Data Store Architecture Detection for Automatic Change Tracking
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Solution Overview
Problem
Existing data store architectures are often inaccurately represented due to lack of updates in initial design documents, leading to incorrect operations and suboptimal performance, especially when multiple applications modify the architecture without updating the documentation.
Innovation Solution
A complementary system comprising a 'Data Store Analyzer' module that automatically recognizes and tracks data store architecture changes by analyzing data store structure and user queries, generating an approximation of the architecture without requiring prior query knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If initial design documents are used to represent data store architecture, then the architecture information is available at the initial stage, but the documents become inaccurate and outdated when multiple applications modify the architecture
Solution Approach 1:
The system automatically detects and tracks data store architecture changes by analyzing data store structures and user queries without requiring manual intervention. The architecture approximation is generated and updated autonomously, eliminating the need for manual documentation updates while maintaining accuracy despite multiple application modifications
Solution Approach 2:
The system continuously monitors the data store and compares actual architecture with the recorded approximation, detecting discrepancies and automatically updating the architecture information. This feedback mechanism ensures the documentation remains synchronized with the actual data store state without manual intervention
2Measurement precision
If manual tracking of architecture changes is performed, then the initial design document can be maintained, but human effort is extremely high and updates are delayed
Solution Approach 1:
The system replaces manual mechanical processes of architecture tracking with automated computational analysis. By using software to analyze data store structures and generate architecture approximations, the system achieves both high precision in detecting architectural changes and high speed in updating the documentation, eliminating the trade-off between accuracy and productivity
Solution Approach 2:
The system introduces an intermediary architecture approximation that serves as an automatic representation of the data store structure. This intermediary is continuously updated through automated analysis of data store schemas and queries, providing accurate and timely architecture information without requiring direct manual intervention
3Adaptability or versatility
If standard data management tools are used, then simple company requirements are satisfied, but sophisticated data store management needs cannot be met
Solution Approach 1:
The system provides multi-functional capabilities that work across different data store types and complexity levels. It can automatically generate architecture approximations for simple data stores while also handling complex scenarios involving multiple applications and frequent modifications, making it adaptable to both basic and sophisticated data store management needs without requiring separate specialized tools
Data Source
AI summary
A system is configured for automatic recognition of data store architecture and tracking dynamic changes and evolution in data store architecture. The system is a complementary system, which can be added onto an existing data store system using the existing interfaces or can be integrated with a data store system. The system comprises three main components that are configured to compose an approximation of the data store architecture. The first of these components is adapted to execute an analysis of the architecture of the data store; the second of the components is adapted to collect and compile statistics from said data store; and the third of the components is adapted to compose an approximation of the architecture of said data store.


