Abstract: User information for a particular user is accessed. Expert information for experts and training that is available in an organization of the particular user is accessed. One or more pattern matches between the user information and the expert information are determined. One or more expert recommendations are generated based on the one or more pattern matches and provided.

Abstract: User-generated input is received that includes a sequence of words associated with initiation of a computer-implemented event. Thereafter, such input is parsed using at least one natural language processing (NLP) model. This parsed input is then used by a machine learning model to determine a suggested template having a plurality of fields for initiating the event. The template can then be presented in a graphical user interface. Related apparatus, systems, techniques and articles are also described.

Abstract: A method may include receiving a search phrase including a first word. In response to receiving the search phrase, a database may be queried to retrieve an item description matching the search phrase. The first item description may match the search phrase by including a second word that matches the first word in the search phrase. A semantic role for the first word included in the search phrase may be determined based on a semantic role of the second word included in the item description. An analytics result associated with the search phrase may be generated based on the semantic role of first word included in the search phrase. Related systems and articles of manufacture, including computer program products, are also provided.

Abstract: A method, a system, and a computer program product for executing a query. A query associated with a calculation scenario defining a data flow model that includes one or more calculation nodes is received. Each calculation node corresponds to an operation being performed on one or more database tables stored at a database. The calculation nodes include one or more nodes specifying a window function operation. The window function operation including one or more first attributes and one or more second attributes. A calculation engine executes the calculation scenario by performing, using at least one of the first and second attributes, the window function operation on the database tables stored at the database. Based on the execution of the calculation scenario, a result data set is generated and provided by the database server to the application server.

Abstract: A method and system including receiving a set of integration steps to transfer data between a first application and a second application, wherein the set of integration steps includes execution of at least one component; transmitting the received set of integration steps to a blueprint generator; converting, at the blueprint generator, the received set of integration steps to a binary runtime executable code; inserting at least two input/output interceptors into the binary runtime executable code; receiving the binary runtime executable code at a runtime component; executing the received binary runtime executable code at the runtime component using data, in a case that execution of the at least one component is complete, an output of the executed at least one component is saved; in a case that execution of the at least one component is incomplete: receiving an update to the data; re-generating, at the blueprint generator, the binary runtime executable code for one or more an unexecuted integration steps; and

Abstract: Various embodiments for providing a user interface test and validation system are described herein. An embodiment operates by determining user interface (UI) settings and metadata, and fetching data corresponding to the metadata. A plurality of test procedures corresponding to the UI element are identified. A plurality of states to be present in a rendering of the UI element based on the plurality of test procedures, the metadata, and the data are identified. A rendering of the UI element is validated against the plurality of states. A test report is provided based on the validating.

Abstract: Systems and methods are provided for receiving, from a computing device, a selection of a template for a custom microservice and configuration parameters for the custom microservice, generating the template for the custom microservice using the configuration parameters, the template for the custom microservice comprising defined interfaces for accessing core microservices, defined integration points for integration with a system providing the core microservices, and stubs for custom components for the custom microservice, and providing the template for the custom microservice to the computing device, wherein custom components for the custom microservice are added to the template via the computing device using the stubs for the custom components. The systems and methods further provide for registering the custom microservice to be exposed to and accessed by a tenant with authorization to access the custom microservice along with the core microservices.

Abstract: A system and method of managing highly-volatile statistics of a multi-threaded application environment. The statistics are represented by one or more statistics objects. Each statistics object of the one or more statistics objects is prefixed with an object header having a version counter with an initial version count of zero. Each statistics object is associated with a statistics class instance, each statistics class instance being associated with an associative registry that is configured to allocate smallest possible objects of a size equal to or greater than to that of the statistics objects, the registry segmenting the statistics objects according to a size class. Each allocated statistics object is constructed in the object frame after the object header. Then, the object header of each allocated statistics object is initialized. Once allocated, objects can be deallocated.

Abstract: Disclosed herein are system, method, and computer program product embodiments for performing fair prefetching. An embodiment operates by splitting a data vector into a first subrange and a second subrange. The embodiment performs a first chance prefetch operation on the first subrange based on a fixed number of pages, thereby loading a set of pages of the first subrange into a main memory. The embodiment performs the first chance prefetch operation on the second subrange based on the fixed number of pages, thereby loading a first set of pages of the second subrange into the main memory. The embodiment performs a second chance prefetch operation on the second subrange based on the performing the first chance prefetch operation on the second subrange, thereby loading a second set of pages of the second subrange into the main memory. The embodiment then executes the query.

Abstract: Systems and processes for managing service orders for service bundles are provided herein. An account assignment object may be created in a service order database corresponding to a main item and a plurality of subitems may be linked to the account assignment object, the main item representing the service bundle and the plurality of subitems offered collectively as the service bundle. The main item and subitems may be part of a hierarchy structure in which the main item is at a higher level than the subitems. A value of the main item may be set corresponding to a price of the service bundle. Follow-up processing may be automatically performed and a billing document may be generated for the service order using the account assignment object. Entries for each of the main item and the plurality of subitems for the order may be displayed in a hierarchical line item view.

Abstract: Techniques and solutions are described for converting data models between formats, such as between a conceptual data model and a physical data model for a database system, or between a conceptual data model and artefacts to be implemented in the database system. The conceptual data model is annotated with annotations that allow the physical data model or database artefacts to be automatically generated from the conceptual data model. The annotations can reflect relationships between entity types in the physical data model, such as inheritance relationships, header/item relationships, or one-to-one cardinality relationships. Annotations can also indicate attributes that should be added to entity types in the conceptual data model, such as attributes for versioning or data governance, that may not be used in the conceptual data model. Annotations can be used to determine how entity types in the conceptual data model will be denormalized in the physical data model.

Abstract: Various examples are directed to systems and methods for searching application rules. A rule management system may access application rule data describing a first application rule and generate a first textual summary of the first application rule. The rule management system may encode the first textual summary to generate a first rule vector. The rule management system may receive a application rule query. The application rule query may include a query description. The rule management system may encode the query description to generate a first query vector and select the first application rule as responsive to the application rule query using the first rule vector and the first query vector. The rule management system may return the first application rule in response to the application rule query.

Abstract: A computer-implemented method is disclosed. In a deployed enterprise resource planning system implementing a first fiscal year variant, the method can configure a second fiscal year variant that is different from the first fiscal year variant. The method can identify a list of target tables in the deployed enterprise resource planning system that contains the first fiscal year variant. The method can convert the first fiscal year variant to the second fiscal year variant in the list of target tables. In certain embodiments, the method can replace the first fiscal year variant with the second fiscal year variant in a reference framework interfacing with the list of target tables.

Abstract: The disclosure relates to a computed-implemented method, a computer program, and a computer system for selectively verifying personal data. The method comprises receiving, by an identity application of a client device, personal data of a user. The method further comprises computing, via a cryptographic hash function, one or more cryptographic hashes from elements of the personal data. The method further comprises storing the cryptographic hashes, an internal identifier and a timestamp as an entry in a distributed database. The internal identifier is unique within the distributed database. The method further comprises receiving a user request from the user. The method further comprises selecting one or more of the elements of personal data for verification. The method further comprises requesting verification of the selected elements of personal data. The method further comprises determining an authorization indication in response to the verification request.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receiving a request for a map visualization that includes geo-enriched data comprising a set of shapes. In response to the request, the program further generates a query for the geo-enriched data. The program also sends the query to a geo-enriching data system. The program further receives the geo-enriched data from the geo-enriching data system. The program also generates the map visualization that includes the set of shapes.

Abstract: A user interface may be generated to receive inputs for constructing a data processing pipeline that includes an orchestrator node, a preparator node, and an executor node. The preparator node may generate a training dataset and a validation dataset for a machine learning model. The executor node may execute machine learning trials by applying, to the training dataset and the validation dataset, machine learning models having different sets of trial parameters. The orchestrator node may identify, based on a result of the machine learning trials, an optimal machine learning model for performing a task. The data processing pipeline may be adapted dynamically based on the input dataset and/or computational resource budget. The optimal machine learning model for performing the task may be generated by executing, based on the graph, the data processing pipeline the orchestrator node, the preparator node, and the executor node.

Abstract: Integrating proxies within an integration environment can be implemented as a computer-implemented method. Deployment of integration content to integrate with a destination system having a destination system configuration is determined. The integration content has a destination configuration that is incompatible with the destination system configuration. In response to determining that the integration content has the destination configuration that is incompatible with the destination system configuration, the integration content is dynamically modified to integrate with a black box integration content having a black box source address and having a destination configuration as the destination system configuration. The modified integration content is integrated to the destination system through the generated black box integration content.

Abstract: A system includes a processor that executes instructions stored in a memory to implement an auto-solution advisor on a server. The auto-solution advisor receives a current help request describing in lay language text a problem with a computer application or computing device, and determines whether the current help request is textually similar to a previous help request for a previous problem. Based on the similarity of the current help request to the previous help request, the auto-solution advisor assigns a known solution for the previous problem as the suggested solution for the current help request.

Abstract: Methods and apparatus are disclosed for serializing software objects for loading onto a cloud-hosted tenant, or for other serialized operations. Nodes and edges of a directed graph represent respective software objects and the dependencies among the software objects. A search for strongly connected components reveals cyclic dependencies. Each strongly connected component can be replaced by a contracted node to obtain a condensation of the original directed graph. A topological ordering can be determined for the condensation, and the software objects can be processed or loaded according to the topological ordering. Such ordering provides that software objects of a strongly connected component are processed consecutively while, for all other dependencies, a prerequisite object is processed (loaded) before its dependent object(s). Examples of SAP Analytics Cloud and Data Warehouse Cloud are provided. Exemplary, push and pull loading procedures, topological ordering, and validation are disclosed.

Abstract: A method of tenant user management in cloud database operation can be implemented. The method can receive an original job request from a user for a database service, wherein the original job request can include a login credential of the user. The method can authenticate the login credential of the user by a scheduler, verify the user has privileges for the original job request by the scheduler, create a modified job request from the original job request by the scheduler based on a predefined role corresponding to the privileges of the user, send the modified job request from the scheduler to a database service platform, and allocate an instance of database service to the user in response to the modified job request.