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: 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: 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: 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: 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.