Automatic analysis of difference between multi-dimensional datasets

    公开(公告)号:US11734317B2

    公开(公告)日:2023-08-22

    申请号:US17694799

    申请日:2022-03-15

    CPC classification number: G06F16/288 G06F16/2264 G06F16/248 G06F16/285

    Abstract: According to implementations of the subject matter described herein, there is proposed a solution for automatic analysis of a difference between multi-dimensional datasets. In this solution, an analysis request is received for a first dataset and a second dataset, each of which including data items corresponding to a plurality of dimensions. In response to the analysis request, data items corresponding to a first dimension in the first and second datasets are compared. Based on the comparison, a first set of influence factors associated with the first dimension are determined, each influence factor indicating a reason for a difference between the first and second datasets from a respective perspective. An analysis result related to the difference between the first and second datasets is presented based on the first set of influence factors. In this way, it is possible to achieve automatic and efficient analysis of the difference between the different datasets.

    Automatic analysis of difference between multi-dimensional datasets

    公开(公告)号:US11308134B2

    公开(公告)日:2022-04-19

    申请号:US16620381

    申请日:2018-05-23

    Abstract: According to implementations of the subject matter described herein, there is proposed a solution for automatic analysis of a difference between multi-dimensional datasets. In this solution, an analysis request is received for a first dataset and a second dataset, each of which including data items corresponding to a plurality of dimensions. In response to the analysis request, data items corresponding to a first dimension in the first and second datasets are compared. Based on the comparison, a first set of influence factors associated with the first dimension are determined, each influence factor indicating a reason for a difference between the first and second datasets from a respective perspective. An analysis result related to the difference between the first and second datasets is presented based on the first set of influence factors. In this way, it is possible to achieve automatic and efficient analysis of the difference between the different datasets.

    AUTOMATIC NOTIFICATION OF DATA CHANGES

    公开(公告)号:US20210377203A1

    公开(公告)日:2021-12-02

    申请号:US17417283

    申请日:2019-01-04

    Abstract: A method provides an automatic notification manner of data changes. After collecting information related to a target user (202) 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 (204). Then, upon the dataset is updated, a variety of critical data changes in the dataset may be detected as an alert (206), and a notification related to the alert may be provided to the user via various manners (208). 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.

    Data Segmentation and Visualization
    7.
    发明申请
    Data Segmentation and Visualization 审中-公开
    数据分段和可视化

    公开(公告)号:US20160117373A1

    公开(公告)日:2016-04-28

    申请号:US14898067

    申请日:2013-06-13

    CPC classification number: G06F16/26 G06F16/27 G06F16/287

    Abstract: The techniques described herein provide tools that summarize a dataset by creating a final set of segments that, when visually presented via a histogram or other data presentation tool, show the distribution of at least a portion of the data. To create the final set of segments, the techniques described herein may collect or receive a dataset with distinct values, and divide the dataset into a number of segments that is less than or equal to a segment presentation threshold (e.g., ten segments). After creating the final set of segments, the techniques may configure and/or present data visualizations, such as histograms, for the created segments so that an observer is provided with a good viewing experience.

    Abstract translation: 本文描述的技术提供了通过创建最终的段集合来总结数据集的工具,当通过直方图或其他数据呈现工具直观呈现时,该组段显示数据的至少一部分的分布。 为了创建最终的段集合,本文描述的技术可以收集或接收具有不同值的数据集,并将数据集划分成小于或等于段呈现阈值(例如,10个段)的多个段。 在创建最后一组片段之后,技术可以为创建的片段配置和/或呈现诸如直方图的数据可视化,使得向观察者提供良好的观看体验。

    Automatic insights for multi-dimensional data

    公开(公告)号:US11809422B2

    公开(公告)日:2023-11-07

    申请号:US17821843

    申请日:2022-08-24

    CPC classification number: G06F16/2453 G06F16/26 G06F16/283 G06Q10/06

    Abstract: Automatically identifying insights from a dataset and presenting the insights graphically and in natural language text ranked by importance is provided. Different data types and structures in the dataset are automatic recognized and matched with a corresponding specific analysis type. The data is analyzed according to the determined corresponding analysis types, and insights form the analysis are automatically identified. The insights within a given insight type and between insight types are ranked and presented in order of importance. Insights include those having multiple pipelined attributes and other insights include multiple insights identified as having some relationship for the included insights.

    Automatic insights for multi-dimensional data

    公开(公告)号:US11468056B2

    公开(公告)日:2022-10-11

    申请号:US16859649

    申请日:2020-04-27

    Abstract: Automatically identifying insights from a dataset and presenting the insights graphically and in natural language text ranked by importance is provided. Different data types and structures in the dataset are automatic recognized and matched with a corresponding specific analysis type. The data is analyzed according to the determined corresponding analysis types, and insights from the analysis are automatically identified. The insights within a given insight type and between insight types are ranked and presented in order of importance. Insights include those having multiple pipelined attributes and other insights include multiple insights identified as having some relationship for the included insights.

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