Servicenow, Inc.

Ciprian Mocanu

Aida Rikovic Tabak

Manjeet Singh

Georgi Ivanov

Vadim Denisov

Marta Penzo

Hans Jochen Gerhard Pohle

Andrei-Mihai Gabur

Jimmy Castex

Seth Tucker Stafford

Benedetto Fiorelli

Abhijith Thette Nagarajan

Prabhakaran Subramani Thandayuthapani

Robert-Jan Barmentloo

Robert Andrew Ninness

Shayan Shahand

Sumana Ravikrishnan

Dileeshvar Radhakrishnan

Adrianus Augustinus Mathijssen

Johannes Von Sichart

Lidhvija Boini

Hans Joachim Gerhard Pohle

Anita Lugomer

Andrei Gabur

Andrei Vlad Olteanu

Bojan Tomić

Ramya Raghavan

An embodiment involves receiving a request specifying a particular process, wherein an event table associates event identifiers of events, process identifiers of processes that generated to the events, timestamps of times when the events occurred, states of the processes at the times, and references to related processes; generating nodes of a graph, wherein the particular process and each of its related processes are represented by entity nodes annotated with respective process identifiers, and the events are represented by event nodes annotated with respective event identifiers; generating edges between the entity nodes and the event nodes for which the events of the event nodes either were: generated by the processes represented by the entity nodes, or refer to the processes represented by the entity nodes; and generating edges between pairs of the event nodes that: generated by a common process, and the events of which occurred sequentially according to their timestamps.

Multi-dimensional process mining and analysis

An embodiment may involve a server-side log collected by a server device, where the server-side log includes a set of entries indicating a unique identifier, and wherein the unique identifier is assigned to a work item of a server-based application executed by the server device. The embodiment may further involve one or more processors configured to: receive, from a client device disposed upon a network, a client-side log, wherein the client-side log includes operational data related to usage of a client-based application executed by the client device; identify, from the operational data, the client-based application and one or more activities performed by the client-based application; determine that the one or more activities are related to the unique identifier; based on the one or more activities, determine an action that can be taken to improve efficacy of the server-based application; and write, to the persistent storage, a representation of the action.

Server-side workflow improvement based on client-side data mining

A system includes a client instance hosted by a datacenter, wherein the client instance is generated for one or more client networks. The system performs operations comprising generating a graphical user interface, receiving, via the graphical user interface, an input adjusting the selected time period, and updating the graphical user interface in real time in response to the received input. The graphical user interface includes a timeline that spans an entirety of an incident dataset, a selected time period, wherein the selected time period is a portion of the timeline, a plot of incident data from the incident dataset over the selected time period, and a plurality of calculated metrics based on the incident data during the selected time period.

Systems and method for incident scorecard

An enterprise management platform is configured to host a respective instance for multiple client networks. The enterprise management platform receives incoming data including one or more metrics being tracked in the incoming data by the enterprise management platform. For each metric of the one or more metrics, a determination is made that a statistic generator is to be processed for the corresponding metric, and responsive to determining that the statistic generator is to be processed, a statistic is generated using the statistic generator. For each statistic, a news score is generated, using a news evaluator, to convert the statistic generator to a news score. The news scores are then sorted and stored in a database disposed within the enterprise management platform.

Data insight scoring for performance analytics

Systems, methods, and media are presented to analyze unstructured text. Unstructured data is retrieved from a user inputs or records. The user inputs include an incident report or a problem report. Text words in the unstructured data are identified. A number of occurrences of each text word is counted. The text words are displayed in a word cloud by displaying each of the text words with a size corresponding to the number of occurrences of the respective text word. A larger number of occurrences results in a larger size of the respective text word when displayed. At least one trendline for occurrences for a corresponding text word is also displayed.

Text analysis of unstructured data

Visualizations are automatically generated based at least on a received identifier identifying a report. One or more data sets and one or more style configurations are retrieved from a shared visualization library via a backend API based on the received identifier and passed to a router component. The router component includes a switch that renders a score component, which generates a score visualization, if the retrieved data sets include score data. If the data sets include time series data, or the score visualization also includes a time series graph, the router component renders a time series component that passes the data sets and the style configurations to a parser that parses the data sets and the style configurations and outputs one or more highcharts options objects. A highcharts component generates the time series visualizations and/or adds the time series graph to the score visualization based on the highcharts options objects.

Systems and method for shared visualization library

Visualizations are automatically generated based at least on an identifier that identifies a report. One or more data sets and style configurations are retrieved from a shared visualization library via a backend API based on the received identifier and passed to a router component. The router component includes a switch that renders a score component, which generates a score visualization, if the retrieved data sets include score data. If the data sets include time series data, or the score visualization also includes a time series graph, the router component renders a time series component that passes the data sets and the style configurations to a parser that parses the data sets and the style configurations and outputs one or more highcharts options objects. A highcharts component generates the time series visualizations and/or adds the time series graph to the score visualization based on the highcharts options objects.

A hosted client instance includes a performance analytics module to present an internal key performance indicator and an external key performance indicator on a performance analytics dashboard. A query is executed to a connection to an external data source over a network to obtain a result set of data associated with the external key performance indicator. REST APIs associated with the performance analytics module are executed to: store the result set of data in a performance analytics storage device on the hosted client instance, the performance analytics storage device storing both the data associated with external and internal key performance indicators; and render, via a UI rendering engine of the performance analytics module, one or more widgets on the performance analytics dashboard. The REST APIs interact with the data associated with the internal and external indicators in the storage device to render the one or more widgets.

External data collection for REST API based performance analytics

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Amsterdam, Netherlands

Ciprian Mocanu