US-12625873-B2 - System and method for generating data visualization scores for use with a data analytics environment

US12625873B2US 12625873 B2US12625873 B2US 12625873B2US-12625873-B2

Abstract

Embodiments described herein are generally related to systems and methods for generating data visualization scores, for use with data analytics environments. In accordance with an embodiment, the system can operate in the manner of an expert system, or according to a series of processes or rules, to examine a data visualization of interest, compare a list of found elements with element types specified by an analytics data visualization score matrix, and generate, based on matching found elements with the analytics data visualization matrix, a data visualization score associated with the data visualization. In accordance with an embodiment, the system can operate as a data visualization advisor, during preparation of a data visualization, to provide a user with recommendations or score values indicative of a quality or complexity of their data visualization, which may be helpful in improving their data visualization, for example from a beginner-level to a more advanced-level.

Inventors

Benjamin Arnulf

Assignees

ORACLE INTERNATIONAL CORPORATION

Dates

Publication Date: 20260512
Application Date: 20241101

Claims (12)

1 . A system for generating data visualization scores, comprising: a computer including one or more processors, that provides access to a data analytics environment, wherein the data analytics environment comprises a query engine that operates to process queries against a database according to a query execution plan, wherein the query engine creates the query execution plan responsive to a request for data analytics or visualization information received via a client application and user interface and communicated to the data analytics environment, wherein the system retrieves an appropriate dataset to address a user or business context, for use in generating and returning the requested data analytics or visualization information to the client, as a data visualization; wherein the data analytics environment includes an analytics data visualization score matrix generated grammatically or automatically by the system using a training set of data visualizations assessed as being of varying levels or by using machine learning or other machine or computer-automated techniques to determine relevant element types, and determining a weighting or amount of point values or rules associated therewith, for purposes of creating the matrix, said weighting or amount of point values indicative of their relative importance in assessing a data visualization; wherein the computer operates to: receive a request to assess a data visualization of interest, wherein the data visualization is defined by one or more associated JSON, XML, software code, or metadata; examine the data visualization of interest to prepare a matrix or list of found elements within the data visualization as defined by its associated JSON, XML, software code, or metadata; compare the matrix or list of found elements within the data visualization of interest, with the element types and weighting or amount of point values specified by the analytics data visualization score matrix; and generate, based on a matching of found elements with the analytics data visualization score matrix, a data visualization score associated with the data visualization of interest; wherein the system operates as a data visualization advisor, during preparation of a data visualization, to provide a user with recommendations or score values indicative of a quality or complexity of their data visualization.
2 . The system of claim 1 , wherein the system operates as an expert system, or according to a series of processes or rules, to: examine the data visualization as defined by its associated JSON, XML, software code, or metadata; and compare the matrix or list of found elements within the data visualization of interest, with the element types and weighting or amount of point values specified by the analytics data visualization score matrix, and provide recommendations associated with the data visualization.
3 . The system of claim 1 , wherein the data visualization score is displayed within a user interface as a changeable icon and/or score value indicative of a quality and/or complexity associated with the data visualization of interest.
4 . The system of claim 1 , wherein the system is provided within a cloud computing or data analytics environment.
5 . A method performed by a system for generating data visualization scores, comprising: providing, by a computer including one or more processors, access to a data analytics environment, wherein the data analytics environment comprises a query engine that operates to process queries against a database according to a query execution plan, wherein the query engine creates the query execution plan responsive to a request for data analytics or visualization information received via a client application and user interface and communicated to the data analytics environment, wherein the system retrieves an appropriate dataset to address a user or business context, for use in generating and returning the requested data analytics or visualization information to the client, as a data visualization; wherein the data analytics environment includes an analytics data visualization score matrix generated grammatically or automatically by the system using a training set of data visualizations assessed as being of varying levels or by using machine learning or other machine or computer-automated techniques to determine relevant element types, and determining a weighting or amount of point values or rules associated therewith, for purposes of creating the matrix, said weighting or amount of point values indicative of their relative importance in assessing a data visualization; receiving a request to assess a data visualization of interest, wherein the data visualization is defined by one or more associated JSON, XML, software code, or metadata; examining the data visualization of interest to prepare a matrix or list of found elements within the data visualization as defined by its associated JSON, XML, software code, or metadata; comparing the matrix or list of found elements within the data visualization of interest, with element types and weighting or amount of point values specified by the analytics data visualization score matrix; and generating, based on a matching of found elements with the analytics data visualization score matrix, a data visualization score associated with the data visualization of interest; wherein the method is performed by a data visualization advisor, during preparation of a data visualization, to provide a user with recommendations or score values indicative of a quality or complexity of their data visualization.
6 . The method of claim 5 , wherein the method operates as an expert system, or according to a series of processes or rules, to: examine the data visualization as defined by its associated JSON, XML, software code, or metadata; and compare the matrix or list of found elements within the data visualization of interest, with the element types and weighting or amount of point values specified by the analytics data visualization score matrix, and provide recommendations associated with the data visualization.
7 . The method of claim 5 , wherein the data visualization score is displayed within a user interface as a changeable icon and/or score value indicative of a quality and/or complexity associated with the data visualization of interest.
8 . The method of claim 5 , wherein the method is performed by or within a cloud computing or data analytics environment.
9 . A non-transitory computer readable storage medium having instructions thereon, which when read and executed by a system comprising a computer including one or more processors cause the computer to perform a method comprising: providing, by the computer, access to a data analytics environment, wherein the data analytics environment comprises a query engine that operates to process queries against a database according to a query execution plan, wherein the query engine creates the query execution plan responsive to a request for data analytics or visualization information received via a client application and user interface and communicated to the data analytics environment, wherein the system retrieves an appropriate dataset to address a user or business context, for use in generating and returning the requested data analytics or visualization information to the client, as a data visualization; wherein the data analytics environment includes an analytics data visualization score matrix generated grammatically or automatically by the system using a training set of data visualizations assessed as being of varying levels or by using machine learning or other machine or computer-automated techniques to determine relevant element types, and determining a weighting or amount of point values or rules associated therewith, for purposes of creating the matrix, said weighting or amount of point values indicative of their relative importance in assessing a data visualization; receiving a request to assess a data visualization of interest, wherein the data visualization is defined by one or more associated JSON, XML, software code, or metadata; examining the data visualization of interest to prepare a matrix or list of found elements within the data visualization as defined by its associated JSON, XML, software code, or metadata; comparing the matrix or list of found elements within the data visualization of interest, with element types and weighting or amount of point values specified by the analytics data visualization score matrix; and generating, based on a matching of found elements with the analytics data visualization score matrix, a data visualization score associated with the data visualization of interest; wherein the method is performed by a data visualization advisor, during preparation of a data visualization, to provide a user with recommendations or score values indicative of a quality or complexity of their data visualization.
10 . The non-transitory computer readable storage medium of claim 9 , wherein the method operates as an expert system, or according to a series of processes or rules, to: examine the data visualization as defined by its associated JSON, XML, software code, or metadata; and compare the matrix or list of found elements within the data visualization of interest, with the element types and weighting or amount of point values specified by the analytics data visualization score matrix, and provide recommendations associated with the data visualization.
11 . The non-transitory computer readable storage medium of claim 9 , wherein the data visualization score is displayed within a user interface as a changeable icon and/or score value indicative of a quality and/or complexity associated with the data visualization of interest.
12 . The non-transitory computer readable storage medium of claim 9 , wherein the method is performed by or within a cloud computing or data analytics environment.

Description

CLAIM OF PRIORITY AND CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of priority to U.S. Provisional patent application titled “SYSTEM AND METHOD FOR GENERATING DATA VISUALIZATION SCORES FOR USE WITH A DATA ANALYTICS ENVIRONMENT”, Application No. 63/615,732, filed Dec. 28, 2023; which application and the contents thereof are herein incorporated by reference. COPYRIGHT NOTICE A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever. TECHNICAL FIELD Embodiments described herein are generally related to systems and methods for providing data analytics, and are particularly related to a system and method for generating data visualization scores, for use with data analytics environments. BACKGROUND Data analytics enables computer-based examination of large amounts of data, for example to derive conclusions or other information from the data. For example, business intelligence tools can be used to provide users with business intelligence describing their enterprise data, in a format that enables the users to make strategic business decisions. A data analytics environment may allow users to create data visualizations which reflect a particular set of data or understanding. When creating such data visualizations, users may seek assistance as to whether their data visualization is appropriately designed to illustrate the data, or if the data visualization could perhaps be enhanced or improved in some way. However, although an organization may provide a set of design principles by which a data visualization might be prepared for use within that organization, the assessment of such data visualizations may be somewhat subjective, or based on a user's personal preferences. SUMMARY Embodiments described herein are generally related to systems and methods for generating data visualization scores, for use with data analytics environments. In accordance with an embodiment, the system can operate in the manner of an expert system, or according to a series of processes or rules, to examine a data visualization of interest, compare a list of found elements with element types specified by an analytics data visualization score matrix, and generate, based on matching found elements with the analytics data visualization matrix, a data visualization score associated with the data visualization. In accordance with an embodiment, the system can operate as a data visualization advisor, during preparation of a data visualization, to provide a user with recommendations or score values indicative of a quality or complexity of their data visualization, which may be helpful in improving their data visualization, for example from a beginner-level to a more advanced-level. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 illustrates an example data analytics system or environment, in accordance with an embodiment. FIG. 2 further illustrates an example data analytics environment, in accordance with an embodiment. FIG. 3 further illustrates an example data analytics environment, in accordance with an embodiment. FIG. 4 further illustrates an example data analytics environment, in accordance with an embodiment. FIG. 5 further illustrates an example data analytics environment, in accordance with an embodiment. FIG. 6 further illustrates an example data analytics environment, in accordance with an embodiment. FIG. 7 illustrates the preparation of a data visualization for use with a data analytics environment, in accordance with an embodiment. FIG. 8 further illustrates the preparation of a data visualization for use with a data analytics environment, in accordance with an embodiment. FIG. 9 illustrates the use of analytics data visualization scores, for assessing data visualizations, in accordance with an embodiment. FIG. 10 illustrates a method for generating data visualization scores, for use with data analytics environments, in accordance with an embodiment. FIG. 11 illustrates how the system can be used to generate data visualization scores, in accordance with an embodiment. FIG. 12 further illustrates how the system can be used to generate data visualization scores, in accordance with an embodiment. FIG. 13 illustrates an example use of generating data visualization scores, in accordance with an embodiment. FIG. 14A illustrates another example use of generating data visualization scores, in accordance with an embodiment. FIG. 14B illustrates another example use of generating data visualization scores, in accordance with an embodiment. FIG. 15A illustrates another example use of generating data visualization scores, in accordance with an embodiment. FIG. 15B illustrates another example use of generating data visualizat