Row-Level Calculation Tabs for Multi-Table Data Visualization
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Solution Overview
Problem
Existing data visualization applications struggle with generating accurate visualizations from complex or multiple data sources, often omitting rows of data and failing to meet user expectations due to unclear data relationships and insufficient Level of Detail (LOD) specifications.
Innovation Solution
An object model is constructed to represent data relationships, allowing the data visualization application to recommend additional fields, limit actions, and generate visualizations based on user selections, with features like separate tabs for aggregate measures and disaggregated level of detail displays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single Level of Detail (LOD) is specified for data visualization, then the visualization can be generated, but it is insufficient to build certain complex calculations across multiple data tables
Solution Approach 1:
The patent divides the single LOD specification into multiple LOD expressions, allowing different levels of detail to be specified for different data tables. This enables complex calculations across multiple tables by segmenting the LOD requirement into table-specific specifications, resolving the limitation of using a single LOD for all tables.
2Reliability
If data visualizations are generated from complex or multiple data sources, then more comprehensive data analysis is enabled, but rows of data are often omitted and user expectations are not met
Solution Approach 1:
The patent implements a feedback mechanism by displaying both the aggregate measures and the disaggregated level of detail in the visualization. This allows users to verify data completeness and understand how aggregate values are derived from individual rows, ensuring that no data is omitted and user expectations are met while handling complex data sources.
3Ease of operation
If aggregate measures are displayed without disaggregated level of detail, then the visualization is simplified, but user understanding of data relationships is reduced
Solution Approach 1:
The patent applies the nesting principle by embedding disaggregated level of detail within the aggregate measure display. The visualization maintains its simplified aggregate view while nesting detailed row-level information that can be accessed when needed, preserving both simplicity and information completeness about data relationships.
Data Source
AI summary
A computer system displays a data visualization in a data visualization user interface. In response to detecting a user input that selects a subset of visual data marks from the data visualization, the computer system displays a summary of the selected subset of visual data marks in a summary tab of a view data window. When the computer system determines that the selected subset of visual marks (1) corresponds to a plurality of data fields and (2) references a row-level calculation that uses logical fields from at least two logical tables of a plurality of logical tables of a data model, the computer system (i) generates a representation of the row-level calculation and (ii) displays the representation of the row-level calculation as a first tab in the view data window, distinct from the summary tab.