Automated Graph Generation System for Data Analysis
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Solution Overview
Problem
Generating multiple graphs for large data sets is time-intensive and challenging for data analysts, who often struggle to determine which types of graphs and variables are necessary for analysis.
Innovation Solution
A computer-program product and method that automates the generation of graphs by receiving user input data, obtaining variable selection data, and generating an electronic representation of a graph selection structure to produce compatible graph types, utilizing heuristics to create various graph types based on variable types and metadata, and learning user preferences for customized graph generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a data analyst manually determines and creates multiple graphs for large data sets, then the graphs can be customized and reviewed for quality, but the process is time-intensive and inefficient
Solution Approach 1:
The system performs automated graph generation without requiring manual analyst intervention for each graph. The graph generation engine automatically selects variables, determines appropriate graph types, and creates visualizations based on the data set and user preferences, enabling the system to serve itself in the graph creation process
Solution Approach 2:
The system pre-generates multiple graph types for selected variables before the user needs them. By automatically creating a comprehensive set of graphs in advance based on the data set characteristics and user preferences, the system eliminates the need for time-consuming manual graph creation when analysis is needed
2Adaptability or versatility
If a data analyst manually selects graph types and variables, then the selection can be tailored to specific analysis needs, but it is challenging to determine which combinations are necessary
Solution Approach 1:
The graph selection structure acts as an intermediary between the user's analysis needs and the graph generation process. This structured representation automatically determines compatible graph types for selected variables based on predefined rules and data characteristics, eliminating the complexity of manual selection while ensuring adaptability to different analysis requirements
Solution Approach 2:
The system segments the graph generation process into distinct components: variable selection, graph type determination, and graph creation. By breaking down the complex task of selecting appropriate graphs into manageable segments with clear rules for each, the system reduces overall complexity while maintaining versatility in generating appropriate graph types
Data Source
AI summary
Systems and methods for generating one or more graphs corresponding to a data set are included. A computing system may receive user input data indicating a data set, the data set including one or more variables. Variable selection data indicating a subset of the one or more variables included in the data set may be obtained for the data set. An electronic representation of a graph selection structure may be generated based on the variable selection data. One or more graphs may be generated using the graph selection structure.