Project Data Linkage Across Heterogeneous Database Sources
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Solution Overview
Problem
Existing systems face challenges in efficiently aggregating and analyzing data from disparate sources with different protocols and conventions, particularly in industries like construction management, where real-time tracking of equipment, supplies, and personnel is necessary, and data must be securely ingested, classified, and matched to project-specific data buckets.
Innovation Solution
A data aggregation platform utilizing machine learning algorithms and neural networks for real-time data analysis, securely ingesting data from multiple sources, classifying information, translating data, and matching it to project-specific data buckets, while ensuring privacy and security through role-based access control and secure communication protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is aggregated from multiple independent sources with different protocols and conventions, then data completeness and analytical capability are improved, but data integration complexity and processing time increase
Solution Approach 1:
The patent implements an intermediary layer (data aggregation platform) that sits between multiple independent data sources and the analytical systems. This platform translates diverse data protocols and conventions into a unified format, enabling data aggregation without requiring modification of the source systems. The intermediary handles protocol conversion, data normalization, and integration logic, thereby improving data completeness while containing integration complexity within the platform itself.
Solution Approach 2:
The system segments data integration into distinct modular components: data ingestion modules for each source type, translation layers for protocol conversion, normalization layers for convention alignment, and aggregation modules for combining data. This segmentation allows each component to handle specific data sources independently, reducing overall integration complexity while maintaining comprehensive data aggregation capability.
2Reliability
If data is partitioned across multiple database instances for security and client isolation, then data security and privacy are improved, but data querying and analysis complexity increase
Solution Approach 1:
The patent introduces an intermediary query translation layer that sits between user queries and the partitioned database instances. This layer translates high-level analytical queries into distributed queries across multiple database instances, handling the complexity of data partitioning transparently. Users interact with a unified query interface while the intermediary manages the distributed nature of the database, thereby maintaining data security through partitioning while simplifying query operations.
Solution Approach 2:
The data aggregation platform implements a universal query interface that can handle multiple types of queries across different partitioned database instances through a single unified system. This multi-functional interface provides consistent data access patterns regardless of the underlying database partitioning structure, reducing querying complexity while maintaining security boundaries between client accounts.
3Reliability
If role-based access control is implemented for secure data access, then data privacy and security are improved, but system operation complexity increase
Solution Approach 1:
The patent implements self-service authentication and authorization mechanisms where users automatically receive appropriate access permissions based on their roles and the data they need to access. The system autonomously manages role-based access control policies, authentication tokens, and permission validation without requiring manual intervention for each data access request. This automates security enforcement while maintaining operational simplicity for end users.
Solution Approach 2:
The system performs preliminary authentication and authorization checks before data access operations are executed. User roles, permissions, and access rights are pre-configured and validated in advance, allowing the system to automatically enforce security policies during data operations. This preliminary security setup reduces the operational burden during actual data access while maintaining strong privacy protections.
Data Source
AI summary
Systems, methods, and devices for data ingestion, database management, and data security. A method includes storing a plurality of data entries in a project bucket on a database, wherein the plurality of data entries represents information applicable to a plurality of data units associated with a project. The method includes organizing at least a portion of the plurality of data units according to a polymorphous data schema. The method includes linking two or more data units of the plurality of data units to generate a project linkage. The method further includes restricting a user from removing only a portion of the project linkage from the project without first manually breaking the project linkage.