Multi-Fact Data Modeling With Visual Relationship Guidance
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Solution Overview
Problem
Current data visualization applications struggle with complex data sources and multiple data sources, making it unclear how to generate appropriate visualizations and relate data fields, limiting analysis to a single set of facts and imposing maintenance burdens on data stewards.
Innovation Solution
A computing device with an improved user interface facilitates the creation and analysis of multi-fact data models, providing visual feedback, disambiguation of relationships, and guiding analysts through relevant field selection using grayed-out and explained irrelevant fields, while supporting query semantics compatible with Tableau's VizQL for sophisticated analytic questions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data visualization applications support multiple data sources and complex data sources, then the comprehensiveness of data analysis is improved, but it becomes unclear how to generate appropriate visualizations and relate data fields
Solution Approach 1:
The patent introduces an object model as an intermediary layer between multiple data sources and the visualization interface. This object model contains classes that represent data sources, data fields, and their relationships, providing a unified semantic framework that simplifies how users interact with complex multi-source data while maintaining comprehensive data analysis capabilities
2Device complexity
If analysis is restricted to a single set of facts, then the complexity of data modeling is reduced, but the ability to answer sophisticated analytic questions is limited
Solution Approach 1:
The patent creates a universal object model framework that can handle multiple fact sets through a common class structure. The data source class, data field class, and their relationship mechanisms are designed to be multi-functional, supporting both single-fact and multi-fact scenarios within the same system, thereby enabling sophisticated analytics without proportionally increasing modeling complexity
3Loss of information
If data models span multiple fact tables, then the completeness of data picture is improved, but the maintenance burden on data stewards increases
Solution Approach 1:
The patent implements automated validation mechanisms within the object model that check relationships between data sources and data fields. This self-validation capability reduces the manual maintenance burden on data stewards by automatically detecting and reporting inconsistencies in multi-fact data models, while still achieving complete data pictures across multiple fact tables
Data Source
AI summary
A computing device displays a first object icon representing a first object of a first data source and a second object icon, representing a second object of the first data source. The first object icon is connected to the second object icon via a first connector representing a relationship between the first object and the second object. In response to receiving a first user input to add a third object, the computing device displays a third object icon representing the third object. In response to receiving a second user input on the third object icon, in accordance with a determination that the second object and the third object include at least one common data field, the computing device displays a second connector, connecting the third object icon to the second object icon.