Abstract: Methods and apparatus are disclosed for efficient factor analysis of a large population of data records, using factors that are categorical variables. Computation is balanced between extracting key factors by training a machine learning classifier on a reduced sample of data records, for computational efficiency, and scoring the categorical values of the key factors on the entire population, for accuracy of results. A joint factor is constructed by combining all proposed root factors, and the sample is generated by stratified sampling on the joint factor. The key factors are selected from candidate factors which can be combinations of the root factors. Original variables of a dataset, whether categorical or not, can be binned to obtain new categorical factors. Variations and user interfaces are also disclosed.

Abstract: Methods and apparatus are disclosed for efficient factor analysis of a large population of data records, using factors that are categorical variables. Computation is balanced between extracting key factors by training a machine learning classifier on a reduced sample of data records, for computational efficiency, and scoring the categorical values of the key factors on the entire population, for accuracy of results. A joint factor is constructed by combining all proposed root factors, and the sample is generated by stratified sampling on the joint factor. The key factors are selected from candidate factors which can be combinations of the root factors. Original variables of a dataset, whether categorical or not, can be binned to obtain new categorical factors. Variations and user interfaces are also disclosed.

Abstract: Raw data is received that characterizes each of a plurality of transactions. The data can be received, for example, via an adapter coupled to at least one data source. At least one first table is populated using the raw data according to a normalized data model. At least one second table is then populated, by applying a key figure data model to transform and enrich the at least one first table, such that it is optimized for data analysis operations. The at least one second table can include a subset of data stored in the at least one first table and additional enrichment data. At least one data analysis operation can later be initiated on the data populated in at least one second table to characterize one or more aspects of the transactions. Data can be provided that characterizes the initiated at least one data operation.

Abstract: Raw data is received that characterizes each of a plurality of transactions. The data can be received, for example, via an adapter coupled to at least one data source. At least one first table is populated using the raw data according to a normalized data model. At least one second table is then populated, by applying a key figure data model to transform and enrich the at least one first table, such that it is optimized for data analysis operations. The at least one second table can include a subset of data stored in the at least one first table and additional enrichment data. At least one data analysis operation can later be initiated on the data populated in at least one second table to characterize one or more aspects of the transactions. Data can be provided that characterizes the initiated at least one data operation.

Abstract: Runtime performance of report generation and other response to query requests can be improve using a report analyzer that can parse the query request and distribute the necessary analytical task among two or more analytical engines of varying levels of complexity.

Abstract: A multidimensional analytical view (MDAV) type can be supported for an in-memory, columnar database, and MDAV calculations can be integrated into the database. Such an MDAV can be combined with other MDAV types as desired. Calculations typically performed at the application layer can be pushed down to the database. A model-based approach allows generation of a calculation plan, and calculations can be performed directly on the database.

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: According to some embodiments, a database may store business information and meta-data associated with the business information. A processor coupled to the database may generate: (i) a first report associated with at least some of the business information, wherein the first report is to be displayed in a first area of a display of a remote touch sensitive device, and (ii) a second report associated with at least some of the business information, wherein the second report is to be displayed in a second area of the touch sensitive device. A communication port coupled to the processor may transmit the first and second reports and receive a destination location from the touch sensitive device, wherein the destination location is associated with a movement of a selected report element of the first report.

Abstract: According to some embodiments, a system, method, means, and/or computer program code are provided to facilitate a display of information on a client device. For example, a server may retrieve first enterprise data from an enterprise database and store the first enterprise data into a first client based cache at the server, the first client based cache being associated with a first user. Similarly, the server may retrieve second enterprise data from the enterprise database and store the second enterprise data into a second client based cache at the server, the second client based cache being associated with a second user. Subsequent to the storing of the first enterprise data, the server may receive a display request from a first client device associated with the first user and transmit the first enterprise data to the first client device.

Abstract: A system may include reception of an instruction to add an extension field to a node of a business object object model, identification of at least one multi-dimensional analytical view object model including a reference field referring to the node of the business object object model, determination of at least one report associated with the determined at least one multi-dimensional analytical view object model, reception of a selection of one of the at least one report, extension of the one of the at least one multi-dimensional analytical view object model associated with the report based on the extension field, and extension of the selected report based on the extension field.

Abstract: Runtime performance of report generation and other response to query requests can be improve using a report analyzer that can parse the query request and distribute the necessary analytical task among two or more analytical engines of varying levels of complexity.

Abstract: A multidimensional analytical view (MDAV) type can be supported for an in-memory, columnar database, and MDAV calculations can be integrated into the database. Such an MDAV can be combined with other MDAV types as desired. Calculations typically performed at the application layer can be pushed down to the database. A model-based approach allows generation of a calculation plan, and calculations can be performed directly on the database.

Abstract: A system may include reception of the first instruction, execution of the business process in a first software work process, reception, during execution of the business process, of an indication of a business object process associated with the business process, determination of progress information associated with the business process based on the indication of the business object process, and storage of the progress information within a memory. Aspects may further include reception, at a second work process, of a request from the client application for progress information, retrieval of the progress information from the shared memory and provision of the progress information to the client application.

Abstract: Embodiments may provide a system and method for providing aggregated data to a client from a plurality of data sources. The method may include maintaining data in a data repository, maintaining a first analytical view having a first set of metadata including a first set of attributes, and maintaining a second analytical view having a second set of metadata including a second set of attributes. The method may include receiving a request for information, the request specifying the first analytical view and the second analytical view. The information from the data repository in accordance with the first set of metadata and the second set of metadata may be extracted and the extracted information may be analyzed to generate aggregated data in accordance with the first set of metadata and the second set of metadata. The aggregated data may be provided to the client.

Abstract: A system for accessing analytical data for external use may include a database storing a first data set and a second data set. The first data set and the second data set may include analytical data. A first access layer may provide access to a first data set from the database and a second access layer may provide access to a second data set from the database. A first application programming interface may provide functions to access the first access layer and a second application programming interface may provide functions to access the second access layer. The first application programming interface may be configured to receive a request via the first access layer to access the first data set from the database and the second application programming interface may be configured to receive a request via the second access layer.

Abstract: A system may include reception of a request from a user to start a report associated with a node of a business object object model, where the node of the business object object model is associated with an access control list associating instances of the node with at least one access context restriction, determination of a first access context restriction associated with the user, retrieval of the at least one instance of the node based on the first access context restriction and on the access control list associated with the node, and presentation of an instance of the report to the user, the instance of the report populated with the at least one instance.

Abstract: According to an example implementation, a method may include receiving metadata from a first external data source, the metadata indicating types of fields stored by the first external data source, generating a signal configured to cause a display to generate a metadata graphical user interface (GUI) presenting the types of fields to a user, receiving a signal indicating a selection of at least a first type of field and a second type of field by the user via the metadata GUI, receiving data from the first external data source, and converting a type of at least a first field of the received data into the first type and a type of at least a second field of the received data into the second type.

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 a computing system, key figures are made available for selection in an electronic data repository. The key figures are selectable by any of a plurality of distributed systems. A request for a key figure value calculation is received from one of the distributed systems, and request is made for an identifier of one of the key figures. Data is accessed for the key figure from at least one electronic data source, and the data is used to compute a value for the key figure. The value for the key figure is stored in an electronic storage location.

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.