Data Governance Graph for Interconnection Visualization
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Solution Overview
Problem
Existing data governance systems lack efficient methods for managing and governing digital assets, leading to unnecessary time and resources spent on understanding data interconnections.
Innovation Solution
A computer-implemented method and system for creating a data governance graph that represents interconnections between data sets based on common traits, allowing for improved data management, security, and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional data governance methods are used to manage digital assets, then data management processes can be performed, but unnecessary time and resources are spent on understanding data interconnections
Solution Approach 1:
The patent introduces a data governance graph as an intermediary visual representation that mediates between raw data assets and user understanding. The graph displays nodes representing data assets and edges representing relationships between them, serving as a mediator that makes complex data interconnections visually comprehensible without requiring users to manually analyze the underlying complexity.
Solution Approach 2:
The patent employs visual attributes including color coding to represent different types of data assets, relationships, and governance states in the data governance graph. Different colors help users quickly distinguish between various data categories and relationship types, reducing the time needed to understand data interconnections while maintaining manageable system complexity.
2Productivity
If data governance graph is implemented to visualize data interconnections, then efficiency and understanding are improved, but system complexity increases
Solution Approach 1:
The patent segments the data governance system into distinct components: data assets represented as nodes, relationships represented as edges, and the overall governance graph as a unified visualization. This segmentation allows the system to manage complexity by breaking down the governance structure into manageable, visually distinct elements that can be independently analyzed and understood.
Solution Approach 2:
The patent transforms complex data relationship information from a multi-dimensional data structure into a two-dimensional visual graph representation. By mapping data assets and their interconnections onto a visual plane with nodes and edges, the system enables users to comprehend complex relationships that would be difficult to perceive in tabular or hierarchical formats, thereby improving productivity.
Data Source
AI summary
A method is disclosed for creating a representation of interconnections between datasets using machine learning. The system receives datasets, each having traits, stores the datasets into a catalog, and trains, via an iterative training and testing loop, a ML program utilizing a neural network to generate a trained predictive model, a training dataset utilized during the training of the ML program. The training includes inserting a target variable value and iteratively predicting the target variable via the iterative training and testing loop. The system deploys the model and predicts: (1) a common trait for a first and second dataset; (2) a representation of a first interconnection between the first and second dataset; and (3) a common trait for the second dataset and a third dataset. The system generates a representation of the second interconnection, comprising a second value, displaying a governance graph depicting the first interconnection and the second interconnection.