Abstract: Embodiments of the present invention relate to a system and method for analyzing processes. Specifically, embodiments of the present invention relate to identifying a node of a process that is potentially affected by an affected resource using information relating to a link between the node and the affected resource, the process having a related process instance that has an execution stage, and applying an interval prediction model corresponding to the execution stage of the process instance and the node, the interval prediction model determining a probability that the process instance will reach the node before a designated occurrence.

Abstract: A system and method is disclosed for generating process simulation parameters. The method discloses: identifying an execution process; partitioning the process in accordance with a partitioning rule; and generating simulation parameters for each partition. The system discloses various means for effecting the method.

Abstract: Embodiments in accordance with the present invention include methods and systems for data prediction.

Abstract: Events are received from at least one source. An abstract definition of a process provides a modified version of the process. In accordance with mapping information, events from the received events corresponding to the modified version of the process are identified. Data relating to execution of the process is stored into a repository, wherein the stored data is produced from the identified events.

Abstract: Various approaches are disclosed for loading data from a vertical database table into a horizontal database table. In one embodiment, a number of rows in a vertical database table and a number of columns in a horizontal database table are determined. Entries in a first column of the vertical table contain object identifiers, entries in a second column contain attribute names corresponding to the object identifiers, and entries in a third column contain attribute values corresponding to the attribute names. The horizontal table includes a column for the object identifiers and respective attribute columns for the attributes names. One of a plurality of methods is selected and used for reading data from the vertical database table and writing data to the horizontal database table based in part on the number of rows in the vertical database table and the number of columns in the horizontal database table.

Abstract: Systems and methods of analyzing decision points in a business process are described. In one aspect, process execution data that is generated by a workflow management system during execution of one or more instances of a business process involving a set of one or more activities and a set of one or more decision points is accessed. Based upon the accessed process execution data, a predictive quantitative model including a set of one or more rules correlating context data at different stages of the business process with business process outcomes at one or more decision points in the business process is built. In another aspect, one or more rules correlating context data at different stages of the business process with business process outcomes at one or more decision points in the business process are presented to a user.