nodes most relevant to the requested recommend action base on a shortest paths of traversal in the selected subgraph of nodes; determining the requested recommended action based on an event identified in the relationships between the identified most relevant nodes; and transmitting the recommended action to the external application.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for engineering a data analytics platform using machine learning are disclosed. In one aspect, a method includes the actions of receiving data indicating characteristics of data for analysis, analysis techniques to apply to the data, and requirements of users accessing the analyzed data. The actions further include accessing provider information that indicates computing capabilities of a respective data analysis provider, analysis techniques provided by the respective data analysis provider, and real-time data analysis loads of the respective data analysis provider. The actions further include applying the characteristics of the data, the analysis techniques, the requirements of the users, and the provider information, the analysis techniques, and the real-time data analysis loads to a model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for engineering a data analytics platform using machine learning are disclosed. In one aspect, a method includes the actions of receiving data indicating characteristics of data for analysis, analysis techniques to apply to the data, and requirements of users accessing the analyzed data. The actions further include accessing provider information that indicates computing capabilities of a respective data analysis provider, analysis techniques provided by the respective data analysis provider, and real-time data analysis loads of the respective data analysis provider. The actions further include applying the characteristics of the data, the analysis techniques, the requirements of the users, and the provider information, the analysis techniques, and the real-time data analysis loads to a model.

Abstract: According to examples, system control may include accessing a plurality of procedures to control an operation of a system to prevent an occurrence of a fault in the system and/or a reduction of an output of the system. A highest ranked procedure may be learned from the plurality of procedures to control the operation of the system to prevent the occurrence of the fault in the system and/or the reduction of the output of the system. Real-time data associated with the system may be accessed. Further, the operation of the system may be controlled by applying the highest ranked procedure to prevent the occurrence of the fault in the system and/or the reduction of the output of the system.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for a system to create and employ associative memory maps for analysis of security file and/or logs are disclosed. In one aspect, a method includes the actions of receiving, from an external application, a request for a recommended action; extracting information regarding the entities and relationships between the entities from a data source; constructing an associative memory map from the extracted information; selecting a subgraph from the associative memory map based on a result of employing a vector to search nodes in the associative memory map; identifying the nodes most relevant to the requested recommend action base on a shortest paths of traversal in the selected subgraph of nodes; determining the requested recommended action based on an event identified in the relationships between the identified most relevant nodes; and transmitting the recommended action to the external application.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for engineering a data analytics platform using machine learning are disclosed. In one aspect, a method includes the actions of receiving data indicating characteristics of data for analysis, analysis techniques to apply to the data, and requirements of users accessing the analyzed data. The actions further include accessing provider information that indicates computing capabilities of a respective data analysis provider, analysis techniques provided by the respective data analysis provider, and real-time data analysis loads of the respective data analysis provider. The actions further include applying the characteristics of the data, the analysis techniques, the requirements of the users, and the provider information, the analysis techniques, and the real-time data analysis loads to a model.

Abstract: According to examples, system control may include accessing a plurality of procedures to control an operation of a system to prevent an occurrence of a fault in the system and/or a reduction of an output of the system. A highest ranked procedure may be learned from the plurality of procedures to control the operation of the system to prevent the occurrence of the fault in the system and/or the reduction of the output of the system. Real-time data associated with the system may be accessed. Further, the operation of the system may be controlled by applying the highest ranked procedure to prevent the occurrence of the fault in the system and/or the reduction of the output of the system.