Abstract: The present disclosure relates to computer-implemented methods, software, and systems for automated process execution. A neural network including machine learning rules encoded at a rules engine is trained to synthesize input and to generate output for automated execution of processes at a platform landscape of a platform environment. The neural network is configured to convert the received input requesting a process execution into a sequence of executable work units based on the machine learning rules. A first input is received that defines a request in a natural language format. The first input is synthesized based on the machine learning rules at the neural network to generate a first sequence of actions corresponding to the request. The first sequence of actions is generated based on an evaluation of the first input in relation to keywords, parameter names, and parameter values. The generated sequence of actions is provided for automated execution.

Abstract: The present disclosure involves analyzing data relevancy of particular fields within one or more databases in a big data system. In one example method, an interaction with at least one of a plurality of monitored data sources is identified, wherein the identified interactions is associated with a particular field of a database table of one of the monitored data sources. A set of data associated with the interaction is determined which includes an identification of each field associated with the identified interaction and a count of a number of interactions associated with each particular field. A relevancy index table is updated to include the determined set of data, wherein each identified field is associated with a row in the index table. At least one relevancy rule is identified for the relevancy index table and is executed to generate a relevancy score for at least one of the fields.

Abstract: The present disclosure involves analyzing data relevancy of particular fields within one or more databases in a big data system. In one example method, an interaction with at least one of a plurality of monitored data sources is identified, wherein the identified interactions is associated with a particular field of a database table of one of the monitored data sources. A set of data associated with the interaction is determined which includes an identification of each field associated with the identified interaction and a count of a number of interactions associated with each particular field. A relevancy index table is updated to include the determined set of data, wherein each identified field is associated with a row in the index table. At least one relevancy rule is identified for the relevancy index table and is executed to generate a relevancy score for at least one of the fields.

Abstract: A method, implemented at least in part by a computing device, for software upgrade analysis includes receiving a selection of at least one object class of a plurality of available object classes. One or more application programming interface (API) calls may be retrieved from a plurality of API calls based on the received selection. A test definition may be generated based at least in part on the one or more API calls. A first test may be executed by using the one or more API calls in the test definition within a software environment. The first test is run on the software environment prior to upgrading the environment. Subsequent to upgrading the environment, a second test is executed by using the one or more API calls within the upgraded software environment. A software upgrade report is generated based on a comparison of test results from the first and second tests.

Abstract: A method, implemented at least in part by a computing device, for software upgrade analysis includes receiving a selection of at least one object class of a plurality of available object classes. One or more application programming interface (API) calls may be retrieved from a plurality of API calls based on the received selection. A test definition may be generated based at least in part on the one or more API calls. A first test may be executed by using the one or more API calls in the test definition within a software environment. The first test is run on the software environment prior to upgrading the environment. Subsequent to upgrading the environment, a second test is executed by using the one or more API calls within the upgraded software environment. A software upgrade report is generated based on a comparison of test results from the first and second tests.