Microsoft Technology Licensing, LLC

Igor B Peev

Keri Talbot

Christopher D Edwards

Scott Randall Shell

Ehab Sobhy

Liang Chen

Bryan Todd Agnetta

Robert Pengelly

Jonathan Alexander Lee

Curtis Glenn Wong

Zeke Koch

Yuhang Zhu

Jonathan Edgar Fay

Karen Xiaoxu Cheng

B Scott Ruble

John Alfred Payne

Udiyan Padmanabhan

Lewey Geselowitz

Kevin Fan

Palani Sundaramurthy

Robert Charles Johnstone Pengelly

Jorge Armando Peraza

Brian Scott Ruble

Daniel Benjamin Witriol

Hung Minh Dang

Kevin John Savage

Jimmy Y Sun

Nicholas Milton Hofmeister

Chee Heng Chew

Chad B Rothschiller

Jai Srinivasan

Dominique Fortier

Stephen C Rowe

Michael P Calligaro

Lee M Butler

Alexander A Babanov

Ehab Sobhy Deraz

Safiya Bhojawala

Steven Marcel Elza Wilssens

Xiaoyu Chai

Puneet Bhatia

Anil Dhawan

Dmitri Viktorovich Kotchetov

Connie Qin Yang

James Thomas Marshall

Paavany Jayanty

Alexander S Weil

Matthew Willem Asplund

Adam Swank

Sumonto Ghosh

Megan Moriko Langley

Tomas Aleksas Mereckis

Eamon Guthrie Cosgrove Millman

Soheil Sadeghi

Omari Carter-thorpe

Jagan Subhas

Disclosed herein is a system for leveraging telemetry data representing usage of a component installed on a group of sampled computing devices to confidently infer the quality of a user experience and/or the behavior of the component (e.g., an operating system) on a larger group of unsampled computing devices. The system is configured to use a propensity score matching approach to identify a sampled computing device that best represents an unsampled computing device using configuration data that is collected from both the sampled and unsampled computing devices. The quality of the user experience and/or the behavior of the component may be captured by a metric of interest (e.g., a QoS value). Accordingly, the system is configured to use the known metric of interest, determined from the telemetry data collected for the sampled computing device, to determine or predict the metric of interest for the unsampled computing device.

Using propensity score matching to determine metric of interest for unsampled computing devices

A user request to display an application while the device is locked is received. In response to this user request, one or more images generated by the application are obtained and displayed while the device is locked. Additionally, an indication of an application to be displayed upon resuming operation from a power-saving mode can be received, and an image generated by the application is displayed in response to resuming operation from the power-saving mode.

Application display on a locked device

Various techniques for visualizing cross-pivoted tables are disclosed herein. In one embodiment, a method includes determining if a first dimension and a second dimension of a cross-pivoted table contain non-numerical values, the cross-pivoted table having a plurality of data points each dependent upon a first value in the first dimension and a second value in the second dimension. In response to determining that the first dimension and the second dimension contain non-numerical first and second values, the non-numerical first and second values can be converted to corresponding numerical first and second values. The method can then include plotting, on a display, a visual representation of the plurality of data points of the cross-pivoted table using the numerical first and second numerical values as first and second axis, respectively.

Visualization of cross-pivoted data

Performance and capability improvements of computer devices that provide digital images of heatmap visualizations for datasets are provided via both systems and methods. A value-color spectrum is correlated to the dataset via a multi-pass rendering. The multi-pass rendering yields a two-channel mask, which is applied to a map to show the dataset in a heatmap visualization on that map, and may be continually used as the map is manipulated by a user. User interface tools are also provided to enable a user to specify a custom value-color spectrum, how the dataset is to be aggregated, the area of effect for a data point in the visualization, the strength of effect for a data point in the visualization, and which specifies how a dataset will be visually represented in a heatmap.

Custom heatmaps

Three dimensional, conditional formatting based data visualization is provided. Received underlying data may be analyzed and one or more portions of the underlying data that are of interest to a user determined. The portions may be selected actively by a user of automatically determined based on a variation of values in each portion, values of data points in each portion, a usage history of the user, and/or a credential of the user. A background image may be generated by converting the tabular data into a three dimensional image or selecting and image or a graphic associated with the underlying data. The visualization(s) may then be displayed over the background. Scenes may be selected for animated slide shows or movies.

Three dimensional conditional formatting

Concepts and technologies are described herein for generating scenes and tours in a spreadsheet application. In accordance with the concepts and technologies disclosed herein, a computer system executes a visualization component. Selection of an option to create a tour can be detected by the computer system. In response to detecting selection of the option, the computer system can create a tour. The computer system also can detect selection of an option to add a scene to the tour. The tour can be saved. Playback of the tour can be started in response to detecting selection of a play option. If the playback is paused, changes made to the tour and/or the scenes can be tracked by the computer system, and an updated version of the tour can be saved.

Generating scenes and tours in a spreadsheet application

Systems and methods are provided to improve map type data visualizations in which custom images are used as background against which datasets are visualized. In various examples, coordinate systems are automatically generated and applied to the custom image based on the positional data of the dataset. The custom image may replace a pre-existing background, and the plotting of the dataset may be automatically modified based on differences between the pre-existing background and the custom image. Aspects provide for enhanced user control of the map type visualization to further modify how datasets are plotted and how visualizations are presented. Example modifications include offsets and scales, which may be automatically determined and applied or set manually. In some examples, the custom image may be part of a set of image tiles, which are operable to provide various levels of detail from several viewing angles and heights.

Custom map configuration

Concepts and technologies are described herein for displaying temporal information in a spreadsheet application. In accordance with the concepts and technologies disclosed herein, spreadsheet data can be obtained at a computer system. The spreadsheet data can include data values, temporal information, and geographic information. The computer system can generate a visualization of the spreadsheet data based, at least partially, upon the data values, the temporal information, and the geographic location information. The computer system also can output the visualization.

Displaying temporal information in a spreadsheet application

A user profile is used to assist a user in identifying events of interest and to provide context to users regarding events that matches user preferences. The user profile may be based on behaviors exhibited on a mobile device, on input by the user or on data on the mobile device. The user profile is analyzed to provide notification of events of interest to the user based upon the analysis of the user profile. The user profile may include anything that contributes to a state on the device.

Discovering an event using a personal preference list and presenting matching events to a user on a display

Automatic recognition and presentation of insights of data is provided through analysis of overall data to infer locations of a user's data. Statistical, heuristic, and comparable analysis on the user's data sets is used to determine insights such as trends, correlations, outliers, comparisons, and patterns. The insights are then presented to the user through automatically optimized visualizations (highlighting determined insights), emphasis on presented raw data, data formatting suggestions, and similar ones with the capability to explore further.

Automatic recognition and insights of data

Display screen with animated graphical user interface

Growing community of inventors

Seattle, WA, United States of America

Igor B Peev