Abstract: According to one aspect of systems and methods for dynamic recreation of multidimensional analytical data, lost sets of calculation scenarios that provide multidimensional analytical data results after aggregations and transformations of the multidimensional analytical data are recreated in the volatile storage of an in-memory computing engine. A multidimensional analytical data view (MDAV) compiler is triggered to read the MDAV metadata stored in an intermediate buffer in the MDAV compiler. The read MDAV metadata is compiled into a calculation scenario including calculation view metadata. The calculation view metadata is stored in the intermediate buffer. The recreated set of calculation scenarios is deployed on the in-memory computing engine.

Abstract: In an embodiment, the runtime framework is responsible for executing multidimensional analytical metadata in a runtime environment that is determined by the runtime framework. To generate such a runtime framework, the received multidimensional analytical metadata is analyzed to determine a type of an associated calculation pattern. Based upon the type, subsets of the multidimensional analytical metadata and corresponding runtime decision rules are determined. To execute the subsets, executable conditions corresponding to the multidimensional analytical metadata are identified. Based upon the executable conditions, the calculation pattern associated with the multidimensional analytical metadata is executed by executing the associated subsets, and the runtime framework is generated.

Abstract: In an embodiment, the compiler infrastructure allows execution of multidimensional analytical metadata from various databases by providing a generic transformation. A compilation request to execute a multidimensional analytical metadata is received. A type of the compilation request is determined to identify an associated transformation and corresponding transformation rules. Based upon the type of compilation request, a database of an application server is queried to retrieve the corresponding multidimensional analytical metadata. Based upon the identified transformation rules, the multidimensional analytical metadata is transformed into a generic metadata that is executable by any desired engine. An instance of a calculation scenario is generated based upon the transformation. The compiler infrastructure is generated by deploying the instance of the calculation scenario in the desired engine (e.g. in-memory computing engine.

Abstract: The disclosure generally describes computer-implemented methods, computer readable mediums, and distributed systems for providing a message-based interface for exchanging customer requirement information. One method includes receiving, via a message-based interface derived from a common business object model that includes business objects having relationships enabling derivation of message-based interfaces and message packages, a first message for providing a notification of an update of product availability including a first message package hierarchically organized as a product available to promise update notification and fulfillment confirmation message entity and an accompanying set of specific, ordered packages, each including specifically ordered elements.

Abstract: In an embodiment, a runtime callback function is a part of a code that is invoked upon execution of an associated function. To execute the runtime callback function associated with an in-memory computing engine, multidimensional analytical metadata associated with an application server is received and transformed into an in-memory executable metadata, to generate an instance of an in-memory executable calculation scenario. The instance of the in-memory executable calculation scenario is analyzed to determine process callbacks associated with nodes of the in-memory executable calculation scenario. Based upon the determined process callbacks, the runtime callback function is executed by executing a selection callback at the nodes and a transformation callback at part providers associated with the in-memory executable calculation scenario.

Abstract: During an online analytical processing session, actions can be presented for performance on transactional data underlying the session. Actions can be filtered to those valid for a particular context. Other features, such as acquisition of parameters for the actions can be supported.

Abstract: In an embodiment, a runtime callback function is a part of a code that is invoked upon execution of an associated function. To execute the runtime callback function associated with an in-memory computing engine, multidimensional analytical metadata associated with an application server is received and transformed into an in-memory executable metadata, to generate an instance of an in-memory executable calculation scenario. The instance of the in-memory executable calculation scenario is analyzed to determine process callbacks associated with nodes of the in-memory executable calculation scenario. Based upon the determined process callbacks, the runtime callback function is executed by executing a selection callback at the nodes and a transformation callback at part providers associated with the in-memory executable calculation scenario.

Abstract: According to one aspect of systems and methods for dynamic recreation of multidimensional analytical data, lost sets of calculation scenarios that provide multidimensional analytical data results after aggregations and transformations of the multidimensional analytical data are recreated in the volatile storage of an in-memory computing engine. A multidimensional analytical data view (MDAV) compiler is triggered to read the MDAV metadata stored in an intermediate buffer in the MDAV compiler. The read MDAV metadata is compiled into a calculation scenario including calculation view metadata. The calculation view metadata is stored in the intermediate buffer. The recreated set of calculation scenarios is deployed on the in-memory computing engine.

Abstract: In an embodiment, the compiler infrastructure allows execution of multidimensional analytical metadata from various databases by providing a generic transformation. A compilation request to execute a multidimensional analytical metadata is received. A type of the compilation request is determined to identify an associated transformation and corresponding transformation rules. Based upon the type of compilation request, a database of an application server is queried to retrieve the corresponding multidimensional analytical metadata. Based upon the identified transformation rules, the multidimensional analytical metadata is transformed into a generic metadata that is executable by any desired engine. An instance of a calculation scenario is generated based upon the transformation. The compiler infrastructure is generated by deploying the instance of the calculation scenario in the desired engine (e.g. in-memory computing engine.

Abstract: In an embodiment, the runtime framework is responsible for executing multidimensional analytical metadata in a runtime environment that is determined by the runtime framework. To generate such a runtime framework, the received multidimensional analytical metadata is analyzed to determine a type of an associated calculation pattern. Based upon the type, subsets of the multidimensional analytical metadata and corresponding runtime decision rules are determined. To execute the subsets, executable conditions corresponding to the multidimensional analytical metadata are identified. Based upon the executable conditions, the calculation pattern associated with the multidimensional analytical metadata is executed by executing the associated subsets, and the runtime framework is generated.

Abstract: A business object model, which reflects data that is used during a given business transaction, is utilized to generate interfaces. This business object model facilitates commercial transactions by providing consistent interfaces that are suitable for use across industries, across businesses, and across different departments within a business during a business transaction. In some operations, software creates, updates, or otherwise processes information related to a customer requirement business object.

Abstract: The present disclosure relates to methods, systems, and software for processing or otherwise managing scrap information in a business application. For example, the software can instantiate a planning business object using production model data for production activities. The business object data and scrap information may be used to calculate requirements for a production planning model. The calculations may include adding an activity yield to activity scrap and fixed resource scrap to generate a component quantity. The component quantity can be multiplied by a component scrap ratio to generate additional component requirements. The component quantity may be added to the additional component requirements to determine a total quantity.

Abstract: The present disclosure relates to methods, systems, and software for processing or otherwise managing scrap information in a business application. For example, the software can instantiate a planning business object using production model data for production activities. The business object data and scrap information may be used to calculate requirements for a production planning model. The calculations may include adding an activity yield to activity scrap and fixed resource scrap to generate a component quantity. The component quantity can be multiplied by a component scrap ratio to generate additional component requirements. The component quantity may be added to the additional component requirements to determine a total quantity.