Abstract: An analytics server is disclosed that enables natural language queries (NLQs) to be used to access key performance indicator (KPI) data. The analytics server includes a graphical user interface (GUI) that presents a set of KPIs associated with a user. The GUI includes suitable user interface elements to enable the user to provide natural language queries regarding these KPIs. The user interface elements provide the user with suggested NLQs based on, for example, KPIs to which the user has access and/or previous NLQs of the user. In response to the analytics server receiving a suitable NLQ from the user, the analytics server generates an appropriate database query to retrieve the KPI data requested by the NLQ. The GUI is then updated to present a visual representation (e.g., a bar graph, a pie chart, a trend line, a single value) of the retrieved KPI data.

Abstract: 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. The enterprise management platform determines that a condition is reached based on the one or more metrics and selects at least a portion of the incoming data for a dashboard of the enterprise management platform responsive to determining that the incoming data is indicative of the condition being reached. The enterprise management platform provides, to a client device associated with one of the plurality of client networks, a representation of a graphical user interface displaying a data insights widget of the dashboard that displays the data indicative of the condition being reached without displaying other data in the incoming data that has not reached a level indicative of other conditions.

Abstract: 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.

Abstract: 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.

Abstract: An analytics server is disclosed that enables natural language queries (NLQs) to be used to access key performance indicator (KPI) data. The analytics server includes a graphical user interface (GUI) that presents a set of KPIs associated with a user. The GUI includes suitable user interface elements to enable the user to provide natural language queries regarding these KPIs. The user interface elements provide the user with suggested NLQs based on, for example, KPIs to which the user has access and/or previous NLQs of the user. In response to the analytics server receiving a suitable NLQ from the user, the analytics server generates an appropriate database query to retrieve the KPI data requested by the NLQ. The GUI is then updated to present a visual representation (e.g., a bar graph, a pie chart, a trend line, a single value) of the retrieved KPI data.

Abstract: 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.

Abstract: 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.

Abstract: Time series data is generated and forecasted with a selected forecasting mechanism. Time series data to forecast including a plurality of data points is received. A count of the plurality of data points is determined to meet a threshold. Responsive to that determination, a plurality of test forecasts are generated with respective forecasting mechanisms of a plurality of forecasting mechanisms using a first subset of the plurality of data points. Errors are then determined for the respective forecasting mechanisms, such as based on comparisons of corresponding ones of the plurality of test forecasts and a second subset of the plurality of data points. One of the plurality of forecasting mechanisms is selected based on the errors. An output forecast is then generated with the selected forecasting mechanism using the first and second subsets of the plurality of data points.

Abstract: 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. The enterprise management platform determines that a condition is reached based on the one or more metrics and selects at least a portion of the incoming data for a dashboard of the enterprise management platform responsive to determining that the incoming data is indicative of the condition being reached. The enterprise management platform provides, to a client device associated with one of the plurality of client networks, a representation of a graphical user interface displaying a data insights widget of the dashboard that displays the data indicative of the condition being reached without displaying other data in the incoming data that has not reached a level indicative of other conditions.

Abstract: Visualizations are automatically generated based at least on a received identifier that identifies 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.

Abstract: 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.

Abstract: 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. The enterprise management platform determines that a condition is reached based on the one or more metrics and selects at least a portion of the incoming data for a dashboard of the enterprise management platform responsive to determining that the incoming data is indicative of the condition being reached. The enterprise management platform provides, to a client device associated with one of the plurality of client networks, a representation of a graphical user interface displaying a data insights widget of the dashboard that displays the data indicative of the condition being reached without displaying other data in the incoming data that has not reached a level indicative of other conditions.

Abstract: One or more client instances hosted by a platform may support access to a cloud-based application to select a dashboard, such as via a client device. Each dashboard includes one or more visualizations of analytic or summary information. When a user of the client device accesses the cloud-based application, a subset of dashboards are initially provided based on recent usage history of dashboards. Specifically, the cloud-based application determines if the user has access to each dashboard of the subset of dashboards and, in response to determining the user does have access to a dashboard, displays the dashboard within the subset of dashboards. The user may select a dashboard from the subset of dashboards, where the selected dashboard is displayed on the client device.

Abstract: 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.

Abstract: Visualizations are automatically generated based at least on an a 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.

Abstract: 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.

Abstract: A computing system includes a server. The server is communicatively coupled to a data repository clone and is configured to store a calendar-based data in the data repository. The server is further configured to receive a request to create a custom calendar, and to create the custom calendar based on a calendar data schema and the request. The server is additionally configured to provide the custom calendar to systems communicatively coupled to the server. The server is also configured to provide a data analysis using the calendar-based data and the custom calendar.

Abstract: One or more client instances hosted by a platform may support access to a cloud-based application to select a dashboard, such as via a client device. Each dashboard includes one or more visualizations of analytic or summary information. When a user of the client device accesses the cloud-based application, a subset of dashboards are initially provided based on recent usage history of dashboards. Specifically, the cloud-based application determines if the user has access to each dashboard of the subset of dashboards and, in response to determining the user does have access to a dashboard, displays the dashboard within the subset of dashboards. The user may select a dashboard from the subset of dashboards, where the selected dashboard is displayed on the client device.

Abstract: A system includes a memory and a processor configured to analyze a data set to determine a first number of incidents during a first period of time and a second number of incidents during a second period of time, train a plurality of models predict a number of incidents during the second period of time, wherein the plurality of respective models comprise a random forest model, a drift model, and a naïve seasonal drift model, identifying the model that best predicted the number of incidents during the second period of time, and utilizing the identified model to predict a third number of incidents within a set allowable range of values during a third period of time, and upper and lower limits of the third number of incidents during the third period of time based on a set confidence level and displaying the third number of incidents during the third period of time.

Abstract: Systems and methods for generating analytics widgets using a graphical user interface (GUI) are provided. The analytics widgets are generated using a visually guided workflow presented via the GUI in which attributes relating to the analytics widgets are specified at the same time the analytics widget and its associated data visualization are generated.