Automated Drill Path Creation for Data Visualization Analysis
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Solution Overview
Problem
Users face challenges in creating and documenting drill paths for data analysis, which can be time-consuming and often results in incomplete exploration of data visualizations and resources, making it difficult to recover intermediate steps and present analysis effectively.
Innovation Solution
The system automatically creates drill paths by suggesting relevant data visualizations and resources based on criteria such as data values, types, and user selections, allowing for iterative exploration and recording of analysis paths for playback and sharing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually create drill paths by looking up data, then they can explore data visualizations, but it consumes significant time and may result in incomplete exploration
Solution Approach 1:
The system pre-generates multiple potential drill paths and data visualizations in advance, so when a user starts an analysis, ready-made paths are immediately available for selection rather than requiring real-time manual creation
Solution Approach 2:
The system automatically generates drill paths and suggests next steps in the analysis process without requiring manual intervention, allowing the analysis workflow to proceed autonomously while the user reviews and selects options
2Loss of information
If users manually document analysis steps, then they can recover intermediate steps, but it requires careful record keeping and is time-consuming
Solution Approach 1:
The system automatically records and preserves the complete drill path and intermediate analysis steps as the analysis progresses, so all intermediate steps are captured without requiring manual documentation at each stage
Solution Approach 2:
The system provides automatic feedback by tracking and storing the user's navigation path through data visualizations, making the complete analysis journey recoverable and shareable without additional user effort
3Adaptability or versatility
If users manually explore data visualizations, then they can find relevant information, but they may miss highly relevant data visualizations and resources
Solution Approach 1:
The system autonomously generates and suggests relevant data visualizations and drill paths based on the current analysis context, expanding the exploration beyond what a user might manually discover while maintaining relevance to the analysis goals
Solution Approach 2:
The system generates multiple potential drill paths and data visualization options beyond what a single manual path would provide, allowing users to select from several relevant directions rather than following one predetermined route
Data Source
AI summary
A data analysis system may automatically suggest data visualizations to a user. A primary data visualization may be displayed to graphically illustrate a primary data set of a database. Criteria may be automatically applied to the database to identify a secondary data set that meets the criteria. A secondary data visualization that graphically illustrates the secondary data visualization and/or a corresponding indicator may be displayed. Multiple visualizations and/or indicators may be displayed, and the user may select one for viewing. The criteria may again be applied to the database to identify a tertiary data set. An analysis path may be recorded to enable the user to easily view the decisions made and/or the data visualizations viewed. The criteria may include determination that the secondary data set has the desired amount of data, has unique data types or descriptors, includes data previously selected by the user, or the like.