Conversational Data Analysis for Automatic Indicator Selection
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Solution Overview
Problem
Operation users with weak data analysis capabilities face inefficiencies in obtaining analysis indicators for service analysis targets, often requiring offline inquiries and leading to increased time and costs.
Innovation Solution
A data analysis method and apparatus that utilize a conversation interaction region to automatically provide analysis indicators through natural language processing, allowing users to input question text and receive relevant reply content, including analysis indicators with different dimensions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If operators use offline inquiry to experienced users to obtain analysis indicators, then the accuracy of analysis indicators is improved, but the time consumption increases and efficiency decreases
Solution Approach 1:
The system enables operators to independently obtain analysis indicators through natural language questioning without requiring offline inquiry to experienced users. The AI assistant automatically generates appropriate analysis indicators based on the user's questions, allowing self-service operation that maintains accuracy while eliminating time-consuming manual inquiries
Solution Approach 2:
An AI assistant serves as an intermediary between operators and the data analysis system. This intermediary automatically translates natural language questions into appropriate analysis indicators, eliminating the need for operators to directly query experienced users while maintaining the accuracy and expertise in analysis indicator selection
2Adaptability or versatility
If operators manually configure analysis parameters, then the flexibility of analysis is improved, but the configuration cost and time increase
Solution Approach 1:
The system automatically configures analysis parameters based on the user's natural language questions. The AI assistant interprets the questions and automatically selects appropriate parameters, eliminating manual configuration while maintaining the flexibility to handle diverse analysis scenarios through natural language input
3Ease of operation
If operators lack data analysis experience, then the ease of operation is improved for beginners, but the quality of analysis results deteriorates
Solution Approach 1:
The AI assistant acts as an intermediary that bridges the gap between operators with limited experience and the complex data analysis system. It translates simple natural language questions into sophisticated analysis queries, enabling beginners to obtain reliable analysis results without requiring extensive technical knowledge
Solution Approach 2:
The system provides automatic feedback by interpreting user questions and generating appropriate analysis indicators. This feedback mechanism guides operators with limited experience toward correct analysis approaches while maintaining ease of operation through natural language interaction
Data Source
AI summary
The present disclosure relates to a data analysis method and apparatus, a medium, and an electronic device. The data analysis method includes: displaying a data analysis page, wherein the data analysis page includes a conversation interaction region; and displaying, in the conversation interaction region, first reply content obtained for the first question text in response to a trigger operation for first question text inputted in the conversation interaction region, wherein the first question text is used for describing an analysis target, the first reply content includes at least one analysis indicator, and different analysis indicators have different analysis dimensions. The analysis indicator of the analysis target is automatically obtained in the form of a conversation, so that an operation user with weak experience is assisted in disassembling the analysis target of a service into analysis indicators, and the efficiency of data analysis is improved.