Abstract: A method may include accessing, from a data store, telemetry data for an application, the telemetry data identifying actions executed by the application for a set of users of the application; retrieving an engagement index for the application using the telemetry data based on an engagement index profile, the engagement index profile identifying a selection of actions and a set of calculation dimensions; and presenting a user interface, the user interface including: a first portion identifying the selection of actions; a second portion identifying the set of calculation dimensions; a third portion identifying an original value of an action of the selection of actions with respect to a dimension in the set of calculation dimensions; and a fourth portion identifying a weighted composite value of the action with respect to set of calculation dimensions.

Abstract: A method may include accessing, from a data store, telemetry data for an application, the telemetry data identifying actions executed by the application for a set of users of the application; retrieving an engagement index for the application using the telemetry data based on an engagement index profile, the engagement index profile identifying a selection of actions and a set of calculation dimensions; and presenting a user interface, the user interface including: a first portion identifying the selection of actions; a second portion identifying the set of calculation dimensions; a third portion identifying an original value of an action of the selection of actions with respect to a dimension in the set of calculation dimensions; and a fourth portion identifying a weighted composite value of the action with respect to set of calculation dimensions.

Abstract: A data processing system implements adaptive telemetry sampling by obtaining first telemetry data from a plurality of telemetry data sources, analyzing the first telemetry data to identify a subset of telemetry data sources for which a reduced sampling rate may be implemented, determining a reduced sampling rate for each event type of the plurality of event types, selecting a subset of the event types for which the reduced sampling rate is to be applied, obtaining second telemetry data from the subset of telemetry data sources at the reduced sampling rate associated with each event type of the subset of event types, analyzing the second telemetry data to determine one or more estimated metric values for one or more metrics, and generating a report comprising the one or more estimated metric values and an estimated total cost saving based on an estimated cost saving associated with each event type.

Abstract: A method of and system for performing pilot testing of a software program in an organization is carried out by collecting pilot testing data generated from a pilot testing of a software program run on one or more hardware assets in the organization, determining whether a sufficient amount of pilot testing data has been collected, and, when so, calculating one or more pilot test metrics from the collected data. The calculated pilot test metrics may then be compared to similar metrics in a target population to evaluate the software program.

Abstract: In one example, a system includes an electronic processor configured to receive telemetry data originating from a plurality of client applications. The telemetry data includes data points associated with errors associated with one or more operations. The electronic processor also classifies the telemetry data based a plurality of classes of data, converts the plurality of classes of data into one or more metrics based on a plurality of dimensions, and aggregates the metrics for the classes of data by all the dimensions. The electronic processor accesses a predictive scoring model for a stored metric associated with a dimension of interest, determines a prediction error associated with the dimension of interest, detects an anomaly based on an item selected from the group consisting of the prediction error and a static threshold, and transmits an alert message, generates a bug report, and stores the bug report in a database.

Abstract: Methods and systems for determining an upgrade readiness metric of a tenant in a cloud environment. One method includes receiving, with an electronic processor, device telemetry data for a plurality of devices associated with a first plurality of tenants in the cloud environment and receiving, with the electronic processor, software telemetry data for a second plurality of tenants in the cloud environment. The method also includes determining, with the electronic processor, the upgrade readiness metric for the tenant based on the device telemetry data and the software telemetry data and displaying the upgrade readiness metric within a user interface.

Abstract: A method of and system for performing pilot testing of a software program in an organization is carried out by collecting pilot testing data generated from a pilot testing of a software program run on one or more hardware assets in the organization, determining whether a sufficient amount of pilot testing data has been collected, and, when so, calculating one or more pilot test metrics from the collected data. The calculated pilot test metrics may then be compared to similar metrics in a target population to evaluate the software program.

Abstract: In one example, a system includes an electronic processor configured to receive telemetry data originating from a plurality of client applications. The telemetry data includes data points associated with errors associated with one or more operations. The electronic processor also classifies the telemetry data based a plurality of classes of data, converts the plurality of classes of data into one or more metrics based on a plurality of dimensions, and aggregates the metrics for the classes of data by all the dimensions. The electronic processor accesses a predictive scoring model for a stored metric associated with a dimension of interest, determines a prediction error associated with the dimension of interest, detects an anomaly based on an item selected from the group consisting of the prediction error and a static threshold, and transmits an alert message, generates a bug report, and stores the bug report in a database.

Abstract: Methods and systems for determining an upgrade readiness metric of a tenant in a cloud environment. One method includes receiving, with an electronic processor, device telemetry data for a plurality of devices associated with a first plurality of tenants in the cloud environment and receiving, with the electronic processor, software telemetry data for a second plurality of tenants in the cloud environment. The method also includes determining, with the electronic processor, the upgrade readiness metric for the tenant based on the device telemetry data and the software telemetry data and displaying the upgrade readiness metric within a user interface.

Abstract: Aspects of the present disclosure relate to systems and methods for providing recommended collaborators. In one aspect, collaboration data associated with at least one application may be received at a data modeling service. A collaboration graph for representing the collaboration data associated with the at least one application may be created. The collaboration graph may be queried to identify a plurality of recommended collaborators for collaborating within the at least one application. The plurality of recommended collaborators may be ranked in a ranking order based on a set of criteria.

Abstract: Increasingly, productivity services are executed in collaborative environments. While new collaboration features may provide users with a rich set of tools to expand collaboration methods and gain productivity, users may not be aware of the features' existence. Embodiments are directed to automatic provision of recommendations for content collaboration. Actions performed in conjunction with a document may be monitored to determine a usage pattern associated with the document in response to detecting an opening of the document through an application user experience. An identifier associated with the document and other interactions with the document may be determined. A recommendation may then be provided or display through the application user experience based on the usage pattern associated with the document, the identifier, and the other interactions with the document.

Abstract: Self-learning and adaptive modeling is employed with respect to predictive analytics. A hierarchical model structure can be employed comprising a set of predictive models automatically built from accumulated data and distributed across multiple levels. For a given input type, a set of candidate models can be identified across varying levels of granularity, and a best model selected based on a comparison of performance metrics of the models. The best model can then be activated for use in making predictions. Of course, the best model can change based on most recent training performance results, since as more data becomes available more specific models can be developed.

Abstract: Self-learning and adaptive modeling is employed with respect to predictive analytics. A hierarchical model structure can be employed comprising a set of predictive models automatically built from accumulated data and distributed across multiple levels. For a given input type, a set of candidate models can be identified across varying levels of granularity, and a best model selected based on a comparison of performance metrics of the models. The best model can then be activated for use in making predictions. Of course, the best model can change based on most recent training performance results, since as more data becomes available more specific models can be developed.

Abstract: Systems and methods for electronically ranking records of inventory items are provided. Inventory items satisfying search criteria are electronically identified and ranked according to an inventory score calculated from a function comprising inventory attribute values of the inventory items and weighting values corresponding to the inventory attributes. The scored inventory may be further displayed to a user, such as a user that electronically submits the search criteria. The attribute values may include inventory item characteristics perceptible to users of the inventory items. The weighting values may be generated from a discrete choice model employing a conditional logit function fit to training data. The inventory score function may further include a long term function that numerically represents inventory items characteristic that are not perceptible to users of the inventory items. The disclosed embodiments may be applied to inventory including, but not limited to, travel inventory, such as hotels.