Corporate Network Visualization for Data Insight
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Solution Overview
Problem
Large-scale corporate networks face challenges in gaining insights from substantial volumes of data, making it difficult to analyze and understand corporate structures, connections, and trends directly.
Innovation Solution
A computer-implemented method and system that transforms corporate data into graphical representations, including nodes based on employee reporting relationships and keyword frequencies, allowing for visual characterization and user-driven adaptations to facilitate network analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If corporate data is stored in databases for internal systems, then data volume and information storage capacity increase, but the ability to gain insights and analyze corporate structures deteriorates
Solution Approach 1:
The patent creates visual copies of corporate data in the form of graphical representations. Instead of analyzing raw database entries directly, the system generates visual copies showing organizational structures, reporting relationships, and network connections. These visual representations make it easier to detect patterns, anomalies, and insights that would be difficult to identify in tabular data formats.
Solution Approach 2:
The patent transforms one-dimensional or two-dimensional tabular data into multi-dimensional visual representations. By displaying corporate data as graphical networks with nodes and edges in spatial arrangements, the system adds dimensional context that reveals structural relationships, hierarchy levels, and connection patterns that are not apparent in traditional database views.
2Loss of information
If detailed corporate information is retained for comprehensive analysis, then information completeness improves, but visualization complexity and computational requirements worsen
Solution Approach 1:
The patent segments corporate data into distinct visual components such as nodes representing employees or departments, and edges representing reporting relationships or collaborations. This segmentation allows the system to process and visualize large datasets by breaking them into manageable graphical elements that can be rendered and analyzed independently, reducing overall system complexity while preserving information completeness.
Solution Approach 2:
The patent implements interactive visualization that allows users to gradually explore data at different levels of detail. Instead of displaying all corporate information simultaneously, the system provides partial views that can be expanded or filtered based on user needs, reducing initial visualization complexity while maintaining the option to access complete information when required.
3Productivity
If graphical visualizations are created to improve data understanding, then insight generation improves, but data processing time and computational resources worsen
Solution Approach 1:
The patent performs preliminary processing of corporate data by pre-computing organizational structures, reporting relationships, and network connections before visualization is requested. This preliminary action includes organizing data into graph structures and calculating key metrics in advance, so that when visualizations are generated, the system can quickly render graphical representations without performing heavy computations at query time, thus reducing processing time while maintaining insight generation efficiency.
Data Source
AI summary
Systems and methods for graphical representation of corporate networks are provided. The graphical representation may be used to present corporate information, e.g., corporate reporting structure, employee keywords, etc. The graphical representation may include nodes whose sizes are based on the corporate data, such as the number of direct reports, or frequencies of keywords appearances. The graphical representation may also include multi-layer corporation information. Further, the graphical representation may present a subset of corporate data in response to user inputs.