Abstract: A system for root cause analysis based on process optimization data is provided. The system receives log data associated with a first trace between a first activity and a second activity of a process. The system further determines a state of inefficiency between the first activity and the second activity based on the received log data. The system further applies a first machine learning (ML) model on the received log data. The system further determines a first label and a first value to be associated with the first trace of the process based on the application of the first ML model. The system further generates presentation data associated with the determined state of inefficiency of the first trace based on the determination of the first label and the first value and further transmits the generated presentation data on a user device.

Abstract: An example embodiment may involve identifying local traces of related events within a plurality of event data repositories, wherein each of the event data repositories is respectively associated with a software application; using a clustering model, assigning the local traces into clusters; determining positive rules that define when pairs of the local traces are linked to a common global trace, and negative rules that define when the pairs are linked to different global traces; linking the pairs into global traces; iteratively training a similarity model to project the local traces into a vector space such that the pairs that are linked to common global traces exhibit a greater similarity with one another than the pairs that are linked to different global traces; and based on the similarity model as trained, linking further local traces to the global traces.

Abstract: An example embodiment may involve identifying local traces of related events within a plurality of event data repositories, wherein each of the event data repositories is respectively associated with a software application; using a clustering model, assigning the local traces into clusters; determining positive rules that define when pairs of the local traces are linked to a common global trace, and negative rules that define when the pairs are linked to different global traces; linking the pairs into global traces; iteratively training a similarity model to project the local traces into a vector space such that the pairs that are linked to common global traces exhibit a greater similarity with one another than the pairs that are linked to different global traces; and based on the similarity model as trained, linking further local traces to the global traces.

Abstract: A system for root cause analysis based on process optimization data is provided. The system receives log data associated with a first trace between a first activity and a second activity of a process. The system further determines a state of inefficiency between the first activity and the second activity based on the received log data. The system further applies a first machine learning (ML) model on the received log data. The system further determines a first label and a first value to be associated with the first trace of the process based on the application of the first ML model. The system further generates presentation data associated with the determined state of inefficiency of the first trace based on the determination of the first label and the first value and further transmits the generated presentation data on a user device.

Abstract: The disclosed embodiments relate to a system and a method for process discovery. Embodiments of the present invention comprise extracting process data from a data source, creating a trace using the extracted process data, wherein the trace comprises a plurality of events, and detecting a process model using the plurality of events.

Abstract: Provided are systems, methods and techniques for discovering protocols of a network-provided service by initially collecting interaction data that pertain to messages between a plurality of devices across a network. Metrics that indicate frequencies of occurrence for different message sequences within the interaction data are calculated, and a protocol structure based on the interaction data and the metrics is generated. Finally, the protocol structure, which describes permitted conversations for a particular service implemented across the network, is output.

Abstract: Embodiments of the present invention relate to a system and method for process discovery. Specifically, embodiments of the present invention relate to defining a trace using process data, the trace comprising a collection of events, analyzing the trace to detect nodes and arcs between the nodes using relationships between the collection of events, and detecting interleaving in the arcs by analyzing relationships between the collection of events and the detected nodes and arcs.

Abstract: Disclosed embodiments of the present invention relate to a system and method for automatic generation of a star schema. The system and method may comprise categorizing a data field into one of a plurality of data field types, one of the data field types being an enumeration type data field. The system and method may further comprise developing dimensions for a table that represents an initial star schema design using the categorization of the data, detecting functional dependencies between the data field and other data fields, and refining the initial star schema design by modifying the table based on detected functional dependencies.

Abstract: A method and system are disclosed for monitoring the performance of web-based services. The method comprises receiving a transaction from a client and routing the transaction to an appropriate web service for execution of the transaction. During execution of the transaction, performance data relating to the execution of the transaction is monitored and logged. The collected performance data is then queried based on pre-defined performance metrics and web service performance reports are generated. A system for the foregoing method is also disclosed.

Abstract: Embodiments of the invention provide a method and an apparatus for creating a digital dashboard. One embodiment provides a dashboard palette in an application. In addition, at least one object is provided for the dashboard palette, wherein at least one property of the at least one object is linked to a data source. The at least one object is then coupled with the dashboard palette to form a dashboard description. The dashboard description is then exported to a dashboard creator and publisher, wherein the dashboard creator and publisher provide a functional dashboard based on the dashboard description.

Abstract: A method of process-driven analysis of operations includes defining an abstract process, defining at least one metric over the abstract process using a metric definer and computing metric values using a metric computation engine. The method further includes building an analysis model and a prediction model using an analysis and prediction engine to provide analysis on the computed metric values and optimizing the abstract process based on the computed metric values.

Abstract: The present disclosure relates to a system and method for analyzing a process. Embodiments of the present invention may include obtaining a process execution trace including at least one subtrace, the process execution trace comprising at least one loop repetition. Further, embodiments may include removing loop repetitions within the process execution trace, identifying the subtrace as a point for data collection in a process, and collecting data related to the subtrace.

Abstract: A method and system for integrating workflow management systems with business-to-business interaction standards. An automatic business-to-business (B2B) template generator is provided for supporting workflow design. The B2B template generator automatically generates process templates and service templates based either on a description of a business-to-business interaction standard is received or a structured representation of the business-to-business interaction standard. When the (B2B) template generator receives the description of business-to-business interaction standard as the input, the (B2B) template generator first converts the description of the business-to-business interaction standard into a structured representation of the business-to-business interaction standard. At least process template is automatically generated based on the structured representation of the business-to-business interaction standard. The template (e.g.

Abstract: An event management method for a computer implemented business process system. The method includes the step of executing a plurality of events for representing a business process, the business process implemented by progressing through the events. A plurality of event nodes are executed for the business process, the event nodes defining points in the progress of the business process for communicating with an external process to exchange information. The business process is executed by sequentially executing the events, wherein the execution proceeds in accordance with the event nodes.

Abstract: A system comprises a first store of process instance data, a second store of data including predictions and statistics respectively corresponding to the process instance data, and a dynamic prioritization system configured to selectively access data in the first store and the second store and to estimate a cost of a process instance responsive to the accessing, wherein process instance node priorities are adjusted responsive to the estimate. A method comprises providing a first store of process instance data, providing a second store of data including predictions and statistics respectively corresponding to the process instance data, selectively accessing data in the first store and the second store, estimating a cost of a process instance responsive to the accessing and selectively adjusting process instance node priorities using a dynamic prioritization system responsive to the estimating.

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 semantically investigating business processes are described. In one aspect, execution data that is generated by one or more components of a business process platform is accessed. The data is generated during execution, at each of one or more nodes, of one or more instantiations of one or more business processes each involving a set of one or more activities each defined by a respective service and performed by a respective set of one or more resources. The accessed execution data is mapped into one or more semantic concepts to obtain outcome data. The outcome data is visualized in terms of a user-selected perspective.

Abstract: Systems and methods of investigating business processes are described. These systems and methods support real-time monitoring, analysis, management, and optimization of business processes. A graphical user interface enables users to apply data warehousing and data mining techniques to business process execution data and to visualize process execution data along multiple configurable dimensions and at different configurable levels of granularity.

Abstract: A method for generating a pixel-oriented graph provides visual boundaries for representing aggregate information. The present method for generating a pixel-oriented graph includes determining a visual boundary for representing an aggregate of a set of information depicted in the pixel-oriented graph and constructing a set of pixel blocks that represent the information such that the pixel blocks are visually distinguished by the visual boundary. A method according to the present techniques employs a visual weight to classify labels and high weight information is shown and other information is made invisible and hidden in the property of a graph.

Abstract: Systems and methods of improving business processes are described. These systems and methods enable service providers to improve the quality of services delivered to customers and employees by improving service execution through the optimal selection of resources (e.g., internal resources or external resources, or both) that are invoked to execute the delivered services. In one aspect, process execution data is accessed. Business process instances are classified in accordance with a quality taxonomy. A predictive model including a set of rules for scoring business process outcomes at different stages of the business process is built based upon the classified business process instances. In another aspect, process entities to be invoked at stages of an active business process instance are selected based upon the predictive model. In another aspect, a user is prompted to define a quality taxonomy for classifying outcomes of instances of a business process.