Sap Se

Andreas Seifried

Kefeng Wang

Dimitrij Raev

Armin Maier

Sabine Stellmacher

Birgitta Bruegel

Dirk Riemer

Kieran Turley

Christian Buschmann

In some implementations, generating enriched data includes actions of receiving a user input comprising object data. A communication with an analytics library is triggered to determine, by using an identification algorithm, a derivation scenario corresponding to the object data, the derivation scenario being stored in a relational database and comprising derivation rules. Modeled information is determined based on the derivation rules. Enriched data is generated based on the object data and by using the modeled information and provided for display.

Automation of master data processes with user-centric management of derivation rules

Data is received that defines a rule mining run including a scope of a search and at least one data source to be searched. In response, the at least one data source is polled to obtain rules responsive to the rule mining run. Each rule can specify one or more actions to take as part of a computer-implemented process when certain conditions are met. A list of rules (i.e., a proposed subset of the obtained rules) can then be generated using at least one machine learning model. The generated list of rule can then be displayed in a graphical user interface. Related apparatus, systems, techniques and articles are also described.

Machine learning-based rule mining algorithm

Growing community of inventors

Hügelsheim, Germany

Andreas Seifried