Data Table Transformer Multi-Dimensional Projection
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Solution Overview
Problem
Existing data display technologies struggle to present relational data in a multi-dimensional, cross-tabular format, limiting user control over data presentation and analysis, as they often require server-side or database applications to manage data aggregation and visualization.
Innovation Solution
A data table transformer module that receives input data as rows with attributes, designates zero-based edges, and distributes values to an edge tree for a multi-dimensional display, allowing user applications to choose data presentation and aggregation, enabling expansion and collapse of layers for detailed analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If server-side or database applications are used to manage data aggregation and visualization, then data can be presented in traditional tabular format, but user control over data presentation and analysis is limited
Solution Approach 1:
The patent extracts the data transformation functionality from server-side applications and database systems, placing it directly in the client application. This allows users to control data presentation locally without relying on complex server-side processing, thereby improving adaptability while reducing system architecture complexity
Solution Approach 2:
The client application performs data aggregation and transformation operations independently using the transformation module. This self-service capability eliminates the need for server-side mediation, giving users direct control over how data is presented and analyzed
2Adaptability or versatility
If relational data is displayed in traditional tables with rows and columns, then data structure is simple, but multi-dimensional analysis and drill-down capabilities are limited
Solution Approach 1:
The transformation module converts traditional two-dimensional tabular data into multi-dimensional presentations with hierarchical groupings. Users can drill down through multiple levels of data organization, adding dimensional depth to flat relational data structures
Solution Approach 2:
The patent segments data into hierarchical groups and sub-groups that can be independently explored. This segmentation enables multi-dimensional analysis by organizing data into manageable, navigable units that reveal patterns across different dimensions
3Measurement precision
If data is presented in detailed format, then analysis precision is high, but data volume and processing time increase
Solution Approach 1:
The transformation module dynamically adjusts data presentation based on user interaction. Data can be aggregated at higher levels for quick overview or expanded to detailed levels for precise analysis, optimizing processing time based on the required precision at each moment
Data Source
AI summary
A data table transformer includes a data receiving module configured to receive a set of rows, each row with a set of attributes, as input data. The data receiving module is also configured to receive locations for at least some of the attributes as zero-based edges. Layers of the edge are presented from the slowest to the fastest varying layers. The data receiving module is further configured to receive a designation of data values that appear at intersections of edge attributes from the same row. The data table transformer is also configured to walk input data by row and for each edge attribute, to distribute the value of the edge attribute to an edge tree created for each zero-based edge location. The data table transformer is further configured to display the data with a multi-dimensional, crosstabular display.