Data Aggregation System with Parameter-Based Filtering
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Solution Overview
Problem
There is a need for efficient methods to manage and access data across complex computing networks, particularly in tracking and aggregating data that includes specific parameters, while ensuring data integrity and security.
Innovation Solution
A method and system utilizing computing device processors to receive, store, and analyze data for parameter identification, aggregating data sets based on parameter presence, and generating reports from filtered data, with secure data cloud servers and external sources facilitating data management and access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is aggregated from multiple external sources across complex computing networks, then data completeness and accessibility are improved, but data integrity and security are compromised
Solution Approach 1:
The system performs preliminary analysis of incoming data to assign content information and identify parameters before aggregation. Markers are pre-assigned to data elements based on their parameters, enabling later filtering and validation during aggregation to maintain data integrity while achieving completeness
Solution Approach 2:
The patent introduces an intermediary processing layer that acts as a mediator between external data sources and the aggregation system. This layer analyzes data, assigns markers, and validates content information, serving as a buffer that ensures data integrity while enabling comprehensive data collection from multiple sources
2Quantity of substance
If all data elements are aggregated without filtering, then data volume and completeness are improved, but processing efficiency and report accuracy deteriorate
Solution Approach 1:
The system performs preliminary analysis and marker assignment before aggregation, identifying which data elements contain specific parameters. This pre-processing enables efficient filtering during aggregation, allowing the system to handle large data volumes while maintaining high processing efficiency by only including relevant data elements in final reports
Solution Approach 2:
The patent segments data into categories based on content information and parameters, with markers indicating the presence of specific parameters. This segmentation allows the aggregation process to efficiently select and process only the relevant data segments needed for specific reports, improving overall processing efficiency
3Measurement precision
If data analysis is performed to identify specific parameters in each data element, then data precision and report accuracy are improved, but computational complexity and processing time increase
Solution Approach 1:
The system performs preliminary analysis of data elements to assign content information and identify parameters before aggregation. This pre-processing step, while computationally intensive, is performed once on each data element and enables subsequent rapid filtering and aggregation operations, improving overall efficiency despite the initial computational investment
Solution Approach 2:
The patent creates simplified representations of data elements by assigning markers that indicate the presence of specific parameters. These markers serve as copies or proxies for the full data elements, enabling efficient filtering and aggregation operations without requiring repeated analysis of the complete data elements
Data Source
AI summary
Systems and methods are provided for tracking data in a computer network. An exemplary method includes: storing a first data in the one or more data servers; receiving a first request to aggregate the first data; aggregating a first set of the first data; analyzing one or more fields of each of the first set of the first data; removing the one or more first data elements from the first set of the first data; generating a second set of the first data; aggregating the second set of the first data; retrieving information associated with the aggregation of the second set of the first data; and generating one or more reports using the retrieved information associated with the aggregation of the second set of the first data.