Data Analysis Control for Parallel Scripts and Same-Screen Results
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Solution Overview
Problem
Existing data analysis methods require users to individually execute processing for each learning model, leading to increased labor when multiple scripts are executed, which is inefficient and time-consuming.
Innovation Solution
A data analysis apparatus and method that enables the simultaneous execution of multiple scripts on selected analysis data, allowing parallel processing and displaying results on the same screen, thereby reducing user labor and time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple learning models are registered in the apparatus, then analysis versatility is improved, but user labor increases when executing each model individually
Solution Approach 1:
The patent combines multiple learning models into a unified interface where users can select and execute multiple models simultaneously through a single operation. The control unit manages the execution of multiple learning models in parallel, merging what would otherwise require multiple separate user operations into one consolidated interaction, thereby reducing user labor while maintaining analysis versatility
2Reliability
If multiple scripts are executed sequentially individually, then processing completeness is ensured, but processing time increases
Solution Approach 1:
The patent implements periodic action through parallel execution of multiple learning models. Instead of sequential processing where each model must complete before the next begins, the control unit enables simultaneous execution of multiple models in parallel. This periodic action allows all models to process data concurrently, ensuring processing completeness while significantly reducing total processing time
3Measurement precision
If individual execution of each learning model is required, then result accuracy is maintained, but work efficiency decreases
Solution Approach 1:
The control unit performs self-service by automatically managing the execution of multiple learning models in parallel. The system autonomously handles model selection, data processing coordination, and result aggregation without requiring manual intervention for each individual model. This self-service approach maintains result accuracy through proper data handling while dramatically improving work efficiency by eliminating the need for sequential manual execution
Data Source
AI summary
A data analysis apparatus includes a control unit that performs control of receiving an operation to select analysis data, control of receiving an operation to select a plurality of scripts that execute analysis on the selected analysis data, and control of executing analysis on the selected analysis data by the plurality of selected scripts in parallel. The data analysis apparatus also includes a display unit configured to display analysis results of the analysis data by the control unit on the same screen.