Overlay Visualizations Using Data Layer UNION Queries

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Solution Overview

Problem

Conventional data visualization methods struggle to plot multiple dimensions from the same value set on a shared axis, leading to increased complexity and resource consumption, especially when data updates require regenerating and superimposing visualizations.

Innovation Solution

Implementing overlay visualizations by executing queries that combine subqueries using operations like UNION or FULL OUTER JOIN, allowing a measure to be plotted along a common axis with different dimensions differentiated through constant formula fields for visualization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If conventional visualization methods are used to plot multiple dimensions on separate charts and then superimpose them, then multiple dimensions can be visualized, but device complexity and resource consumption increase significantly

Engineering Contradiction:

Improveability to plot multiple dimensionsVSAvoidvisualization complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent merges multiple separate dimension visualizations into a single unified chart by combining multiple subqueries using SQL operations (UNION, FULL OUTER JOIN). This allows multiple dimensions to be plotted on the same axes simultaneously, eliminating the need to create and superimpose separate charts, thus reducing visualization complexity while maintaining the ability to display multiple dimensions.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent creates a universal query structure that can handle multiple dimensions from different value sets through a standardized approach using constant formula fields and SQL operations. This multi-functional query template can accommodate various dimension combinations without requiring separate visualization logic for each case, reducing overall system complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Loss of information

If separate charts are generated and superimposed to display multiple dimensions, then multiple dimensions can be compared, but processing resources are consumed significantly

Engineering Contradiction:

Improvedimension comparison capabilityVSAvoidprocessing resource consumption

Core Design Contradiction:

Loss of informationVSUse of energy by moving object

Solution Approach 1:

The patent combines multiple dimension data streams into a single query result set using SQL UNION and FULL OUTER JOIN operations. This consolidation allows the visualization layer to process and display multiple dimensions in one chart rather than generating and merging multiple separate charts, significantly reducing processing resource consumption while preserving full dimension comparison capability.

Inventive Principle:

Principle #5Merging (Combining)

3Reliability

If data is updated in the data layer, then data freshness is improved, but the visualization layer must regenerate and superimpose charts which increases time consumption

Engineering Contradiction:

Improvedata freshnessVSAvoidvisualization regeneration time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent establishes a preliminary unified query structure that combines multiple dimensions using SQL operations. This pre-configured query template can be efficiently re-executed when data updates occur, avoiding the need to regenerate and superimpose multiple separate charts. The standardized query structure enables faster data refresh cycles while maintaining data freshness.

Inventive Principle:

Principle #10Preliminary action

4Adaptability or versatility

If multiple subqueries are combined using UNION or FULL OUTER JOIN, then multiple dimensions can be plotted on a common axis, but query complexity increases

Engineering Contradiction:

Improvemulti-dimensional plotting capabilityVSAvoidquery structure complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments the multi-dimensional visualization problem into separate subqueries, each handling a specific dimension. By using SQL UNION and FULL OUTER JOIN operations to combine these segmented subqueries, the system achieves flexible multi-dimensional plotting on a common axis. The segmentation approach makes the complex query structure manageable and maintainable while preserving adaptability.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS10529099B2Overlay visualizations utilizing data layer

Publication Date: 2020.01.07 SAP SE

AI summary

Overlay visualizations are implemented utilizing data of a data layer. A table comprises a measure and two or more different dimensions mapping to a same value range. For visualization, the measure for those dimensions may be plotted along a common axis in a same chart. Accordingly, a query executes a UNION of multiple subqueries. A first subquery aggregates the first dimension over the value range, injecting a constant formula field to identify the original first dimension. A second subquery aggregates the second dimension over the value range, again injecting the constant formula field to identify the original second dimension. UNION of these subquery results presents one larger dataset for input to the overlying visualization layer. The constant formula field may be relied upon to differentiate between the combined dimensions on the common axis, allowing association of the measure values with the original dimensions in the displayed plot (e.g., via coloring).