Dynamic Linked Panels for Data Visualization
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Solution Overview
Problem
Existing systems struggle to efficiently integrate, analyze, and visualize large volumes of data from various sources in a user interface, particularly in managing queries and display settings across multiple panels, and securely writing data to these sources.
Innovation Solution
A system that generates a user interface with dynamic panels, allowing linked queries and display settings, and uses template engines with custom functions to securely write data to diverse data sources, ensuring parameterized queries to prevent SQL injection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple panels with queries and display settings are integrated in a user interface, then data visualization capability is improved, but system complexity increases
Solution Approach 1:
The system divides the user interface into multiple independent panels, each capable of executing its own query and displaying results. Each panel is a self-contained unit with query logic, display settings, and result presentation, allowing the system to handle complex data visualization tasks through modular components rather than a monolithic structure.
Solution Approach 2:
Each panel in the system is designed to be multi-functional, capable of executing queries, processing results, and displaying data in various formats. The panels can serve multiple purposes including data exploration, analysis, and presentation, reducing the need for separate specialized components for each function.
2Loss of information
If panels are linked through shared variables and queries, then data integration is improved, but query execution time increases
Solution Approach 1:
The system pre-loads and caches query results when possible, and maintains shared variables across panels that can be quickly referenced without re-executing queries. When panels are linked through shared variables, the system checks for cached results first before executing queries, reducing redundant computation and execution time.
Solution Approach 2:
The system merges query execution across linked panels by identifying shared variables and consolidating query operations. When multiple panels reference the same variables or data sources, the system executes the query once and shares the results across all dependent panels, reducing total execution time while maintaining data integration.
3Reliability
If parameterized queries are used to prevent SQL injection, then security is improved, but query processing complexity increases
Solution Approach 1:
The system introduces an intermediary layer between user input and query execution that automatically parameterizes queries. This intermediary component handles the complexity of SQL injection prevention by intercepting user inputs, converting them into parameterized query forms, and managing the mapping between user-friendly parameters and database query parameters, thereby shielding users from complexity while maintaining security.
Data Source
AI summary
A computer system may be configured to: execute a first query associated with a first panel; display the first panel in a user interface based on first display settings of the first panel, the first panel displaying at least a portion of the result of the first query, the result of the first query associated with a variable; execute a second query associated with a second panel, wherein the second query refers to the variable associated with the first query; display the second panel in the user interface based on second display settings of the second panel, the second panel displaying at least a portion of the result of the second query; and in response to user input changing the displayed result in the first panel: re-execute the second query; and update the display of the second panel in the user interface based on results of the re-executed second query.