Abstract: Certain example embodiments relate to techniques for real-time generation of temporal comparative and superlative analytics. For instance, certain example embodiments analyze real-time events to generate building blocks that are assemblable into natural language question templates. These natural language question templates, which may include natural language phrases and templated fields, may be comparative or superlative in nature. User selectable options or parameters may be inserted in place of the templated fields, and complete questions, including user selections and the comparative or superlative, may be translated into a formal query language for execution on the real-time data source. In certain example embodiments, a GUI may enable users to build pre-constructed questions with selectable parameters.

Abstract: A computer system, a computer-readable non-transitory medium, and/or a computer-implemented method generates analytics applicable to data of an undetermined structure and type. A processor device receives data formatted in an undetermined structure. The processor device discovers, in a cross filter model processor, dynamically in response to receiving the data in the undetermined structure, a structure and a data type of the data which was received in the undetermined structure. The processor device determines, in response to the structure and the data type of the data discovered by the cross filter model processor, which of a plurality of analytic queries are applicable to the data.

Abstract: Certain example embodiments relate to techniques for real-time generation of temporal comparative and superlative analytics. For instance, certain example embodiments analyze real-time events to generate building blocks that are assemblable into natural language question templates. These natural language question templates, which may include natural language phrases and templated fields, may be comparative or superlative in nature. User selectable options or parameters may be inserted in place of the templated fields, and complete questions, including user selections and the comparative or superlative, may be translated into a formal query language for execution on the real-time data source. In certain example embodiments, a GUI may enable users to build pre-constructed questions with selectable parameters.

Abstract: A computer system includes a display interface; a user input device interface; and a processor cooperatively operable with the display and user input device interfaces. The processor provides a browser user interface that interacts with a user to selectively indicate (i) content fields displayed in the source user interface from which information is to be sent and (ii) content fields displayed in the destination user interface which are to receive the information from the source content fields. The computer system stores an indication of the destination app registered for the topic together with an indication of the selected destination content fields which are to receive the information from the selected content fields of the source app. The source app and destination app do not publish/subscribe to each other. An intermediary brokers messages from the source app, maps the data, and sends on to the destination app.

Abstract: A system for continuous analytics comprises an in-memory storage and a processor. The processor receives a query that indicates an analytic function to be performed on a combination of static data and real-time data. The processor loads the in-memory storage from a first source external to the processor with data that was stored as the static data. At the same time that the in-memory storage is already loaded with the static data, the processor continuously receives ephemeral real-time data as it is being generated by a second source external to the processor. The processor runs the analytic function from the query against the in-memory storage loaded with the first data and the real-time data that is being continuously received, in combination, to produce a result of the analytic function. The result is stored and time-stamped in the in-memory storage as an analytic cube.

Abstract: A common dashboard framework includes dashboard configuration data that specifies a configuration of dashboard content and a user interface configuration for a mashup dashboard. The dashboard content and the user interface configuration control visual and behavioral characteristics of the mashup dashboard that are independent of mashup data, and that are controlled to provide a same look and feel for different mashups. Different dashboard configuration data provides a different look and feel for the different mashups. The dashboard module data specifies whether the mashup dashboard is associated with a group of mashup dashboards. If so, the mashup dashboard further reflects the pre-defined group of mashup dashboards. The apparatus assembles the mashup dashboard based on the dashboard configuration data, the dashboard module data, and a workspace for the mashup data.

Abstract: A system for continuous analytics comprises an in-memory storage and a processor. The processor receives a query that indicates an analytic function to be performed on a combination of static data and real-time data. The processor loads the in-memory storage from a first source external to the processor with data that was stored as the static data. At the same time that the in-memory storage is already loaded with the static data, the processor continuously receives ephemeral real-time data as it is being generated by a second source external to the processor. The processor runs the analytic function from the query against the in-memory storage loaded with the first data and the real-time data that is being continuously received, in combination, to produce a result of the analytic function. The result is stored and time-stamped in the in-memory storage as an analytic cube.

Abstract: A computer system, a computer-readable non-transitory medium, and/or a computer-implemented method generates analytics applicable to data of an undetermined structure and type. A processor device receives data formatted in an undetermined structure. The processor device discovers, in a cross filter model processor, dynamically in response to receiving the data in the undetermined structure, a structure and a data type of the data which was received in the undetermined structure. The processor device determines, in response to the structure and the data type of the data discovered by the cross filter model processor, which of a plurality of analytic queries are applicable to the data.

Abstract: A computer system includes a mashup section that provides a mashup that performs an action on a resource. An attribute identification section identifies an attribute of a user running the mashup. An access control section provides access control. The mashup is associated to a permission artifact. The permission artifact specifies a principal and whether to permit the principal to take the action on the resource. The access control is triggered only when the mashup attempts to perform the action on the resource, and checks whether the attribute of the user running the mashup is predefined as belonging to the principal specified in the permission artifact associated to the mashup, and then permits the action on the resource only when the attribute belongs to the principal. Plural users with the same attribute belong to the principal when the same attribute is defined as belonging to the principal.