Business management method and system based on 3D model

Abstract

The invention discloses a business management method and device based on a 3D model, and the method comprises the steps: collecting business data and business process information, carrying out the three-dimensional coordinate conversion of the business data, obtaining the three-dimensional coordinate of each piece of data, carrying out the graphic editing of the business data based on the three-dimensional coordinates, obtaining a plurality of graphic elements, carrying out the visual effect adjustment of the graphic elements, and achieving the business management. Obtaining a three-dimensional model, and performing interactive design according to the three-dimensional model to obtain a three-dimensional data display result; performing statistical analysis on the business data to obtain a key factor index, and performing index value calculation by using the business data according to the key factor index to obtain a key index value; a preset threshold range is obtained based on the key index value, if the service data is not in the preset threshold range, it is judged that the service data is abnormal, and an abnormal prompt is sent out, so that a user carries out processing according to the abnormal prompt, the service network is displayed and managed in a 3D mode, and the service data processing efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a business management method and system based on 3D models. Background Art

[0002] In the current business operation environment, a comprehensive understanding and accurate grasp of business conditions have become the key to management. However, traditional data analysis tools often fail to provide intuitive and dynamic displays, and fail to achieve real-time adjustment and traceability of key factor indicators, making it difficult to meet the needs of modern management. Summary of the invention

[0003] In order to solve the above technical problems, the embodiments of the present invention provide a 3D model business management method and system, which realizes the display and management of the business network in 3D and improves the business data processing efficiency.

[0004] A first aspect of an embodiment of the present invention provides a 3D model service management method, the method comprising:

[0005] Collecting business data and business process information, performing three-dimensional coordinate conversion on the business data, and obtaining three-dimensional coordinates of each data, wherein the business data includes several types of business data;

[0006] Based on the three-dimensional coordinates, the business data is graphically edited to obtain multiple graphic elements, the visual effects of the graphic elements are adjusted to obtain a three-dimensional model, and interactive design is performed based on the three-dimensional model to obtain a three-dimensional data display result;

[0007] Conduct statistical analysis on business data to obtain key factor indicators for each type of business data. Based on the key factor indicators, calculate the indicator values ​​using business data to obtain key indicator values.

[0008] Based on the key indicator value, a preset threshold range for business data of the type corresponding to the key indicator value is set, and the business data is monitored for abnormalities according to the preset threshold range. If the business data is not within the preset threshold range, the business data is judged to be abnormal and an abnormal reminder is issued so that the user can handle it according to the abnormal reminder.

[0009] In a possible implementation manner of the first aspect, performing three-dimensional coordinate conversion on the business data to obtain the three-dimensional coordinates of each data includes:

[0010] Adjust or delete duplicate business data, abnormal business data and invalid business data in the business data to obtain complete business data;

[0011] Standardize the complete business data to obtain standard business data, and determine multiple key features of the standard business data based on the business needs and data characteristics of the standard business data;

[0012] Based on the key features, the standard business data is mapped and transformed using linear mapping or classification data mapping methods to obtain the three-dimensional coordinates of each standard business data.

[0013] In a possible implementation of the first aspect, statistical analysis is performed on the business data to obtain key factor indicators of each type of business data, including:

[0014] Collect market data, feedback data and operational data;

[0015] Extract relationships between market data, feedback data, operational data, and business data to obtain key factor indicators for each type of business data.

[0016] In a possible implementation of the first aspect, according to the key factor indicator, the indicator value is calculated using the business data to obtain the key indicator value, including:

[0017] Adjust or delete duplicate business data, abnormal business data, and invalid business data in market data, feedback data, operation data, and business data to obtain data cleaning results corresponding to each data;

[0018] Integrate the data cleaning results corresponding to each data to obtain a data set, define the calculation formula for each key factor indicator, and obtain the key indicator value based on the data set and the calculation formula.

[0019] In a possible implementation manner of the first aspect, after the business process information is collected, the method further includes:

[0020] Build a model environment based on business environment information to obtain a sandbox simulation scenario;

[0021] Design the simulation process according to the business process data, design the simulation system according to the sandbox simulation scenario and simulation process, design the interactive function and data analysis function based on the model system, and obtain the sandbox simulation module to enable users to perform business simulation.

[0022] A second aspect of an embodiment of the present invention provides a 3D model-based service management device, the device comprising:

[0023] The acquisition module is used to acquire business data and business process information, and perform three-dimensional coordinate conversion on the business data to obtain the three-dimensional coordinates of each data, wherein the business data includes several types of business data;

[0024] The editing module is used to perform graphic editing on the business data based on the three-dimensional coordinates to obtain multiple graphic elements, adjust the visual effects of the graphic elements to obtain a three-dimensional model, perform interactive design based on the three-dimensional model, and obtain a three-dimensional data display result;

[0025] The statistical module is used to perform statistical analysis on business data to obtain key factor indicators of various types of business data, and calculate the indicator value using the business data according to the key factor indicators to obtain the key indicator value;

[0026] The monitoring module is used to set the preset threshold range of business data of the type corresponding to the key indicator value based on the key indicator value, and monitor the business data for abnormalities according to the preset threshold range. If the business data is not within the preset threshold range, the business data is judged to be abnormal and an abnormal reminder is issued so that the user can handle it according to the abnormal reminder.

[0027] In a possible implementation manner of the second aspect, performing three-dimensional coordinate conversion on the business data to obtain the three-dimensional coordinates of each data includes:

[0028] Adjust or delete duplicate business data, abnormal business data and invalid business data in the business data to obtain complete business data;

[0029] Standardize the complete business data to obtain standard business data, and determine multiple key features of the standard business data based on the business needs and data characteristics of the standard business data;

[0030] Based on the key features, the standard business data is mapped and transformed using linear mapping or classification data mapping methods to obtain the three-dimensional coordinates of each standard business data.

[0031] In a possible implementation of the second aspect, statistical analysis is performed on the business data to obtain key factor indicators of each type of business data, including:

[0032] Collect market data, feedback data and operational data;

[0033] Extract relationships between market data, feedback data, operational data, and business data to obtain key factor indicators for each type of business data.

[0034] In a possible implementation of the second aspect, according to the key factor indicator, the indicator value is calculated using the business data to obtain the key indicator value, including:

[0035] Adjust or delete duplicate business data, abnormal business data, and invalid business data in market data, feedback data, operation data, and business data to obtain data cleaning results corresponding to each data;

[0036] Integrate the data cleaning results corresponding to each data to obtain a data set, define the calculation formula for each key factor indicator, and obtain the key indicator value based on the data set and the calculation formula.

[0037] In a possible implementation manner of the second aspect, after the business process information is collected, the method further includes:

[0038] Build a model environment based on business environment information to obtain a sandbox simulation scenario;

[0039] Design the simulation process according to the business process data, design the simulation system according to the sandbox simulation scenario and simulation process, design the interactive function and data analysis function based on the model system, and obtain the sandbox simulation module to enable users to perform business simulation.

[0040] A third aspect of an embodiment of the present invention provides a computer device, including a processor and a memory, wherein the memory is used to store a computer program, and when the computer program is executed by the processor, the above-mentioned 3D model-based business management method is implemented.

[0041] A fourth aspect of an embodiment of the present invention provides a computer-readable storage medium storing a computer program, which implements the above-mentioned 3D model-based business management method when executed by a processor.

[0042] The present invention collects business data and business process information, performs three-dimensional coordinate conversion on the business data to obtain the three-dimensional coordinates of each data, performs graphic editing on the business data based on the three-dimensional coordinates to obtain multiple graphic elements, adjusts the visual effects of the graphic elements to obtain a three-dimensional model, and performs interactive design based on the three-dimensional model to obtain a three-dimensional data display result; performs statistical analysis on the business data to obtain key factor indicators of various types of business data, calculates indicator values ​​using the business data based on the key factor indicators, and obtains key indicator values; sets a preset threshold range for the type of business data corresponding to the key indicator value based on the key indicator value, performs abnormal monitoring on the business data based on the preset threshold range, and if the business data is not within the preset threshold range, determines that the business data is abnormal and issues an abnormal reminder, so that the user can handle it according to the abnormal reminder. The present invention realizes the display and management of the business network in a 3D manner, and improves the efficiency of business data processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 : A flow chart of a business management method according to an embodiment of a business management method based on a 3D model provided by the present invention;

[0044] Figure 2 : A device block diagram of an embodiment of the 3D model-based business management method provided by the present invention. DETAILED DESCRIPTION

[0045] 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.

[0046] Please refer to Figure 1 , which is a flow chart of an embodiment of a 3D model-based business management method provided by an embodiment of the present invention, including steps S101 to S104, each of which is specifically as follows:

[0047] S101 . Collect business data and business process information, perform three-dimensional coordinate conversion on the business data, and obtain three-dimensional coordinates of each data, wherein the business data includes several types of business data.

[0048] In this embodiment, the management system includes a 3D data display module, a sandbox simulation module, a key factor index adjustment module, an abnormal influencing factor capture module, an influencing factor and influencing coefficient adjustment module, and a decision opinion generation module. Among them, the 3D data display module is responsible for displaying business data in the form of 3D data, providing intuitive and dynamic visual effects. First, collect and organize business data and organize it into a format suitable for 3D display. Business data includes different types of data such as numerical, time, and classification. Then convert the data into three-dimensional coordinates. Specifically, select the corresponding conversion method according to the data type and feature, and use Cartesian coordinate system or polar coordinate system to represent the position of data points.

[0049] In some embodiments, step S101 includes but is not limited to the following steps:

[0050] Adjust or delete duplicate business data, abnormal business data and invalid business data in the business data to obtain complete business data;

[0051] Standardize the complete business data to obtain standard business data, and determine multiple key features of the standard business data based on the business needs and data characteristics of the standard business data;

[0052] Based on the key features, the standard business data is mapped and transformed using linear mapping or classification data mapping methods to obtain the three-dimensional coordinates of each standard business data.

[0053] Specifically, the business data is cleaned, including removing duplicate data, erroneous data or invalid data. Then the data values ​​are standardized, and the data values ​​can be scaled to a uniform range by normalization to facilitate subsequent processing and visualization. The business data is converted to a data type. Since three-dimensional coordinates require specific numerical values ​​to represent, ensure that all required data is of numerical type.

[0054] Based on business needs and data availability, select three key features that can represent the location of the data points. These features can be coordinates in physical space (such as X, Y, Z), three aspects of a time series (such as year, month, day), or any other meaningful combination. For continuous numerical data, you can directly use a linear function to map the data values ​​to the coordinate axes of the three-dimensional space. For example, if the data range is [0,100] and the coordinate axis range is [-1,1], you can use the linear function f(x) = (x / 100)*2-1 for mapping. For categorical data, different methods can be used to convert it to numerical coordinates. For example, one-hot encoding can be used to assign a unique coordinate combination to each category, or techniques such as multidimensional scaling (MDS) can be used to map the similarity relationship between categories into three-dimensional space.

[0055] According to the intrinsic structure of the data or the display requirements, the coordinates are rotated and translated to better display the distribution and characteristics of the data. Then the scale of the coordinate axis is adjusted to ensure that the data points are evenly distributed in the three-dimensional space and to avoid excessive compression or stretching of certain dimensions. You can choose Cartesian coordinate system, polar coordinate system and other special coordinate systems. Among them, Cartesian coordinate system is the most commonly used three-dimensional coordinate system and is suitable for most scenarios. Polar coordinate system is suitable for data with central symmetry or rotational symmetry. Other special coordinate systems can select appropriate coordinate systems according to the specific properties of the data, such as spherical coordinate system, cylindrical coordinate system, etc.

[0056] After obtaining the converted three-dimensional coordinates, the converted three-dimensional coordinates are output in an array, a list or other format suitable for subsequent processing and data visualization.

[0057] In some embodiments, step S101 includes but is not limited to the following steps:

[0058] Build a model environment based on business environment information to obtain a sandbox simulation scenario;

[0059] A simulation process is designed according to the business process data, a simulation system is designed according to the sandbox simulation scenario and the simulation process, and based on the model system, interactive functions and data analysis functions are designed to obtain a sandbox simulation module so that users can perform business simulation.

[0060] Specifically, the sandbox simulation module provides a dynamic and interactive analysis tool by simulating the actual business environment. First, the business environment to be simulated needs to be clarified, including business types, processes, participants, and related data. Then, according to the determined business environment, the corresponding simulation environment is constructed, including sandbox models, scene settings, role settings, etc. According to the business process, the corresponding simulation process is designed, including task allocation, time planning, event triggering, etc. Use appropriate development tools and technologies, such as computer graphics technology, game development guides, etc. to develop the simulation system. Implement various interactive functions in the simulation system, such as user operations, event triggering, data updates, etc. Integrate the simulation system with data analysis tools so that users can perform real-time data analysis and decision-making during the simulation process, test the simulation module, and make necessary optimizations and adjustments to ensure its normal operation and provide accurate simulation results. Provide training to users and collect user feedback to improve and optimize the functions and performance of the simulation module.

[0061] S102. Based on the three-dimensional coordinates, the business data is graphically edited to obtain a plurality of graphic elements, the visual effects of the graphic elements are adjusted to obtain a three-dimensional model, and interactive design is performed based on the three-dimensional model to obtain a three-dimensional data display result.

[0062] In this embodiment, the business data is graphically edited according to the three-dimensional coordinates to obtain multiple graphic elements, and then the visual effects of the graphic elements are adjusted to obtain a three-dimensional model. According to the three-dimensional model, interactive design is performed to obtain a three-dimensional data display result. Specifically, according to the converted data coordinates, a 3D visualization tool or programming language is used to create graphic elements such as points, lines, and surfaces. These graphic elements can represent data points or data sets. Then, by adjusting visual attributes such as color, size, and shape, the graphic elements can intuitively reflect the characteristics and relationships of the data. At the same time, animation, interaction and other effects can be added to enhance the dynamics and operability of 3D data. Then, interactive functions such as zooming, rotating, and panning are added to the 3D data display module, so that the audience can observe the data from different angles. At the same time, elements such as prompt boxes and toolbars can be set to provide information about data or operations. Then test the performance and compatibility of the 3D data display module on different devices and different network environments. Optimize according to the test results, including adjusting visual effects, optimizing data loading speed, etc. Release the 3D data display module, regularly update and maintain data and functions, and ensure the accuracy of the data and the display effect.

[0063] S103, performing statistical analysis on the business data to obtain key factor indicators of each type of business data, and calculating indicator values ​​using the business data based on the key factor indicators to obtain key indicator values.

[0064] In this embodiment, the key factor indicator adjustment module can dynamically adjust the key factor indicator value according to the actual situation and the settings of the management personnel, reflect its impact on the business in real time, and help the management personnel make timely adjustments. Clearly define the key factor indicators and understand the impact of the key factor indicators on the business. The key factor indicators are obtained by using statistical models, machine learning algorithms or other analytical tools to reveal the complex relationships and patterns in the business data, understand the performance of the current key factor indicators, and their impact on the business.

[0065] It should be noted that key factor indicators refer to core metrics that are closely related to business success or failure, including but not limited to user growth rate, customer satisfaction, market share, conversion rate, etc.

[0066] In some embodiments, step S103 includes but is not limited to the following steps:

[0067] Collect market data, feedback data and operational data;

[0068] Extract relationships between market data, feedback data, operational data, and business data to obtain key factor indicators for each type of business data.

[0069] Specifically, when setting adjustment rules, obtaining the key factor indicator values ​​is a comprehensive and systematic process, which involves multiple steps and data sources. The calculation of key factor indicator values ​​includes business data, market data, customer feedback data and internal operation data, among which business data includes sales data, production data, inventory data, etc., which directly reflect the operation and performance of the business. Market data includes market research data, competitor analysis data, consumer behavior data, etc., which provide insights into market trends and consumer needs. Customer feedback data collected through customer surveys, satisfaction surveys, social media comments, etc. can help understand customers' views on products and services, as well as potential points for improvement. Internal operation data includes employee performance data, process efficiency data, quality control data, etc., which reflect the status and efficiency of the company's internal operations.

[0070] First, the collected data needs to be cleaned to remove duplicate, erroneous or invalid data to ensure the accuracy and reliability of the data. Integrate data from different sources to form a unified data set for analysis and comparison. Standardize or normalize the data as needed to eliminate the dimensional differences between different indicators so that different indicators can be compared and calculated. Define the calculation formula for key factor indicators based on business needs and goals, and finally use the defined formula and the cleaned and integrated business data. Among them, the calculation formula needs to involve multiple variables and parameters, and multiple factors need to be considered comprehensively.

[0071] By analyzing historical data, we can understand the changing trends and patterns of key factor indicators and provide a basis for setting adjustment rules. Based on the business experience of managers and the opinions of industry experts, we can interpret and evaluate key factor indicators and determine reasonable adjustment ranges and thresholds. According to the analysis results and actual needs, we can formulate specific adjustment rules. These rules can be based on certain thresholds, ratios or model predictions, and can be dynamically adjusted according to the actual performance of key factor indicators.

[0072] According to the set adjustment rules, the key factor indicator values ​​are adjusted automatically or manually. For example, the new indicator values ​​can be automatically calculated by algorithms, or manually adjusted by managers. After adjusting the key factor indicator values, its impact on the business needs to be reflected in a timely manner, such as displaying the new indicator values ​​and business data through data visualization tools to help managers understand business changes in a timely manner. According to the actual business situation and adjustment results, timely feedback and optimization of adjustment rules are provided to ensure that the adjustment of key factor indicator values ​​can better reflect business changes.

[0073] S104. Based on the key indicator value, set a preset threshold range for the type of business data corresponding to the key indicator value, and perform abnormal monitoring on the business data according to the preset threshold range. If the business data is not within the preset threshold range, the business data is judged to be abnormal and an abnormal reminder is issued, so that the user can handle it according to the abnormal reminder.

[0074] In this embodiment, the business data related to the key factor indicators are monitored in real time to ensure that the business data is within the normal range. For example, a business data threshold can be set, and when the business data exceeds the preset upper and lower limits, the abnormal monitoring mechanism is triggered; anomaly detection algorithms, such as statistical anomaly detection, anomaly detection based on machine learning, etc., are used to conduct in-depth analysis of the collected business data to find abnormal influencing factors. For example, abnormal business data that is significantly different from the normal business data distribution can be found through algorithms such as isolated forests and outlier scanning; the abnormal business data is further analyzed, and the influencing factors that cause the anomaly are identified in combination with business scenarios and business data characteristics. For example, information related to the anomaly can be extracted from massive business data through business data mining, text mining and other technologies.

[0075] The identified abnormal influencing factors are promptly pushed to managers through emails, text messages, notification bars, etc., reminding them to pay special attention. At the same time, the abnormal data is visualized and displayed to managers in the form of charts, dashboards, etc., to help them intuitively understand the abnormal situation. After receiving the abnormal reminder, managers can take corresponding measures to deal with the abnormal influencing factors, such as adjusting strategies and optimizing processes. At the same time, the abnormal influencing factor capture module can also provide some processing suggestions to help managers quickly solve problems.

[0076] The decision-making opinion generation module will automatically generate corresponding decision opinions based on the analysis results of the above modules to provide reference for managers. The analysis results of the key factor indicator adjustment module and the abnormal influencing factor capture module are integrated to form a comprehensive business analysis report. According to different business scenarios and problems, corresponding decision rules are pre-set, such as formulating corresponding decision strategies based on the weight of key factor indicators and the importance of abnormal influencing factors. According to the analysis report and the preset decision rules, corresponding decision opinions are automatically generated. For example, according to the adjustment suggestions of key factor indicators and the handling suggestions of abnormal influencing factors, corresponding decision opinions are generated. The generated decision opinions are presented to managers through visualization tools, such as reports, charts, dashboards, etc., to help them intuitively understand the decision opinions. According to different business needs and the personalized preferences of managers, customized decision opinion services are provided, such as providing personalized decision models and recommended strategies for different business scenarios.

[0077] In actual applications, users can input or adjust the key factor index values ​​through the system interface, and the system will immediately simulate the corresponding business conditions in the 3D data. At the same time, the system can also automatically capture abnormal influencing factors, and automatically adjust the influencing factors and coefficients when abnormalities are found, and generate corresponding decision opinions. Managers can make more accurate and timely decisions based on this information and the actual business situation.

[0078] This method first collects various business data through the business data collection module, uses the 3D data display module to display the 3D data of the business, and dynamically adjusts the key factor index value according to the settings of the management personnel; at the same time, the abnormal influencing factor capture module is used to capture the abnormal influencing factors of the business data, and the influencing factor system adjustment module automatically adjusts the influencing factors and their influencing coefficients. Through the comprehensive application of expert opinion method, Boost i ng, GBDT and other machine learning technologies, data adjustment is carried out, and the influencing coefficient quantification and influence degree analysis of the associated factors are carried out step by step to achieve comprehensive penetration of indicators. Finally, the decision opinion generation module automatically generates decision opinions based on the adjusted data.

[0079] The system constructed by this method can simulate the business operation status, provide managers with intuitive and comprehensive display, and help them better understand the business; it can dynamically adjust the key factor indicator values ​​according to the actual situation and the settings of managers, reflect its impact on the business in real time, and help managers make timely adjustments; through the analysis of historical data and real-time data, it can help managers trace the evolution of the business and better understand the changing trend of the business; it can analyze the relationship between upstream and downstream businesses, help managers grasp the operation status of the entire business chain, and better coordinate and manage various departments; it can timely discover and capture abnormal influencing factors, and help managers prevent potential risks and problems. The positioning influencing factor system automatically adjusts its influencing factors and influencing coefficients. The system can automatically analyze and adjust the influencing factors and their influencing coefficients, helping managers to more accurately and effectively evaluate the business status and give scientific and reasonable decision-making opinions.

[0080] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0081] In some embodiments, Figure 2 As shown, it shows a block diagram of a 3D model-based service management device 200 provided in an embodiment of the present application, including: a collection module 201, an editing module 202, a statistics module 203 and a monitoring module 204, wherein:

[0082] The acquisition module 201 is used to acquire business data and business process information, and perform three-dimensional coordinate conversion on the business data to obtain three-dimensional coordinates of each data, wherein the business data includes several types of business data;

[0083] The editing module 202 is used to perform graphic editing on the business data based on the three-dimensional coordinates to obtain multiple graphic elements, adjust the visual effects of the graphic elements to obtain a three-dimensional model, and perform interactive design based on the three-dimensional model to obtain a three-dimensional data display result;

[0084] The statistical module 203 is used to perform statistical analysis on the business data to obtain key factor indicators of each type of business data, and calculate the indicator value using the business data according to the key factor indicators to obtain the key indicator value;

[0085] The monitoring module 204 is used to set a preset threshold range for the type of business data corresponding to the key indicator value based on the key indicator value, and perform abnormal monitoring on the business data according to the preset threshold range. If the business data is not within the preset threshold range, the business data is judged to be abnormal and an abnormal reminder is issued so that the user can handle it according to the abnormal reminder.

[0086] In some embodiments, the business data is converted into three-dimensional coordinates to obtain the three-dimensional coordinates of each data, including:

[0087] Adjust or delete duplicate business data, abnormal business data and invalid business data in the business data to obtain complete business data;

[0088] Standardize the complete business data to obtain standard business data, and determine multiple key features of the standard business data based on the business needs and data characteristics of the standard business data;

[0089] Based on the key features, the standard business data is mapped and transformed using linear mapping or classification data mapping methods to obtain the three-dimensional coordinates of each standard business data.

[0090] In some embodiments, statistical analysis is performed on the business data to obtain key factor indicators of each type of business data, including:

[0091] Collect market data, feedback data and operational data;

[0092] Extract relationships between market data, feedback data, operational data, and business data to obtain key factor indicators for each type of business data.

[0093] In some embodiments, according to the key factor indicators, the indicator value is calculated using the business data to obtain the key indicator value, including:

[0094] Adjust or delete duplicate business data, abnormal business data, and invalid business data in market data, feedback data, operation data, and business data to obtain data cleaning results corresponding to each data;

[0095] Integrate the data cleaning results corresponding to each data to obtain a data set, define the calculation formula for each key factor indicator, and obtain the key indicator value based on the data set and the calculation formula.

[0096] In some embodiments, after the business process information is collected, the following is also included:

[0097] Build a model environment based on business environment information to obtain a sandbox simulation scenario;

[0098] Design the simulation process according to the business process data, design the simulation system according to the sandbox simulation scenario and simulation process, design the interactive function and data analysis function based on the model system, and obtain the sandbox simulation module to enable users to perform business simulation.

[0099] In one embodiment of the present application, a computer device is provided, which includes a memory and a processor, wherein a computer program is stored in the memory, and the above steps are implemented when the processor executes the computer program; the computer device provided in this embodiment has an implementation principle and technical effects similar to those of the above method embodiments, and will not be repeated here.

[0100] In one embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and the above steps are implemented when the computer program is executed by a processor; the computer-readable storage medium provided in this embodiment has an implementation principle and technical effects similar to those of the above method embodiment, and will not be repeated here.

[0101] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0102] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0103] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A business management method based on 3D model, characterized in that: include: Collecting business data and business process information, performing three-dimensional coordinate conversion on the business data to obtain three-dimensional coordinates of each data, wherein the business data includes several types of business data; Based on the three-dimensional coordinates, the business data is graphically edited to obtain a plurality of graphic elements, the visual effects of the graphic elements are adjusted to obtain a three-dimensional model, and interactive design is performed according to the three-dimensional model to obtain a three-dimensional data display result; Performing statistical analysis on the business data to obtain key factor indicators of each type of business data, and calculating indicator values ​​using the business data according to the key factor indicators to obtain key indicator values; Based on the key indicator value, a preset threshold range for business data of the type corresponding to the key indicator value is set, and the business data is monitored for abnormalities according to the preset threshold range. If the business data is not within the preset threshold range, the business data is judged to be abnormal and an abnormal reminder is issued, so that the user can handle it according to the abnormal reminder.

2. The 3D model-based business management method according to claim 1, characterized in that: The three-dimensional coordinate conversion of the business data to obtain the three-dimensional coordinates of each data includes: Adjust or delete duplicate business data, abnormal business data and invalid business data in the business data to obtain complete business data; Standardizing the complete business data to obtain standard business data, and determining multiple key features of the standard business data according to business requirements and data characteristics of the standard business data; Based on the key features, the standard business data is mapped and transformed using a linear mapping or a classification data mapping method to obtain three-dimensional coordinates of each of the standard business data.

3. The 3D model-based business management method according to claim 1, characterized in that: The statistical analysis of the business data to obtain key factor indicators of various types of business data includes: Collect market data, feedback data and operational data; Relationships are extracted between the market data, the feedback data, the operation data, and the business data to obtain key factor indicators of each type of business data.

4. The 3D model-based business management method according to claim 3, characterized in that: The step of calculating the indicator value based on the key factor indicator and using the business data to obtain the key indicator value includes: Adjust or delete duplicate business data, abnormal business data, and invalid business data in the market data, the feedback data, the operation data, and the business data to obtain data cleaning results corresponding to each data; The data cleaning results corresponding to the various data are integrated to obtain a data set, a calculation formula for each of the key factor indicators is defined, and the key indicator value is obtained according to the data set and the calculation formula.

5. The 3D model-based business management method according to claim 1, characterized in that: After the business process information is collected, it also includes: Build a model environment based on business environment information to obtain a sandbox simulation scenario; A simulation process is designed according to the business process data, a simulation system is designed according to the sandbox simulation scenario and the simulation process, and based on the model system, interactive functions and data analysis functions are designed to obtain a sandbox simulation module so that users can perform business simulation.

6. A business management device based on a 3D model, characterized in that: include: A collection module, used to collect business data and business process information, and perform three-dimensional coordinate conversion on the business data to obtain three-dimensional coordinates of each data, wherein the business data includes several types of business data; An editing module, used to perform graphic editing on the business data based on the three-dimensional coordinates to obtain a plurality of graphic elements, adjust the visual effects of the graphic elements to obtain a three-dimensional model, and perform interactive design based on the three-dimensional model to obtain a three-dimensional data display result; A statistical module is used to perform statistical analysis on the business data to obtain key factor indicators of each type of business data, and calculate the indicator value using the business data according to the key factor indicators to obtain the key indicator value; A monitoring module is used to set a preset threshold range for business data of the type corresponding to the key indicator value based on the key indicator value, and perform abnormal monitoring on the business data according to the preset threshold range. If the business data is not within the preset threshold range, the business data is judged to be abnormal and an abnormal reminder is issued, so that the user can handle it according to the abnormal reminder.

7. The 3D model-based business management device according to claim 6, characterized in that: The three-dimensional coordinate conversion of the business data to obtain the three-dimensional coordinates of each data includes: Adjust or delete duplicate business data, abnormal business data and invalid business data in the business data to obtain complete business data; Standardizing the complete business data to obtain standard business data, and determining multiple key features of the standard business data according to business requirements and data characteristics of the standard business data; Based on the key features, the standard business data is mapped and transformed using a linear mapping or a classification data mapping method to obtain three-dimensional coordinates of each of the standard business data.

8. The 3D model-based business management device according to claim 6, characterized in that: The statistical analysis of the business data to obtain key factor indicators of various types of business data includes: Collect market data, feedback data and operational data; Relationships are extracted between the market data, the feedback data, the operation data, and the business data to obtain key factor indicators of each type of business data.

9. A computer device, characterized in that: It comprises a processor and a memory, wherein the memory is used to store a computer program, and when the computer program is executed by the processor, the 3D model-based business management method as described in any one of claims 1 to 5 is implemented.

10. A computer-readable storage medium, characterized in that: It stores a computer program, which, when executed by a processor, implements the 3D model-based business management method as described in any one of claims 1 to 5.

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