Data Visualization with Nested Aggregation Levels for Complex Analysis
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Solution Overview
Problem
Existing data visualization applications often require a single Level of Detail (LOD) for aggregate calculations, which is insufficient for complex data analysis, limiting the ability to understand distribution, trends, and outliers effectively.
Innovation Solution
Implementing a system that allows users to specify multiple levels of detail through an interactive graphical user interface, enabling data visualization with two or more aggregations based on different levels of detail, where the output of one aggregation can be referenced or aggregated again in the next, and using operators like SUM, COUNT, MIN, MAX, AVG, MEDIAN, STDEV, VAR, PERCENTILE, ATTR, STDEVP, and VARP to analyze data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single Level of Detail is specified for aggregate calculations, then the data visualization is simple to generate, but it is insufficient for complex data analysis
Solution Approach 1:
The patent divides the aggregation process into multiple distinct levels (first aggregation level and second aggregation level), each with its own grouping fields and aggregation operations. This segmentation allows complex data analysis to be broken down into manageable hierarchical stages, where each level processes data at a different granularity without overwhelming the system with a single monolithic aggregation specification.
Solution Approach 2:
The patent implements nested aggregations where the output of the first aggregation becomes an input for the second aggregation. The first aggregation groups data by a first set of fields and produces aggregated output, which is then further aggregated by a second set of fields in the second aggregation. This nesting structure enables multi-dimensional analysis while maintaining a structured, hierarchical approach that manages complexity through organized layers of processing.
2Loss of information
If multiple levels of detail are specified, then comprehensive data analysis is enabled, but the system complexity increases
Solution Approach 1:
The patent adds a temporal or hierarchical dimension to the aggregation process by introducing multiple aggregation levels executed in sequence. Instead of a single flat aggregation operation, the system performs first aggregation at one level of detail and then applies a second aggregation at a different level of detail, effectively adding a dimensional layer to the data processing that preserves information across different granularities while structuring the complexity through defined processing stages.
3Adaptability or versatility
If a single aggregation is used, then the visualization is quick to generate, but it cannot represent complex data structures
Solution Approach 1:
The patent performs preliminary aggregation operations in a defined sequence, where the first aggregation is executed and its results are prepared as input for the second aggregation. This preliminary action approach allows the system to pre-process data at intermediate levels, organizing complex data structures into manageable formats before final visualization, thereby enabling representation of complex data while maintaining efficiency through structured pre-processing stages.
Data Source
AI summary
A computer system displays a graphical user interface that includes a data visualization region, a shelf region, and a schema information region. The computer system receives a first user input to place a first dimension data field from the schema information region into the shelf region. In accordance with the first user input, the computer system determines a visualization level of detail that is based on at least the first dimension data field. The computer system receives a second user input to specify a first aggregation. The first aggregation has a custom level of detail that is distinct from the visualization level of detail. The computer system builds a visual specification that includes the visualization and custom levels of detail. The computer system generates a data visualization corresponding to the visual specification and displays the data visualization in the data visualization region.