Dynamic Intelligent Code Change System for ETL Automation
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Solution Overview
Problem
The existing ETL process faces challenges in dynamically implementing intelligent code changes across multiple target systems, especially when dealing with large volumes of data and multiple source systems, as it requires manual configuration and lacks efficient mechanisms for predicting and managing data transformation impacts on source systems.
Innovation Solution
A system is developed that dynamically implements intelligent code changes by receiving data transformation requests, extracting and transforming source code based on protocols, and utilizing blockchain technology to store and manage system states, allowing for concurrent transformations and state reversion analysis, thereby automating the process and predicting impacts on target and source systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual configuration is used for code changes in each target application, then implementation control is maintained, but the process becomes time-consuming and inefficient when dealing with multiple target systems
Solution Approach 1:
The patent uses templates to store predefined code change patterns that can be copied and applied across multiple target applications. Instead of manually configuring each target system individually, the system creates a master template that can be replicated and adapted to numerous target applications, dramatically improving implementation efficiency while reducing the complexity of configuring each system separately
Solution Approach 2:
The patent implements a universal template-based code change system that can serve multiple target applications simultaneously. A single template design can be applied across different target systems with minimal customization, allowing the same mechanism to handle diverse code change scenarios across multiple applications, thereby improving productivity without proportionally increasing system complexity
2Adaptability or versatility
If data transformation is implemented across multiple source systems, then data consolidation capability is improved, but the impact prediction and management complexity increases
Solution Approach 1:
The patent performs impact prediction and analysis before actually implementing data transformation across multiple source systems. By conducting preliminary impact assessments, the system identifies potential issues and dependencies in advance, allowing for better planning and execution of data consolidation across multiple systems without overwhelming complexity during the actual transformation process
Solution Approach 2:
The patent divides the impact prediction process into separate, manageable components that can be applied to each source system individually. Rather than attempting to predict impacts across all source systems simultaneously, the system segments the analysis into discrete units that can be processed independently and then aggregated, reducing the overall complexity while maintaining comprehensive adaptability across multiple systems
Data Source
AI summary
Systems, computer program products, and methods are described herein for data transformation prediction and code change analysis. The present invention is configured to electronically receive one or more data transformation protocols; electronically extract data from a first source system based on at least receiving the one or more data transformation protocols; determine the one or more target systems associated with the data transformation request; extract a source code associated with each of the one or more target applications; transform the source code associated with each of the one or more target applications based on at least the one or more data transformation protocols; and implement the one or more changes to the one or more target systems based on at least transforming the source code associated with each of the one or more target applications.