Abstract: Non-limiting examples of the present disclosure describe systems and methods for scanning of data for policy compliance. In one example, network data is evaluated to generate one or more groupings. A grouping may be based on file type of the network data. Data identification rules are applied to identify one or more data schemas from file data of a grouping. One or more policy rules that apply to content of the data schema may be determined. At least one file of the file data may be scanned to determine compliance with the one or more policy rules. A report of compliance with the one or more policy rules may be generated based on a result of a file scan. Other examples are also described.

Abstract: A framework for enhanced search is provided to enable the user to contextually search documents, based on specified events. A management framework provides systems for obtaining a user's contextual data and the user's interaction data for which a Context Graph and an Interaction Graph are created, respectively. The user's context data include the various events associated with the user. The user's interaction data include times and locations the user interacted with a particular document, which device was used, the type of interaction, etc. The data from the two graphs are correlated and joined into an event graph. Upon receiving a natural language query from a user, one or more contextual query elements are identified, and the event graph is spanned to identify matching results which are then provided to the requesting user device.

Abstract: Non-limiting examples of the present disclosure describe systems and methods for scanning of data for policy compliance. In one example, network data is evaluated to generate one or more groupings. A grouping may be based on file type of the network data. Data identification rules are applied to identify one or more data schemas from file data of a grouping. One or more policy rules that apply to content of the data schema may be determined. At least one file of the file data may be scanned to determine compliance with the one or more policy rules. A report of compliance with the one or more policy rules may be generated based on a result of a file scan. Other examples are also described.

Abstract: Non-limiting examples of the present disclosure describe systems and methods for scanning of data for policy compliance. In one example, network data is evaluated to generate one or more groupings. A grouping may be based on file type of the network data. Data identification rules are applied to identify one or more data schemas from file data of a grouping. One or more policy rules that apply to content of the data schema may be determined. At least one file of the file data may be scanned to determine compliance with the one or more policy rules. A report of compliance with the one or more policy rules may be generated based on a result of a file scan. Other examples are also described.

Abstract: A framework for enhanced search is provided to enable the user to contextually search documents, based on specified events. A management framework provides systems for obtaining a user's contextual data and the user's interaction data for which a Context Graph and an Interaction Graph are created, respectively. The user's context data include the various events associated with the user. The user's interaction data include times and locations the user interacted with a particular document, which device was used, the type of interaction, etc. The data from the two graphs are correlated and joined into an event graph. Upon receiving a natural language query from a user, one or more contextual query elements are identified, and the event graph is spanned to identify matching results which are then provided to the requesting user device.

Abstract: A framework for enhanced search is provided to enable the user to contextually search documents, based on specified events. A management framework provides systems for obtaining a user's contextual data and the user's interaction data for which a Context Graph and an Interaction Graph are created, respectively. The user's context data include the various events associated with the user. The user's interaction data include times and locations the user interacted with a particular document, which device was used, the type of interaction, etc. The data from the two graphs are correlated and joined into an event graph. Upon receiving a natural language query from a user, one or more contextual query elements are identified, and the event graph is spanned to identify matching results which are then provided to the requesting user device.

Abstract: A framework for enhanced search is provided to enable the user to contextually search documents, based on specified events. A management framework provides systems for obtaining a user's contextual data and the user's interaction data for which a Context Graph and an Interaction Graph are created, respectively. The user's context data include the various events associated with the user. The user's interaction data include times and locations the user interacted with a particular document, which device was used, the type of interaction, etc. The data from the two graphs are correlated and joined into an event graph. Upon receiving a natural language query from a user, one or more contextual query elements are identified, and the event graph is spanned to identify matching results which are then provided to the requesting user device.

Abstract: Non-limiting examples of the present disclosure describe systems and methods for scanning of data for policy compliance. In one example, network data is evaluated to generate one or more groupings. A grouping may be based on file type of the network data. Data identification rules are applied to identify one or more data schemas from file data of a grouping. One or more policy rules that apply to content of the data schema may be determined. At least one file of the file data may be scanned to determine compliance with the one or more policy rules. A report of compliance with the one or more policy rules may be generated based on a result of a file scan. Other examples are also described.