Dynamic Hierarchical Data Visualization for Drilldown Analysis
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Solution Overview
Problem
Existing visual data comparison techniques, such as simple bar charts and pie charts, are inadequate for effectively analyzing large amounts of business data, as they fail to reveal data distribution, patterns, correlations, and detailed information.
Innovation Solution
A method involving a multi-level dynamic hierarchical structure that automatically computes graphical visual comparisons using drilldown sequences, allowing users to derive and display both aggregated and data distribution paradigms through graphical illustrations, such as multi-pixel bar charts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If simple graphical techniques (bar charts, pie charts) are used to display data, then ease of use is improved, but information completeness deteriorates as they show only highly aggregated data while omitting data distribution, patterns, correlations, and detailed information
Solution Approach 1:
The patent divides data visualization into multiple hierarchical levels, where each level segments different aspects of the data. The first level shows aggregated data through bar charts, while subsequent levels segment and display data distribution, patterns, and detailed information through additional graphical illustrations, allowing users to explore data at progressively finer granularities without losing overall context
Solution Approach 2:
The patent implements a nested structure where multiple graphical illustrations are layered within a unified visualization framework. Each graphical illustration is nested at a specific hierarchical level, with lower-level details embedded within the context of higher-level aggregations, enabling simultaneous display of both summary and detailed information in an organized manner
2Loss of information
If multiple graphical illustrations are displayed simultaneously to show aggregated and data distribution paradigms, then information completeness is improved, but device complexity increases
Solution Approach 1:
The patent implements dynamic interactivity where users can drill down through hierarchical levels by selecting specific data elements. The system dynamically generates and displays appropriate graphical illustrations based on user actions, transitioning between aggregated and detailed views. This dynamic approach allows the system to maintain simplicity at any given moment while providing access to comprehensive information through user-guided exploration
Solution Approach 2:
The patent adds a hierarchical dimension to data visualization, organizing multiple graphical illustrations across different levels rather than displaying them all simultaneously in a single plane. This dimensional organization allows the system to present comprehensive information while maintaining clarity, as users navigate through levels rather than being overwhelmed by simultaneous displays of all data aspects
3Measurement precision
If detailed information is displayed to reveal data distribution and patterns, then measurement precision is improved, but ease of operation deteriorates due to increased complexity in navigating and interpreting multiple graphical illustrations
Solution Approach 1:
The patent performs preliminary organization of data into hierarchical levels before display, pre-computing and structuring aggregated data, data distribution, and detailed information into distinct graphical illustrations. This preliminary preparation allows users to access detailed information through simple drill-down actions rather than requiring complex queries or interpretations, maintaining ease of use while providing precise data analysis capabilities
Data Source
AI summary
A method for presenting data comprises receiving the data; and deriving a multi-level dynamic hierarchical structure for the data based on drilldown sequences input from a user, wherein the drilldown sequences automatically compute a graphical visual comparison of the data and comprise: deriving a multi-pixel bar chart to display an aggregated data paradigm; and deriving a graphical illustration to display a data distribution paradigm.