Nodal Data Tables for Interactive Large-Scale Data Visualization
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Solution Overview
Problem
Conventional data analysis methods struggle with efficiently navigating and visualizing large volumes of structured and unstructured data due to high processing power requirements and lack of systematic approaches, leading to inefficient decision-making and data navigation burdens on users.
Innovation Solution
A method and system that parse data into domain and dimension tables, generate nodal networks with metadata-linked nodes, and display data on a graphical user interface, allowing interactive visualization and clustering of data based on user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional data analysis methods are used to analyze large volumes of data, then data analysis can be performed, but high processing power and computing resources are required
Solution Approach 1:
The patent segments large volumes of data into structured data tables with specific schemas and nodal networks with defined nodes and relationships. This segmentation organizes data into manageable units that can be processed more efficiently, reducing the computational resources required to analyze large datasets while maintaining the ability to handle substantial data volumes.
2Ease of operation
If conventional visualization tools are used to navigate large volumes of data, then data can be displayed, but the burden of data navigation is shifted to users and the approach is not systematic
Solution Approach 1:
The patent implements self-service through automated data parsing into structured tables, automatic generation of nodal networks from the structured data, and automated linking of nodes based on relationships defined in the structured data. This eliminates the need for users to manually navigate complex data structures, as the system automatically organizes and presents data in an intuitive visual format, reducing the navigation burden while providing a systematic approach.
3Loss of information
If existing online tools are used to identify insights in data, then insights can be found, but managing information on different platforms is difficult due to number, size, content, or relationships of the structured and/or unstructured data
Solution Approach 1:
The patent creates a universal data structure that can accommodate various types of data (structured and unstructured) with unified schemas and a standardized nodal network format. This universal approach allows information from different sources and platforms to be managed consistently through a single system, eliminating the complexity of managing multiple platforms while preserving all information regardless of its original format or source.
Data Source
AI summary
Disclosed are methods and computer systems to generate, update, traverse, and analyze a nodal data structure based on data associated with an entity. The methods and systems disclosed herein describe a server that can generate and link various nodes in a nodal network and parse data into unique data tables. The server then displays a web document having a set of words where each word corresponds to a data table. When a user interacts with a word within the web document, the server identifies a set of nodes associated with the word with which the user has interacted. The server then executes one or more analytical protocols using the identified nodes and displays the results.