Data visualization analysis system based on e-commerce platform

Abstract

The invention belongs to the technical field of e-commerce data management, and particularly relates to a data visualization analysis system based on an e-commerce platform, which comprises a data acquisition and integration module, an intelligent analysis engine module, a data visualization processing module, a display interaction module, a rear-end operation monitoring module and a management terminal, the data acquisition and integration module acquires data from the e-commerce platform and processes the data, the intelligent analysis engine module carries out deep mining and analysis on the processed data source, and the data visualization processing module adopts a graphical display technology to carry out visualization processing on an analysis result and presents the result to a user, so that the user understanding threshold is reduced, and the user experience is improved. The rear-end operation monitoring module monitors the operation of the display interaction module and accurately evaluates the operation performance of the display interaction module, and checks and maintains the display interaction module and strengthens subsequent supervision when a rear-end operation early warning signal is generated, so that the operation stability, the operation safety and the display interaction effect of the display interaction module are ensured; and the management difficulty of managers is obviously reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of e-commerce data management, and in particular to a data visualization analysis system based on an e-commerce platform. Background Art

[0002] An e-commerce platform is a platform that provides online transactions for enterprises or individuals. Through the e-commerce platform, buyers and sellers can transcend the limitations of time and space to achieve a series of transaction processes such as product display, browsing, purchase, payment, and logistics distribution. With the rapid development of e-commerce, e-commerce platforms have accumulated a large amount of transaction data, user behavior data, product information data, etc. However, traditional data analysis tools often have difficulty in effectively integrating these complex data, and it is difficult to present them to decision makers in an intuitive and easy-to-understand way and accurately evaluate the interactive performance of the presentation, resulting in the inability to fully explore and utilize the value of the data, increasing the management difficulty for managers and low intelligence. In view of the above technical defects, a solution is now proposed. Summary of the invention

[0003] The purpose of the present invention is to provide a data visualization analysis system based on an e-commerce platform, which solves the problem that the prior art is difficult to effectively integrate the data of the e-commerce platform, and it is difficult to present it to decision makers in an intuitive and easy-to-understand manner and accurately evaluate the interactive performance of the display, resulting in the inability to fully explore and utilize the data value, increasing the management difficulty of managers and the low level of intelligence.

[0004] To achieve the above object, the present invention provides the following technical solutions: A data visualization analysis system based on an e-commerce platform, comprising a data collection and integration module, an intelligent analysis engine module, a data visualization processing module, a display interaction module, a back-end operation monitoring module and a management terminal; The data collection and integration module collects data from the e-commerce platform in real time or at regular intervals, cleans, converts and integrates the collected raw data to form a structured and standardized data warehouse, and sends the processed data source to the intelligent analysis engine module; The intelligent analysis engine module integrates data analysis algorithms and models, conducts in-depth mining and analysis of processed data sources, identifies patterns and trends in the data, and sends the analysis results to the data visualization processing module; The data visualization processing module supports a variety of chart types, uses graphical display technology to visualize the analysis results, and presents them to users in a visual manner through the display interaction module; users can query, filter, sort and compare data through the display interaction module, or customize views and reports according to their needs; The back-end operation monitoring module monitors the operation of the display interaction module, generates a back-end operation warning signal or a back-end operation qualified signal through comprehensive evaluation and analysis of the back-end operation, and sends the back-end operation warning signal or the back-end operation qualified signal to the management terminal. When the management terminal receives the back-end operation warning signal, it issues a corresponding warning.

[0005] Furthermore, the specific analysis process of the back-end operation comprehensive evaluation analysis includes: The running time of the display interaction module per unit time is collected and marked as the operation time detection value, and the transportation risk detection value is obtained through transportation risk tracing analysis, and the exhibition and delivery detection value is obtained through exhibition and delivery tracing analysis. The back-end operation evaluation value is obtained by numerically calculating the operation time detection value, the transportation risk detection value and the exhibition and delivery detection value, and the back-end operation evaluation value is numerically compared with the preset back-end operation evaluation threshold. If the back-end operation evaluation value exceeds the preset back-end operation evaluation threshold, a back-end operation warning signal is generated; if the back-end operation evaluation value does not exceed the preset back-end operation evaluation threshold, a back-end operation qualified signal is generated.

[0006] Furthermore, the specific analysis process of freight insurance traceability analysis is as follows: Real-time temperature data and real-time vibration data of several positions on the display interaction module are collected, and the ratio of the real-time temperature data of the corresponding position to the corresponding preset real-time temperature data threshold is marked as the real temperature detection value. Similarly, the real vibration detection value is obtained, and the number of positions where the real-time temperature data or real-time vibration data on the display interaction module exceeds the corresponding preset threshold is marked as the bit error detection value; The actual temperature performance value is obtained by averaging the actual temperature detection values ​​of all positions, and the actual vibration performance value is obtained in the same way. The actual operation value is obtained by numerically calculating the number of bit difference detection values, the actual temperature performance value and the actual vibration performance value. The actual operation value is numerically compared with the preset actual operation threshold. If the actual operation value exceeds the preset actual operation threshold, it is judged that the display interaction module is in a risky state at the corresponding moment; The number of times the display interaction module is judged to be in a risky state per unit time is obtained and marked as the risk judgment frequency value, and the average of all actual operation values ​​per unit time is calculated to obtain the actual operation inspection value, and the actual operation value with the largest value per unit time is marked as the actual operation amplitude value; the risk detection value is obtained by numerically calculating the risk judgment frequency value, the actual operation inspection value and the actual operation amplitude value.

[0007] Furthermore, the specific analysis process of the exhibition and transaction traceability analysis is as follows: When the user clicks on the display interaction module, the click pressure applied by the user to the display interaction module is collected, and the reaction time of the display interaction module is obtained when the click pressure is within the preset click pressure range, and all reaction times per unit time are averaged to obtain the click latency value, and the proportion of the number of reaction times exceeding the preset reaction time threshold per unit time is marked as the click latency value; When the user performs a drag operation on the display interaction module, if the pressure applied to the display interaction module during the dragging process is always within the corresponding preset pressure range, the deviation between the dragging trajectory identified in the corresponding dragging process and the actual dragging trajectory is obtained and marked as the dragging trajectory deviation value; and the average of all the dragging trajectory deviation values ​​in a unit time is calculated to obtain the dragging anomaly value, and the proportion of the number of dragging trajectory deviation values ​​exceeding the preset dragging trajectory deviation threshold in a unit time is marked as the dragging anomaly detection value; And the display effect table value is obtained through analysis, and the exhibition detection value is obtained by numerically calculating the click delay value, click difference delay value, drag difference table value, drag difference detection value and display effect table value.

[0008] Furthermore, the specific analysis and acquisition method of the display effect table value is as follows: The actual display brightness of the display interaction module is collected, and the deviation value of the actual display brightness compared with the set standard display brightness is marked as the display brightness impact value, and the decibel value of the noise generated by the display interaction module is collected and marked as the display noise impact value; Compare the brightness impact value and the noise impact value with the preset brightness impact threshold and the preset noise impact threshold respectively; if the brightness impact value or the noise impact value exceeds the corresponding preset threshold, it is determined that the display interaction module is in an abnormal display state; The single duration of each time the display interaction module is in the display difference state within the unit time is obtained and marked as the display difference duration value, and all the display difference duration values ​​within the unit time are summed up to obtain the total display difference duration value, and the number of display difference duration values ​​exceeding the preset display difference duration threshold within the unit time is marked as the display difference number detection value, and the display effect table value is obtained by numerically calculating the total display difference duration value and the display difference number detection value.

[0009] Furthermore, the management terminal is communicated with the engine tracking and analysis module, which is used to monitor the intelligent analysis engine module. The detection period is set to L1 days. When the number of days reaches L1, the operating performance of the intelligent analysis engine module is analyzed, and an engine abnormality signal or an engine qualified signal is generated through the analysis. The engine abnormality signal or the engine qualified signal is sent to the management terminal, and the management terminal issues a corresponding warning when receiving the engine abnormality signal.

[0010] Furthermore, the specific analysis process of the engine tracking analysis module is as follows: Obtain all the operation and analysis processes of the intelligent analysis engine module within the detection cycle, mark the actual operation time in the corresponding operation and analysis process as the operation condition value, and mark the number of analysis interruptions in the corresponding operation and analysis process as the operation interruption value, and start timing when the analysis interruption occurs until the operation and analysis are resumed to obtain the operation interruption value, compare the operation interruption value with the preset operation interruption threshold, and mark the number of occurrences in which the operation interruption value in the corresponding operation and analysis process exceeds the preset operation interruption threshold as the operation abnormal interruption value; The operation analysis comprehensive evaluation value is obtained by numerically calculating the operation status value, the operation fault value and the operation abnormal fault value, and the operation analysis comprehensive evaluation value is numerically compared with the preset operation analysis comprehensive evaluation threshold value. If the operation analysis comprehensive evaluation value exceeds the preset operation analysis comprehensive evaluation threshold value, the corresponding operation analysis process is marked as a warning process; The number of warning processes corresponding to the intelligent analysis engine module within the detection period is obtained and the ratio thereof to the total number of operation analysis processes is calculated to obtain the warning detection value, and the ratio of the operation analysis comprehensive evaluation value to the corresponding preset operation analysis comprehensive evaluation threshold is marked as the operation analysis occupancy value, and the average of all operation analysis occupancy values ​​within the detection period is calculated to obtain the operation analysis occupancy value; The warning frequency detection value and the operation analysis detection value are numerically compared with the preset warning frequency detection value and the operation analysis detection value. If the warning frequency detection value or the operation analysis detection value exceeds the corresponding preset threshold, an engine abnormality signal is generated; if both the warning frequency detection value and the operation analysis detection value do not exceed the corresponding preset threshold, an engine qualified signal is generated.

[0011] Compared with the prior art, the present invention has the following beneficial effects: 1. In the present invention, the data is collected and processed from the e-commerce platform through the data collection and integration module, the intelligent analysis engine module performs in-depth mining and analysis on the processed data source, and the data visualization processing module uses graphical display technology to visualize the analysis results and present them to the user, thereby lowering the user's understanding threshold. In addition, the back-end operation monitoring module monitors the operation of the display interaction module and accurately evaluates its operation performance, which is conducive to ensuring the operation stability, operation security and display interaction effect of the display interaction module, and significantly reducing the management difficulty of managers; 2. In the present invention, the intelligent analysis engine module is monitored by the engine tracking and analysis module, and the operating performance of the intelligent analysis engine module is analyzed to generate an engine abnormality signal or an engine qualified signal. When the engine abnormality signal is generated, corresponding optimization and improvement measures are taken for the intelligent analysis engine module to ensure the subsequent analysis efficiency and stability of the analysis process of the data by the intelligent analysis engine module, further reduce the management difficulty of management personnel, and have a high degree of intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings; Figure 1 This is a system block diagram of Embodiment 1 of the present invention; Figure 2 This is a system block diagram of Embodiment 2 and Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0013] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0014] Embodiment 1: Figure 1 As shown, the data visualization analysis system based on the e-commerce platform proposed in the present invention includes a data collection and integration module, an intelligent analysis engine module, a data visualization processing module and a display interaction module; The data collection and integration module collects data from the e-commerce platform in real time or at a scheduled time (including but not limited to transaction records, user behavior, product information, inventory status, etc.), cleans, converts and integrates the collected raw data to form a structured and standardized data warehouse, providing a high-quality data source for subsequent data analysis, and sending the processed data source to the intelligent analysis engine module.

[0015] The intelligent analysis engine module integrates data analysis algorithms and models, such as machine learning, data mining, statistical analysis, etc., conducts in-depth mining and analysis of processed data sources, identifies patterns and trends in the data, extracts valuable information, and sends the analysis results to the data visualization processing module.

[0016] The data visualization processing module supports a variety of chart types (such as bar charts, line charts, pie charts, scatter plots, heat maps, maps, etc.), uses graphical display technology to visualize the analysis results, and presents them to users in a visual way through the display interaction module (presenting the analysis results to users in an intuitive and easy-to-understand way), lowering the user's understanding threshold and improving data analysis efficiency. By combining the prediction and suggestion functions of the intelligent analysis engine, it provides powerful decision-making support for enterprises to formulate operational strategies, optimize inventory management, and improve user experience. Users can query, filter, sort and compare data through the display interaction module, or customize views and reports according to needs to quickly obtain key business indicators and trend information.

[0017] Embodiment 2: Figure 2As shown, the difference between this embodiment and the first embodiment is that it further includes a backend operation monitoring module and a management terminal, the backend operation monitoring module is in communication connection with the management terminal, the backend operation monitoring module monitors the operation of the display interaction module, and generates a backend operation warning signal or a backend operation qualified signal through comprehensive evaluation and analysis of the backend operation; And send the back-end operation warning signal or the back-end operation qualified signal to the management terminal. When the management terminal receives the back-end operation warning signal, it issues a corresponding warning. When the management personnel receive the warning, they inspect and repair the display interaction module and strengthen the subsequent supervision of the display interaction module, so as to ensure the operation stability, operation safety and display interaction effect of the display interaction module and reduce the management difficulty of the management personnel. The specific analysis process of the comprehensive evaluation and analysis of the back-end operation is as follows: The transport risk detection value WR is obtained through transport risk traceability analysis, specifically: the real-time temperature data and real-time vibration data (i.e., vibration amplitude) of several positions on the display interaction module are collected, and the ratio of the real-time temperature data at the corresponding position to the corresponding preset real-time temperature data threshold is marked as the real temperature detection value, and the ratio of the real-time vibration data at the corresponding position to the corresponding preset real-time vibration data threshold is marked as the real vibration detection value; And mark the number of positions where the real-time temperature data or real-time vibration data on the interactive module exceeds the corresponding preset threshold as the bit error detection value; calculate the actual temperature performance value by averaging the actual temperature detection values ​​of all positions, and calculate the actual vibration performance value by averaging the actual vibration detection values ​​of all positions; The actual operation value SY is obtained by numerically calculating the bit error detection value SL, the actual temperature performance value SW and the actual vibration performance value SP through the formula SY=tu1*SL+(tu2*SW+tu3*SP) / tu1; wherein tu1, tu2 and tu3 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the actual operation value SY is, the greater the current operation risk of the display interaction module is; Compare the actual operation value SY with the preset actual operation threshold. If the actual operation value SY exceeds the preset actual operation threshold, it indicates that the current operation risk of the display interaction module is relatively high, and the display interaction module is judged to be in a risky state at the corresponding moment. The number of times the display interaction module is judged to be in a risk state within a unit time is obtained and marked as the risk judgment frequency value, and all the actual operation values ​​within a unit time are averaged to obtain the actual operation inspection value, and the actual operation value with the largest value within a unit time is marked as the actual operation amplitude value; The risk frequency judgment value WG, the actual operation inspection value WS and the actual operation amplitude value WN are numerically calculated by the formula WR=c1*WG+(c2*WS+c3*WN) / 2 to obtain the transport risk detection value WR; wherein c1, c2 and c3 are preset proportional coefficients, c1>c2>c3>0; and the larger the value of the transport risk detection value WR is, the greater the operational safety hazard of the display interactive module per unit time is; The display interaction detection value XF is obtained through display interaction tracing analysis, specifically: when the user clicks on the display interaction module, the click pressure applied by the user to the display interaction module is collected, and the reaction time of the display interaction module is obtained when the click pressure is within the preset click pressure range, wherein the larger the value of the reaction time, the less sensitive the reaction of the display interaction module; and the average of all reaction times within a unit time is calculated to obtain the click latency value, and the proportion of the number of reaction times exceeding the preset reaction time threshold within a unit time is marked as the click latency value; When the user performs a drag operation on the display interaction module, if the pressure applied to the display interaction module during the dragging process is always within the corresponding preset pressure range, the deviation between the dragging trajectory identified in the corresponding dragging process and the actual dragging trajectory is obtained and marked as the dragging trajectory deviation value; wherein, the larger the value of the dragging trajectory deviation value is, the lower the trajectory overlap is; The average of all the drag trajectory deviation values ​​within a unit time is calculated to obtain a drag anomaly value, and the percentage of the number of drag trajectory deviation values ​​exceeding a preset drag trajectory deviation threshold within a unit time is marked as a drag anomaly detection value; The actual display brightness of the display interaction module is collected, and the deviation value of the actual display brightness compared with the set standard display brightness is marked as the display brightness impact value, and the decibel value of the noise generated by the display interaction module is collected and marked as the display noise impact value; Compare the brightness impact value and the noise impact value with the preset brightness impact threshold and the preset noise impact threshold respectively; if the brightness impact value or the noise impact value exceeds the corresponding preset threshold, it is determined that the display interaction module is in an abnormal display state; The single duration of each time the display interaction module is in the display state within a unit time is obtained and marked as the display duration value, and all the display duration values ​​within a unit time are summed up to obtain the total display duration value, and the number of display duration values ​​exceeding the preset display duration threshold within a unit time is marked as the display count detection value; By formula The total display time value ZW and the display number check value ZS are numerically calculated to obtain the display effect table value ZX; wherein eq1 and eq2 are preset proportional coefficients, eq2>eq1>0; and the larger the value of the display effect table value ZX, the worse the display effect of the interactive module in unit time; The display interaction detection value XF is obtained by numerically calculating the click delay value XS, the click abnormal delay value XR, the drag abnormal table value XL, the drag abnormal detection value XP and the display effect table value ZX through the formula XF=0.5*(sw1*XS+sw2*XR+sw3*XL+sw4*XP)+sw5*ZX; wherein sw1, sw2, sw3, sw4 and sw5 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the display interaction detection value XF is, the more abnormal the display interaction status of the display interaction module in unit time is; The running time of the interactive module in a unit time is collected and marked as the running time detection value. The operation time detection value LP, the operation risk detection value WR and the exhibition and delivery detection value XF are numerically calculated to obtain the backend operation evaluation value NY; wherein uy1, uy2 and uy3 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the backend operation evaluation value NY is, the worse the overall operation performance of the display interaction module is; The backend operation evaluation value NY is numerically compared with the preset backend operation evaluation threshold. If the backend operation evaluation value NY exceeds the preset backend operation evaluation threshold, it indicates that the operation performance of the display interaction module is generally poor, and a backend operation warning signal is generated; if the backend operation evaluation value NY does not exceed the preset backend operation evaluation threshold, it indicates that the operation performance of the display interaction module is generally good, and a backend operation qualified signal is generated.

[0018] Embodiment 3: Figure 2 As shown, the difference between this embodiment and the first and second embodiments is that the management terminal is connected to the engine tracking and analysis module in communication, and the engine tracking and analysis module is used to monitor the intelligent analysis engine module, and the detection period is set to L1, preferably, L1 is ten days; when the number of days reaches L1, the operating performance of the intelligent analysis engine module is analyzed, and an engine abnormality signal or an engine qualified signal is generated through the analysis; The engine abnormality signal or engine qualified signal is sent to the management terminal. When the management terminal receives the engine abnormality signal, it issues a corresponding warning. When the management personnel receive the corresponding warning, they make corresponding optimization and improvement measures for the intelligent analysis engine module to ensure the subsequent analysis efficiency and stability of the data by the intelligent analysis engine module, further reduce the management difficulty of the management personnel, and have a high degree of intelligence. The specific analysis process of the engine tracking analysis module is as follows: Obtain all the operation and analysis processes of the intelligent analysis engine module within the detection cycle, mark the actual operation time in the corresponding operation and analysis process as the operation condition value, and mark the number of analysis interruptions in the corresponding operation and analysis process as the operation interruption value, and start timing when the analysis interruption occurs until the operation and analysis are resumed to obtain the operation interruption value, compare the operation interruption value with the preset operation interruption threshold, and mark the number of occurrences in which the operation interruption value in the corresponding operation and analysis process exceeds the preset operation interruption threshold as the operation abnormal interruption value; By formula The operation status value TF, the operation fault value TM and the operation abnormal fault value TD are numerically calculated to obtain the operation analysis comprehensive evaluation value TL; wherein rg1, rg2 and rg3 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the operation analysis comprehensive evaluation value TL is, the worse the operation performance of the corresponding operation analysis process is in general; The operation analysis comprehensive evaluation value TL is numerically compared with the preset operation analysis comprehensive evaluation threshold. If the operation analysis comprehensive evaluation value TL exceeds the preset operation analysis comprehensive evaluation threshold, it indicates that the operation performance of the corresponding operation analysis process is generally poor, and the corresponding operation analysis process is marked as a warning process; The number of warning processes corresponding to the intelligent analysis engine module within the detection period is obtained and the ratio thereof to the total number of operation analysis processes is calculated to obtain the warning detection value, and the ratio of the operation analysis comprehensive evaluation value to the corresponding preset operation analysis comprehensive evaluation threshold is marked as the operation analysis occupancy value, and the average of all operation analysis occupancy values ​​within the detection period is calculated to obtain the operation analysis occupancy value; The warning frequency detection value and the operation analysis detection value are numerically compared with the preset warning frequency detection value and the operation analysis detection value. If the warning frequency detection value or the operation analysis detection value exceeds the corresponding preset threshold, it indicates that the operating performance of the intelligent analysis engine module during the detection period is generally poor, and an engine abnormality signal is generated; if the warning frequency detection value and the operation analysis detection value do not exceed the corresponding preset threshold, it indicates that the operating performance of the intelligent analysis engine module during the detection period is generally good, and an engine qualified signal is generated.

[0019] The working principle of the present invention is as follows: when in use, data is collected from the e-commerce platform in real time or at a scheduled time through the data collection and integration module, and the collected raw data is cleaned, converted and integrated, etc. The intelligent analysis engine module integrates data analysis algorithms and models, and deeply mines and analyzes the processed data source, identifies patterns and trends in the data, and extracts valuable information. The data visualization processing module uses graphical display technology to visualize the analysis results, and presents them to the user in a visual manner through the display interaction module, thereby lowering the user's understanding threshold. The operation of the display interaction module is monitored through the back-end operation monitoring module, and a back-end operation warning signal or a back-end operation qualified signal is generated through a comprehensive evaluation and analysis of the back-end operation. When the back-end operation warning signal is generated, the display interaction module is inspected and repaired, and subsequent supervision is strengthened to ensure the operation stability, operation safety and display interaction effect of the display interaction module, and significantly reduce the management difficulty of management personnel.

[0020] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A data visualization analysis system based on an e-commerce platform, characterized in that: It includes data collection and integration module, intelligent analysis engine module, data visualization processing module, display interaction module, back-end operation monitoring module and management terminal; The data collection and integration module collects data from the e-commerce platform in real time or at regular intervals, cleans, converts and integrates the collected raw data to form a structured and standardized data warehouse, and sends the processed data source to the intelligent analysis engine module; The intelligent analysis engine module integrates data analysis algorithms and models, conducts in-depth mining and analysis of processed data sources, identifies patterns and trends in the data, and sends the analysis results to the data visualization processing module; The data visualization processing module supports a variety of chart types, uses graphical display technology to visualize the analysis results, and presents them to users in a visual manner through the display interaction module; users can query, filter, sort and compare data through the display interaction module, or customize views and reports according to their needs; The back-end operation monitoring module monitors the operation of the display interaction module, generates a back-end operation warning signal or a back-end operation qualified signal through comprehensive evaluation and analysis of the back-end operation, and sends the back-end operation warning signal or the back-end operation qualified signal to the management terminal. When the management terminal receives the back-end operation warning signal, it issues a corresponding warning.

2. According to claim 1, a data visualization analysis system based on an e-commerce platform is characterized in that: The specific analysis process of the comprehensive evaluation and analysis of back-end operation includes: The running time of the display interaction module per unit time is collected and marked as the operation time detection value, and the transportation risk detection value is obtained through transportation risk tracing analysis, and the exhibition and delivery detection value is obtained through exhibition and delivery tracing analysis. The back-end operation evaluation value is obtained by numerically calculating the operation time detection value, the transportation risk detection value and the exhibition and delivery detection value, and the back-end operation evaluation value is numerically compared with the preset back-end operation evaluation threshold. If the back-end operation evaluation value exceeds the preset back-end operation evaluation threshold, a back-end operation warning signal is generated; if the back-end operation evaluation value does not exceed the preset back-end operation evaluation threshold, a back-end operation qualified signal is generated.

3. According to claim 2, a data visualization analysis system based on an e-commerce platform is characterized in that: The specific analysis process of freight insurance traceability analysis is as follows: Real-time temperature data and real-time vibration data of several positions on the display interaction module are collected, and the ratio of the real-time temperature data of the corresponding position to the corresponding preset real-time temperature data threshold is marked as the real temperature detection value. Similarly, the real vibration detection value is obtained, and the number of positions where the real-time temperature data or real-time vibration data on the display interaction module exceeds the corresponding preset threshold is marked as the bit error detection value; The actual temperature performance value is obtained by averaging the actual temperature detection values ​​of all positions, and the actual vibration performance value is obtained in the same way. The actual operation value is obtained by numerically calculating the number of bit difference detection values, the actual temperature performance value and the actual vibration performance value. The actual operation value is numerically compared with the preset actual operation threshold. If the actual operation value exceeds the preset actual operation threshold, it is judged that the display interaction module is in a risky state at the corresponding moment; The number of times the display interaction module is judged to be in a risk state within a unit time is obtained and marked as the risk judgment frequency value, and all the actual operation values ​​within a unit time are averaged to obtain the actual operation inspection value, and the actual operation value with the largest value within a unit time is marked as the actual operation amplitude value; The transport risk detection value is obtained by numerically calculating the risk judgment frequency value, the actual operation inspection value and the actual operation amplitude value.

4. According to claim 2, a data visualization analysis system based on an e-commerce platform is characterized in that: The specific analysis process of exhibition and transaction traceability analysis is as follows: When the user clicks on the display interaction module, the click pressure applied by the user to the display interaction module is collected, and the reaction time of the display interaction module is obtained when the click pressure is within the preset click pressure range, and all reaction times per unit time are averaged to obtain the click latency value, and the proportion of the number of reaction times exceeding the preset reaction time threshold per unit time is marked as the click latency value; When the user performs a drag operation on the display interaction module, if the pressure applied to the display interaction module during the dragging process is always within the corresponding preset pressure range, the deviation between the dragging trajectory identified in the corresponding dragging process and the actual dragging trajectory is obtained and marked as the dragging trajectory deviation value; The average of all the drag trajectory deviation values ​​within a unit time is calculated to obtain a drag anomaly value, and the percentage of the number of drag trajectory deviation values ​​exceeding a preset drag trajectory deviation threshold within a unit time is marked as a drag anomaly detection value; And the display effect table value is obtained through analysis, and the exhibition detection value is obtained by numerically calculating the click latency value, click difference latency value, drag difference table value, drag difference detection value and display effect table value.

5. The data visualization analysis system based on the e-commerce platform according to claim 4 is characterized in that: The specific analysis and acquisition method of the display effect table value is as follows: The actual display brightness of the display interaction module is collected, and the deviation value of the actual display brightness compared with the set standard display brightness is marked as the display brightness impact value, and the decibel value of the noise generated by the display interaction module is collected and marked as the display noise impact value; Compare the brightness impact value and the noise impact value with the preset brightness impact threshold and the preset noise impact threshold respectively; if the brightness impact value or the noise impact value exceeds the corresponding preset threshold, it is determined that the display interaction module is in an abnormal display state; The single duration of each time the display interaction module is in the display difference state within the unit time is obtained and marked as the display difference duration value, and all the display difference duration values ​​within the unit time are summed up to obtain the total display difference duration value, and the number of display difference duration values ​​exceeding the preset display difference duration threshold within the unit time is marked as the display difference number detection value, and the display effect table value is obtained by numerically calculating the total display difference duration value and the display difference number detection value.

6. The data visualization analysis system based on the e-commerce platform according to claim 1 is characterized in that: The management terminal is communicated with the engine tracking and analysis module. The engine tracking and analysis module is used to monitor the intelligent analysis engine module. The detection period is set to L1 days. When the number of days reaches L1, the operating performance of the intelligent analysis engine module is analyzed. An engine abnormality signal or an engine qualified signal is generated through the analysis, and the engine abnormality signal or the engine qualified signal is sent to the management terminal. When the management terminal receives the engine abnormality signal, a corresponding warning is issued.

7. The data visualization analysis system based on the e-commerce platform according to claim 6 is characterized in that: The specific analysis process of the engine tracking analysis module is as follows: Obtain all the operation and analysis processes of the intelligent analysis engine module within the detection cycle, mark the actual operation time in the corresponding operation and analysis process as the operation condition value, and mark the number of analysis interruptions in the corresponding operation and analysis process as the operation interruption value, and start timing when the analysis interruption occurs until the operation and analysis are resumed to obtain the operation interruption value, and mark the number of occurrences in which the operation interruption value in the corresponding operation and analysis process exceeds the preset operation interruption threshold as the operation abnormal interruption value; The operation analysis comprehensive evaluation value is obtained by numerically calculating the operation status value, the operation fault value and the operation abnormal fault value, and the operation analysis comprehensive evaluation value is numerically compared with the preset operation analysis comprehensive evaluation threshold value. If the operation analysis comprehensive evaluation value exceeds the preset operation analysis comprehensive evaluation threshold value, the corresponding operation analysis process is marked as a warning process; The number of warning processes corresponding to the intelligent analysis engine module within the detection period is obtained and the ratio thereof to the total number of operation analysis processes is calculated to obtain the warning detection value, and the ratio of the operation analysis comprehensive evaluation value to the corresponding preset operation analysis comprehensive evaluation threshold is marked as the operation analysis occupancy value, and the average of all operation analysis occupancy values ​​within the detection period is calculated to obtain the operation analysis occupancy value; If the warning frequency detection value or the operation analysis occupancy detection value exceeds the corresponding preset threshold, an engine abnormality signal is generated; if the warning frequency detection value and the operation analysis occupancy detection value do not exceed the corresponding preset threshold, an engine qualified signal is generated.

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