Visual Graph Structure for Multi-Database Data Integrity
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Solution Overview
Problem
Existing data ingestion systems struggle to maintain data integrity across multiple databases, particularly when dealing with diverse data formats and ensuring accurate record-keeping for data security, especially in large entities with varied business lines.
Innovation Solution
A system utilizing a dynamic visual graph structure that captures data ingestion information, determines ingestion patterns, generates query sequences for predictive data extraction, and stores data in application databases, while maintaining data integrity through unique session identifiers and integrity counters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored across multiple databases for security and organization, then data security and structure are improved, but data integrity and consistency across databases deteriorate
Solution Approach 1:
The patent segments data into multiple databases organized by business lines and functions, with each database containing specific data subsets. This segmentation enables security isolation while the graph structure maintains integrity across segments through unique session identifiers and foreign key relationships that track data provenance across the distributed system.
Solution Approach 2:
The patent introduces a graph database as an intermediary layer that connects traditional relational databases. This graph structure serves as a mediator that tracks relationships and integrity across multiple databases without requiring direct synchronization between them, using unique session identifiers to maintain consistency across the distributed architecture.
2Quantity of substance
If data is retrieved on-demand from data lakes, then storage efficiency is improved, but data retrieval latency increases
Solution Approach 1:
The patent implements preliminary action by pre-computing and storing metadata about data relationships in the graph database before queries are executed. This allows the system to quickly identify and retrieve only the necessary data subsets from data lakes, rather than scanning entire datasets, thus reducing retrieval latency while maintaining storage efficiency.
Solution Approach 2:
The patent replaces traditional mechanical query execution against flat data lakes with a graph-based navigation system. The graph structure enables efficient traversal and identification of related data through semantic relationships, substituting brute-force data scanning with intelligent path-based retrieval that significantly reduces access time.
3Reliability
If comprehensive data records are maintained for security auditing, then accountability is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal graph structure that serves multiple functions simultaneously: it stores data relationships, maintains audit trails, tracks session integrity, and enables query optimization. This multi-functional approach consolidates what would otherwise require separate systems into a single unified structure, reducing overall system complexity while maintaining comprehensive accountability.
Solution Approach 2:
The patent changes the fundamental parameter of data organization from traditional hierarchical or relational structures to a graph-based structure with unique session identifiers. This parameter change enables the system to maintain comprehensive audit records through the inherent connectivity of the graph, where relationships and provenance are explicitly modeled rather than implicitly tracked, simplifying the auditing mechanism.
4Productivity
If predictive data extraction is implemented, then data retrieval efficiency is improved, but computational overhead increases
Solution Approach 1:
The patent applies partial action by using predictive analytics to identify and pre-retrieve only the subset of data that is likely to be needed based on historical patterns and current query trends. Rather than pre-processing all available data, the system performs partial pre-computation on high-probability data subsets, reducing computational overhead while maintaining improved retrieval efficiency for the most critical data.
Data Source
AI summary
Systems, computer program products, and methods are described herein for dynamic visual graph structure providing multi-stream data integrity and analysis. The present disclosure is configured to provide a reactive system aimed to trace the root cause of incidents and uncover potential gaps in security of an enterprise system. Maintaining accurate and meaningful information related to incidents is the key for success of data security protocols. The integrity of message data is kept intact for improved forensic investigation, as each database may keep varying information related to a single global session.