Composite Data Values for Heterogeneous Database Correlation
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Solution Overview
Problem
Conventional database management systems struggle to efficiently organize and structure heterogeneous data from multiple sources due to varying data formats and inconsistent collection intervals, leading to fragmented information storage and increased computational overhead, and user interface systems require complex query operations and inefficient resource utilization.
Innovation Solution
A data processing engine that implements data correlation algorithms to establish relationships between disparate data points, calculating a composite data value representing aggregated system performance, and an optimized UI rendering system that positions graphical elements based on numerical magnitude, reducing computational overhead and improving user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional database management systems store heterogeneous data from multiple sources, then data from various sources can be retained, but the data becomes fragmented and requires complex query operations with multiple database joins
Solution Approach 1:
The patent combines multiple disparate data sources and their corresponding tables into a single unified data lake structure. Instead of maintaining separate database tables for different data sources, the system consolidates all operational data into one unified storage structure, eliminating the need for complex multi-table join operations while preserving the ability to store heterogeneous data from multiple sources
2Loss of information
If manual data reconciliation processes are used to correlate information from different sources, then data relationships can be established, but substantial processing time and system memory are consumed
Solution Approach 1:
The system performs preliminary data correlation by organizing all operational data into a unified data lake structure in advance, with data points pre-associated with their contextual relationships. This preliminary organization eliminates the need for time-consuming manual reconciliation processes, as data relationships are already established through the unified structure rather than requiring subsequent processing
Solution Approach 2:
The unified data lake acts as an intermediary structure between disparate data sources and query operations. Instead of directly correlating data from multiple separate sources through complex joins or manual processes, the unified data lake provides a single intermediate storage layer where all data relationships are already established, enabling efficient retrieval without substantial processing time
3Quantity of substance
If conventional systems store operational data from multiple sources, then comprehensive data is available, but system resource utilization becomes inefficient due to fragmented storage
Solution Approach 1:
The patent merges fragmented data storage across multiple sources into a single unified data lake, consolidating all operational data into one efficient storage structure. This consolidation maintains the comprehensive quantity of operational data while dramatically improving system resource utilization efficiency by eliminating redundant storage and simplifying data access operations
Data Source
AI summary
Examples provide a system, method, and computer storage medium for generating composite data values from heterogeneous database sources and rendering them in a user interface display. The system includes a processor and a computer-readable medium storing instructions. The instructions, upon execution, enable the system to automatically receive operational performance data from multiple database sources, identify a plurality of data correlation patterns within the operational performance data, and calculate weighting coefficients for the plurality of data correlation patterns using a computational analysis module. The composite data value is calculated based on the weighted data correlation patterns and rendered as a graphical interface element in a user interface display. The graphical interface element is automatically positioned at a calculated location within the user interface display based on a numerical magnitude of the composite data value.