Data Transformation Impact Prediction System
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Solution Overview
Problem
The existing ETL process struggles to predict and manage data transformation impacts on multiple source systems, often resulting in unintended dependencies and complexities, especially when dealing with large volumes of data and multiple source systems.
Innovation Solution
A system utilizing machine learning algorithms to analyze historical data transformation requests and protocols, predicting impacts on other source systems and providing a graphical user interface for visual representation of these impacts, allowing for informed decision-making and dynamic code changes across target systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data transformation is performed on large volumes of data from multiple source systems, then data consolidation and migration capabilities are improved, but unintended dependencies and system complexities increase
Solution Approach 1:
The system performs impact analysis before executing data transformation to predict and identify potential dependencies on other source systems. This preliminary action allows users to understand consequences before transformation occurs, enabling informed decisions about whether to proceed or modify the transformation parameters.
Solution Approach 2:
The system provides feedback by displaying graphical representations of predicted impacts and dependencies to users. This feedback mechanism allows users to review the analysis results and adjust their transformation requests accordingly, reducing unintended dependencies while maintaining high productivity.
2Productivity
If data transformation protocols are applied to extract data from source systems, then data extraction efficiency is improved, but impacts on neighboring source systems increase
Solution Approach 1:
The system conducts impact analysis before data extraction to predict how transformation protocols will affect other source systems. This allows users to anticipate harmful impacts and modify their extraction requests to minimize negative effects on neighboring systems while maintaining extraction efficiency.
Solution Approach 2:
The system provides graphical feedback showing predicted impacts on source systems, enabling users to review and adjust their extraction protocols. This feedback loop helps maintain high extraction efficiency while reducing harmful impacts on other source systems through informed protocol modification.
3Manufacturing precision
If code changes are implemented across target systems, then data transformation accuracy is improved, but implementation complexity and time increase
Solution Approach 1:
The system performs impact analysis before code changes are implemented to predict which systems and code modules will be affected. This preliminary identification allows for targeted, informed code changes rather than blind implementations, improving accuracy while reducing unnecessary implementation time.
Solution Approach 2:
The system provides feedback through graphical representations of impact analysis results, enabling users to review predicted changes before implementing code modifications. This feedback mechanism ensures accurate transformations by allowing users to verify and adjust their code change requests, reducing time spent on trial-and-error implementations.
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; initiate an impact analysis associated with transforming the data extracted from the first source system using the one or more data transformation protocols, wherein initiating further comprises determining one or more impacts of the data transformation on one or more other source systems; and initiate a presentation of a user interface for display on the user device, wherein the user interface comprises a graphical representation of the one or more impacts of the data transformation of the data extracted from the first source system on the one or more other source systems.