Data Analysis Method for Tracking State Changes in User Information Tables
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Solution Overview
Problem
Existing data analysis methods fail to provide accurate results when content attributes undergo multiple changes, as they are unable to effectively manage and analyze data with active changes in state information.
Innovation Solution
A data analysis method that involves obtaining historical event information, creating user and event recording tables, and updating them based on collected data to accurately track and analyze users whose state information changes, ensuring accurate identification of users and events, even in scenarios with frequent state changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a common database management system is used to record user state information, then the system structure is simple and easy to operate, but it cannot accurately track users whose content attributes change multiple times, leading to inaccurate data analysis results
Solution Approach 1:
The patent segments the data management system into multiple specialized tables: user information table (recording user attributes and state), event recording table (recording target events), and historical event information table (recording state changes). This segmentation allows each table to specialize in storing specific types of data, enabling accurate tracking of users with changing attributes while maintaining manageable system complexity through clear separation of concerns.
Solution Approach 2:
The patent performs preliminary actions by pre-establishing the user information table and event recording table with appropriate schemas before data collection begins. Historical event information is pre-processed and stored in a structured format. This preliminary setup enables the system to accurately track state changes from the beginning, avoiding the need for complex retroactive corrections and ensuring measurement precision from the start.
2Measurement precision
If the system tracks all state changes of users with frequent attribute changes, then data analysis accuracy improves, but the quantity of data to be processed increases significantly
Solution Approach 1:
The patent extracts only the essential and relevant state information from the data stream, storing it in the user information table and event recording table. Rather than processing and storing all possible user attributes and event details, the system extracts and retains only the critical state changes that affect data analysis accuracy. This extraction approach maintains measurement precision while significantly reducing the volume of data that needs to be processed and stored.
3Measurement precision
If historical event information is collected and processed to create user information tables, then accurate data analysis becomes possible, but the time and computational resources required increase
Solution Approach 1:
The patent performs preliminary processing of historical event information to establish the user information table and event recording table before actual data analysis begins. By pre-structuring the data and creating the necessary tables in advance, the system avoids time-consuming processing during the analysis phase. This preliminary action ensures measurement precision is achieved while minimizing time loss during operational data collection and analysis.
Data Source
AI summary
Provided are a data analysis method, a data analysis apparatus and a device. The method includes: obtaining historical event information recording a target event, the historical event information including a user related to the target event and state information of the recorded target event; obtaining a user information table and an event recording table according to the historical event information; after reading collected data, which were recorded according to users' performance of the target event, determining a second target user corresponding to the target event of which the state information is the target state in the collected data, and not recorded in the user information table; and adding the second target user to the user information table, and writing the target event of the second target user into the event recording table according to the collected data.