Microsoft Technology Licensing, LLC

Zhitao Hou

Dongmei Zhang

Haidong Zhang

Xiao Bi Liang

Rui Ding

He Huang

Bryan Dove

Mina Mikhail

Eslam Elsawy

Sanyam Chaudhary

Nikhil Gaekwad

Shi Han

Bo Zhang

Jian-Guang Lou

A method provides an automatic notification manner of data changes. After collecting information related to a target user such as a dataset, a data dashboard, or a data report, the analysis preference of the user can be determined based on the collected information. Then, upon the dataset is updated, a variety of critical data changes in the dataset may be detected as an alert, and a notification related to the alert may be provided to the user via various manners. The method does not require the user to manually configure or create an alert rule for data changes, which makes data-driven alerting much easier for the user, thereby improving the user experience.

Automatic notification of data changes

A method provides an automatic notification manner of data changes. After collecting information related to a target user () such as a dataset, a data dashboard, or a data report, the analysis preference of the user can be determined based on the collected information (). Then, upon the dataset is updated, a variety of critical data changes in the dataset may be detected as an alert (), and a notification related to the alert may be provided to the user via various manners (). The method does not require the user to manually configure or create an alert rule for data changes, which makes data-driven alerting much easier for the user, thereby improving the user experience.

A computing apparatus of an insight interfacing system receives from a user a request for a dataset comprising a plurality of subspaces of a multi-dimensional data structure. Insights are received based on the received request then presented on a display device. Also, a chart may be presented based on the received request. The computing apparatus receives a selection of at least a portion of the presented one or more insights or a portion of the chart, then receives contextual insights based on the selected portion and presents the contextual insights on the display device.

Multi-dimensional data insight interaction

A computing device running a tool for visually exploring datasets receives a request for a dataset comprising a plurality of subspaces of a multi-dimensional data structure and in response to receiving a user selection of a data point associated with the dataset, presents a visualization of the calculations associated with the selected data point. The tool allows the user to select one of the calculations, thus causing presentation of a visualization of the selected calculation. A semantic graphical feature is incorporated into the visualization of the selected calculation depending upon a type of the calculation.

User interface tools for visual exploration of multi-dimensional data

Implementations of the subject matter described herein relate to conversational data analysis. After a data analysis request is received from a user, heuristic information may be determined based on the data analysis request. The heuristic information mentioned here is not a result for the data analysis request but information which may be used for leading the conversation to proceed. Based on such heuristic information, the user may provide supplementary information associated with the data analysis request, for example, clarify meaning of the data analysis request, submit a relevant further analysis request, and so on. A really desired and meaningful data analysis result can be provided to the user according to the supplementary information provided by the user. Thus, data analysis will become more accurate and effective. While obtaining really helpful information, the user also gains good user experience.

Conversational data analysis

Implementations are described related to users directly manipulating visual depictions of aspects of a data set displayed in a user interface to generate or modify visual representations of the data set, such as a chart. The direct manipulation may be either through a computer input device, (e.g., a keyboard or mouse), or based on other input data, such as a touch input. Aspects of a data set include dimensions, which may be used to filter the data set, and metrics, which are quantifiable elements within the data set. In various implementations, input such as drag-and-drop operations corresponding to visual depictions of aspects of a data set may be interpreted in generating or modifying charts.

Direct manipulation interface for data analysis

Data visualizations may include a large number of data points, some of which may be small, and/or data points that are in close proximity to one another. To assist a user in accurately selecting a desired data point, when displaying a data visualization, a magnification area is simultaneously displayed. The magnification area includes a zoomed-in view of a portion of the data visualization, centered at a current location indicated by a selection device. The magnification area also includes centered vertical and horizontal crosshairs to visually indicate the current location indicated by the selection device.

User interface tools for exploring data visualizations

A data exploration user interface includes a selection area with selectable representations of queryable fields of a data source and a visualization area where query results are displayed as data visualizations. Queries are generated by dragging fields from the selectable area to the visualization area of the user interface. A tree structure of data visualizations may be created by dragging data points out of a displayed visualization and applying additional fields to create a new query and resulting visualization. The tree structure is graphically represented with path indicators that provide historical context for each new data visualization within the visualization are of the user interface.

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Beijing, China

Zhitao Hou