Automated Data Modeling GUI for Intuitive Scenario Extrapolation
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Solution Overview
Problem
Current data analytics systems lack the ability to automatically process datasets based on different scenarios and do not have intuitive interfaces for sophisticated data analysis and manipulation, requiring significant manual effort, especially when dealing with unorganized or scanned data forms.
Innovation Solution
A computer-implemented method and system that generates a graphical user interface (GUI) to automatically import, merge, and process raw data sets, allowing users to build customized models without additional input, using a merge icon to combine data sources, select variables, and build predictive models, which can then generate graphical representations and predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated systems are used for data processing, then productivity is improved, but the systems lack capability to extrapolate datasets based on different scenarios
Solution Approach 1:
The system dynamically adjusts data processing operations based on user-defined scenarios and parameters. The automated modeling system allows users to modify variables and conditions, and the system automatically reprocesses data to generate different results, making the rigid automated system adaptable to various scenarios without manual reconfiguration.
2Measurement precision
If sophisticated data analysis capabilities are provided, then measurement precision is improved, but the interface complexity increases requiring more user input
Solution Approach 1:
The system performs automated data processing and model building without requiring extensive user input or expertise. Users simply define high-level scenarios and parameters, while the system automatically handles data merging, variable selection, model construction, and result generation, making sophisticated analysis accessible to non-experts.
3Measurement precision
If manual data entry is used for unorganized forms, then data extraction accuracy is improved, but loss of time increases significantly
Solution Approach 1:
The system replaces manual mechanical data entry with automated computational processing. Users upload unorganized forms or data sources, and the system automatically extracts, merges, and processes the data using algorithms, eliminating the need for manual typing while maintaining data accuracy through systematic processing rules.
4Extent of automation
If automated model building is implemented, then extent of automation is improved, but device complexity increases
Solution Approach 1:
The automated modeling system is divided into distinct modular components: data import module, data merging module, variable selection module, model building module, and result generation module. Each module handles a specific aspect of the process independently, making the complex automation manageable through clear separation of functions while maintaining high-level user-friendly interfaces.
Data Source
AI summary
A computer-implemented method for automatically determining data relationships includes generating a graphical user interface (GUI) that allows a user to intuitively form a customized model of data from different data sources. The GUI includes icons that represent data sources, data variable selection, data modeling, and data prediction. The icons can be logically arranged to form a customized model without any additional user input or knowledge of data modeling. A prediction GUI allows the user to set customized weights of data variables in the model to form predictive controls for data prediction such as in what-if scenarios.