Shared-Dimension Query Semantics for Multi-Fact Visualizations
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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 based on user selections and the relationships between 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 by displaying relationships and disambiguating objects, highlighting relevant fields, and providing informative feedback through tooltips, 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 how data fields are related
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 objects that represent data fields and their relationships, serving as a mediator that organizes complex data from multiple sources into a structured format that is easier to work with and visualize.
Solution Approach 2:
The patent segments complex data from multiple sources into discrete objects within an object model. Each object represents a specific data field or entity, and relationships between objects represent relationships between data fields. This segmentation makes it clearer how data fields are related and how to generate appropriate visualizations.
2Device complexity
If analysis is restricted to a single set of facts, then the complexity of the system is reduced, but the ability to ask sophisticated analytic questions is limited
Solution Approach 1:
The patent creates a universal object model that can represent multiple sets of facts and their relationships in a unified structure. This object model serves multiple functions: it can represent single-fact scenarios simply, and can represent complex multi-fact scenarios with sophisticated relationships, making the system adaptable to various analytic needs without requiring separate systems for each case.
3Loss of information
If data models span multiple fact tables, then a holistic understanding of data is achieved, but the maintenance burden on data stewards increases
Solution Approach 1:
The patent uses object models as copies or representations of the underlying data structure. Instead of directly managing complex relationships between multiple fact tables, data stewards work with the simplified object model copy that mirrors the essential relationships. This copying approach maintains data integrity while reducing the complexity of maintenance tasks.
4Loss of information
If the user interface displays detailed relationships in multi-fact data models, then the information provided to users is improved, but the interface becomes more complex
Solution Approach 1:
The patent applies local quality by providing detailed relationship information contextually within the interface rather than displaying all relationships simultaneously. The interface adapts to show relevant relationship details based on user interactions and current context, providing high information quality where needed without overwhelming the user with unnecessary complexity elsewhere.
Data Source
AI summary
A computing device receives user input specifying a first dimension data field and a second dimension data field that are associated with different objects in an object model, for generating a first data visualization. The device constructs a dimension subquery. The device executes the dimension subquery to retrieve first tuples. The device constructs one or more measure subqueries. Each of the measure subqueries references one or more measure data fields in the object model and the one or more measure data fields include at least a shared measure data field. The device executes the measure subqueries to retrieve second tuples. The second tuples include data values corresponding to the shared measure data field. The device forms extended tuples by combining the retrieved first tuples and the retrieved second tuples. The device also generates and causes display of the first data visualization according to the extended tuples.