Dynamic Graph Models for Interactive Relational Data Analysis
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Solution Overview
Problem
Organizations face challenges in effectively utilizing vast collections of data due to its form or shape, which may hinder effective visualization and analysis, impacting business practices.
Innovation Solution
A system for dynamic graph generation that includes a graphical user interface with a graph panel and visualization panel, utilizing data models, transform models, and graph models to generate interactive data visualizations that can represent relationships not explicitly in the data model, allowing for user interaction and query execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is provided in a fixed form or shape for one type of analysis, then that specific analysis can be performed effectively, but the data becomes disadvantageous for other types of analysis
Solution Approach 1:
The system dynamically transforms data between different forms (relational, hierarchical, network) based on user interaction and analysis needs. The graph model generation is not static but adapts in real-time to user queries and selections, allowing the same data to be represented in multiple structural forms without manual reconfiguration.
Solution Approach 2:
The system creates a universal graph model that can serve multiple analysis purposes simultaneously. By generating graph representations from relational data that preserve both hierarchical and network relationships, the system enables diverse analysis types (hierarchical analysis, network analysis, exploratory analysis) from a single data structure.
2Loss of information
If traditional visualization methods are used on vast data collections, then data can be displayed, but effective utilization and understanding of business operations is hindered
Solution Approach 1:
The system transitions from traditional flat tabular visualizations to multi-dimensional graph representations. By mapping relational data onto graph structures with nodes and edges, the system adds spatial and relational dimensions to data visualization, making hidden patterns, connections, and hierarchies visually apparent that are invisible in traditional formats.
Solution Approach 2:
The graph model acts as an intermediary between raw relational data and user comprehension. It transforms complex relational structures into intuitive visual representations where relationships are explicitly shown through nodes and edges, serving as a bridge that makes vast data collections accessible and interpretable.
3Reliability
If data relationships are not explicitly represented in the data model, then data storage is simplified, but relationships cannot be effectively analyzed or visualized
Solution Approach 1:
The system performs preliminary transformation of relational data into graph models that pre-establish relationship representations. By converting relational schemas into graph structures in advance, the system prepares data for relationship analysis without requiring complex queries or transformations at the time of analysis, making relationships immediately accessible and analyzable.
Data Source
AI summary
Embodiments are directed to visualizing data using a graphical user interface (GUI) that may include a graph panel and a visualization panel arranged to receive inputs or interactions. A data model may be provided and displayed in the visualization panel. Input information that specifies portions of the data model may be provided to the visualization panel. Transform models may be determined based on the specified portions of the data model such that the determined transform models include a model interface that accepts the input information. The transform models may be employed to generate graph objects based on the data model, the input information such that the graph objects may be included in a graph model. Queries based on the graph model may be executed to provide results from the data model such that the results may be displayed in a visualization.