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 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 method for analyzing a target system that includes obtaining a plurality of characteristics from the target system using a characteristics extractor, wherein the plurality of characteristics is associated with a characteristics model, storing each of the plurality of characteristics in a characteristics store, and analyzing the target system by issuing at least one query to the characteristics store to obtain an analysis result.

Abstract: A method for analyzing a target system that includes obtaining a characteristics model, generating at least one selected from the group consisting of a schema, characteristics store API, and a characteristics extractor, using the characteristics model, obtaining a plurality of characteristics from the target system using characteristics extractor, wherein each of the plurality of characteristics is associated with the characteristics model, storing each of the plurality of characteristics in the characteristics store using the schema, and analyzing the target system by issuing at least one query to the characteristics store to obtain an analysis result.

Abstract: A method for analyzing a target system, that includes obtaining a plurality of characteristics from the target system using a characteristics extractor, wherein the plurality of characteristics is defined in a characteristics model and each of the plurality of characteristics is associated with one of a plurality of artifacts defined in the characteristics model, storing each of the plurality of characteristics in a characteristics store, and analyzing the target system by issuing a query to the characteristics store to obtain an analysis result, wherein the query is used to determine the presence of a first pattern in the target system.

Abstract: A method for analyzing a target system that includes obtaining a characteristics model, loading the characteristics model into a meta model, obtaining a plurality of characteristics from the target system using a characteristics extractor, wherein each of the plurality of characteristics is associated with the characteristics model, storing each of the plurality of characteristics obtained from the target system in a characteristics store, and analyzing the target system by issuing at least one query to the characteristics store to obtain an analysis result, wherein the issuing the at least one query comprises verifying the at least one query using the meta model.

Abstract: A method for analyzing a target system that includes obtaining a plurality of characteristics from the target system using a characteristics extractor, wherein the plurality of characteristics is associated with a characteristics model, storing each of the plurality of characteristics in a characteristics store using a tracking mechanism, and analyzing the target system by issuing a query to the characteristics store to obtain an analysis result, wherein the query uses tracking information associated with the tracking mechanism.

Abstract: The present invention provides a method and apparatus for developing enterprise applications using design patterns. Over time, different types of enterprise applications have been developed and implemented by various software developers for different purposes. The present invention determines the purpose of the software that is needed by the developer and obtains a design pattern to solve the problem that is in accord with the best practices and patterns derived from these implementations. In turn a developer can rely on the present invention as a tool to develop and implement applications in a three-tier or multi-tier computer architecture.

Abstract: A method and system for providing an integrated, enterprise-wide customer relationship management architecture comprises separating services provided by the customer relationship management architecture into tiers, separating hardware and software that host services provided by the customer relationship management architecture into layers, and maintaining systemic qualities in each of the tiers and in each of the layers.

Abstract: The present invention provides a method and apparatus for developing enterprise applications using design patterns. Over time, different types of enterprise applications have been developed and implemented by various software developers for different purposes. The present invention determines the purpose of the software that is needed by the developer and obtains a design pattern to solve the problem that is in accord with the best practices and patterns derived from these implementations. In turn a developer can rely on the present invention as a tool to develop and implement applications in a three-tier or multi-tier computer architecture.