Data processing method, data processing system, electronic equipment and readable storage medium

Abstract

The invention provides a data processing method, a data processing system, electronic equipment and a readable storage medium, and relates to the technical field of artificial intelligence, the method comprises the following steps: establishing a unified data warehouse according to source data; determining work information data of the digital employees based on the unified data warehouse, and determining post information and work distribution information according to the work information data; scheduling the digital employees according to the post information and the work distribution information, and generating scheduling information; performing data analysis on the post information, the work distribution information and the scheduling information, and generating an operation analysis report; and early warning and repairing abnormal data in the operation analysis report. According to the technical scheme, the work information data is determined based on the unified data warehouse, the post information, the work distribution information and the scheduling information are determined according to the work information data, and the operation analysis report is generated. According to the mode, the whole life cycle of the digital employees can be managed and controlled, and efficient, intelligent and closed-loop management of the digital employees is realized.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a data processing method, a data processing system, an electronic device and a readable storage medium. Background Art

[0002] In the related art, digital employee operation management methods or platforms mainly simulate the operations of human users on computers through predefined scripts to complete highly repetitive and standardized business processes. However, these methods or platforms lack digital employee management mechanisms and cannot manage the entire life cycle of digital employees.

[0003] Therefore, how to provide a data processing method that can manage the entire life cycle of digital employees and achieve efficient, intelligent, and closed-loop management of digital employees is an issue that urgently needs to be addressed. Summary of the invention

[0004] In order to solve or improve at least one of the above technical problems, an object of the present invention is to provide a data processing method.

[0005] Another object of the present invention is to provide a data processing system.

[0006] Another object of the present invention is to provide an electronic device.

[0007] Another object of the present invention is to provide a readable storage medium.

[0008] To achieve the above object, the present invention provides a data processing method in a first aspect, comprising the following steps: The first step is to establish a unified data warehouse based on source data; the source data includes one or a combination of the following: organizational data, user data, digital employee talent data and business data.

[0009] The second step is to determine the work information data of digital employees based on the unified data warehouse, and determine the position information and work assignment information of digital employees based on the work information data.

[0010] The third step is to schedule digital employees based on job information and work assignment information, and generate scheduling information.

[0011] The fourth step is to conduct data analysis on job information, work assignment information and scheduling information, and generate an operation analysis report.

[0012] The fifth step is to warn and repair abnormal data in the operation analysis report.

[0013] The present invention aims to provide a data processing method, which determines the work information data of digital employees based on a unified data warehouse, determines the position information, work allocation information and scheduling information based on the work information data, and generates an operation analysis report. This method can manage the entire life cycle of digital employees and realize efficient, intelligent and closed-loop management of digital employees.

[0014] In addition, the above technical solution provided by the present invention may also have the following additional technical features: In some technical solutions, optionally, a unified data warehouse is established based on source data, and the steps include: obtaining source data through a database system; and establishing a unified data warehouse based on the source data.

[0015] In this technical solution, organizational data, user data, digital employee talent data and business data are stored in a unified data format to establish a unified data warehouse, providing solid data support for subsequent operational analysis management, digital human resource management, operation and maintenance management and other functions.

[0016] In some technical solutions, optionally, a unified data warehouse is established based on the source data, and the steps include: before establishing the unified data warehouse based on the source data, performing data cleaning, data error correction and data deduplication on the source data.

[0017] In this technical solution, data cleaning can remove noise and erroneous information in the source data. Data cleaning is used to remove irrelevant, redundant and inconsistently formatted problematic data in the source data, making the source data more regular and easier to process.

[0018] Data error correction is used to correct erroneous information in source data to ensure data accuracy and consistency.

[0019] Data deduplication aims to eliminate duplicate records in source data, reduce data redundancy and improve data processing efficiency.

[0020] By preprocessing different types of source data (data cleaning, data error correction, and data deduplication), a high-quality unified data warehouse can be established, so that data processing methods can operate efficiently based on accurate and reliable data, ultimately achieving optimal allocation of enterprise resources and significantly improving business operation efficiency.

[0021] In some technical solutions, optionally, the operational analysis report includes utilization rate, idle rate and overload rate of digital employees, as well as average processing time and error rate.

[0022] In this technical solution, by analyzing the utilization rate, idle rate and overload rate of digital employees, as well as the average processing time and error rate, enterprise managers and platform operators can fully understand the operational status of digital employees, discover problems in a timely manner and take effective improvement measures, thereby continuously improving the efficiency of the digital employee operation management platform and promoting the continuous progress of enterprise digital transformation and business development.

[0023] In some technical solutions, optionally, abnormal data in the operation analysis report is warned and repaired, and the steps include: monitoring the operation analysis report; sending the abnormal data in the operation analysis report to the control terminal via SMS or email.

[0024] In this technical solution, various data indicators in the operation analysis report are continuously scanned and compared according to pre-defined monitoring rules and thresholds, thereby realizing the monitoring of the operation analysis report.

[0025] Abnormal data in the operation analysis report is sent to the control terminal via SMS or email to promptly remind the platform or management personnel, thereby achieving automatic early warning of abnormal data.

[0026] In some technical solutions, optionally, abnormal data in the operation analysis report is warned and repaired, and the steps include: after the abnormal data in the operation analysis report is sent to the control terminal via SMS or email, a work order is dispatched to the digital employee based on the abnormal data to repair the abnormal data.

[0027] In this technical solution, while automatically issuing warnings, work orders are dispatched to digital employees, forming a closed-loop management of risk warnings and ensuring the high availability and stability of digital employees.

[0028] Optionally, the operation analysis report is used to record the repair information of the abnormal data. The repair information includes but is not limited to the repair time, repair measures, digital employees involved in the repair, and repair result verification information.

[0029] In some technical solutions, optionally, the steps of the data processing method also include: before warning and repairing the abnormal data in the operation analysis report, displaying the operation analysis report through a visualization device.

[0030] In this technical solution, real-time monitoring of digital employees is achieved through the use of an intuitive visual interface, which is conducive to improving management efficiency.

[0031] A second aspect of the present invention provides a data processing system, including a basic data management module, a digital human resources management module, an operation analysis management module and an operation and maintenance management module.

[0032] The basic data management module is used to establish a unified data warehouse based on source data, where the source data includes one or a combination of the following: organizational data, user data, digital employee talent data, and business data.

[0033] The digital human resource management module is used to determine the work information data of digital employees based on the unified data warehouse, and to determine the position information and work assignment information of digital employees based on the work information data.

[0034] The digital human resource management module is used to schedule digital employees according to job information and work assignment information, and generate scheduling information.

[0035] The operation analysis management module is used to perform data analysis on job information, work assignment information and scheduling information, and generate operation analysis reports.

[0036] The operation and maintenance management module is used to warn and repair abnormal data in the operation analysis report.

[0037] The present invention aims to provide a data processing system that determines the work information data of digital employees based on a unified data warehouse, determines job information, work assignment information and scheduling information based on the work information data, and generates an operation analysis report. This method can manage the entire life cycle of digital employees and achieve efficient, intelligent and closed-loop management of digital employees.

[0038] The third aspect of the present invention provides an electronic device, comprising a memory and a processor. The memory stores a program or instruction that can be run on the processor, and the processor implements the steps of the data processing method in any of the above technical solutions when executing the program or instruction. Therefore, the electronic device has the beneficial effects of any of the above technical solutions, which will not be repeated here.

[0039] In a fourth aspect, the present invention provides a readable storage medium, which stores a program or instruction, and when the program or instruction is executed by a processor, the steps of the data processing method in any of the above technical solutions are implemented. Therefore, the readable storage medium has the beneficial effects of any of the above technical solutions, which will not be repeated here.

[0040] Additional aspects and advantages of the technical solutions of the present invention will become apparent in the following description or will be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A flow chart showing a data processing method according to an embodiment of the present invention is shown; Figure 2 A flow chart showing a data processing method according to another embodiment of the present invention is shown; Figure 3A flow chart showing a data processing method according to another embodiment of the present invention is shown; Figure 4 A flow chart showing a data processing method according to another embodiment of the present invention is shown; Figure 5 A flow chart showing a data processing method according to another embodiment of the present invention is shown; Figure 6 A flow chart showing a data processing method according to another embodiment of the present invention is shown; Figure 7 A structural block diagram of a data processing system according to an embodiment of the present invention is shown; Figure 8 A structural block diagram of a data processing system according to another embodiment of the present invention is shown; Fig. 9 A structural block diagram of an electronic device according to an embodiment of the present invention is shown.

[0042] in, Figures 1 to 9 The corresponding relationship between the reference numerals and the component names is as follows: 200: data processing system; 210: basic data management module; 220: digital human resource management module; 230: operation analysis management module; 240: operation and maintenance management module; 250: interface service management module; 300: electronic equipment; 310: memory; 320: processor. DETAILED DESCRIPTION

[0043] In order to more clearly understand the above-mentioned purposes, features and advantages of the embodiments of the present invention, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and specific implementation methods. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0044] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the embodiments of the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0045] Refer to the following Figures 1 to 9 The data processing method, data processing system 200, electronic device 300 and readable storage medium provided according to some embodiments of the present invention are described.

[0046] In one embodiment according to the present invention, Figure 1 As shown, the steps of the data processing method include: S102, establishing a unified data warehouse based on source data; wherein the source data includes one of the following or a combination thereof: organizational data, user data, digital employee talent data, and business data.

[0047] When the source data is of one type, the source data includes only one of organizational data, user data, digital employee talent data, and business data. When the source data is of multiple types, the source data includes any combination of organizational data, user data, digital employee talent data, and business data.

[0048] As an important part of source data, organizational data includes the structural information of various departments within the enterprise. Organizational data includes but is not limited to department name data, department hierarchy data, and department function description data. These data or information help to clarify the positioning and collaborative relationship of digital employees in the enterprise organizational system. For example, by analyzing the flow of business processes between departments, the paths and rules for data interaction between digital employees in different departments can be determined, thereby providing a basis for their task allocation and process automation.

[0049] User data includes but is not limited to identity information data, operation authority data and operation history. Identity information data includes user name, user ID and contact information.

[0050] User data is essential for achieving personalized digital employee services and accurate permission management. For example, based on the operation history in user data, the usage preferences and frequency of digital employee functions of different users can be analyzed, and then digital employee services that better meet their needs can be recommended to users or the task execution strategies of digital employees can be optimized. In addition, through the effective management of user permission data, the security and compliance of enterprise data can be guaranteed, and unauthorized access and operation can be prevented.

[0051] Digital employee talent data covers information related to the characteristics and capabilities of digital employees themselves. Digital employee talent data includes but is not limited to the types of digital employees, algorithm models, work efficiency index data, and training and growth record data.

[0052] The types of digital employees include data processing and business process execution. Work efficiency indicator data include task processing time and accuracy.

[0053] With the help of digital employee talent data, enterprises can optimize the configuration of digital employee teams just like managing human resources. For example, when faced with complex business tasks, they can reasonably arrange the division of tasks based on the skills and expertise of digital employees (the algorithm models they possess) to improve the quality and efficiency of overall task completion. At the same time, through the analysis of digital employee training and growth records, they can plan further capacity improvement paths for them in a targeted manner and achieve the continuous development and evolution of digital employees.

[0054] Business data is used to reflect various business activity information during the actual operation of the enterprise. Business data includes but is not limited to sales data, production data and customer service data.

[0055] Business data is an important basis and operation object for digital employees to perform tasks. For example, when digital employees are processing sales order process automation tasks, they need to read order details, customer information and other content in the sales data; when automating customer service responses, they need to intelligently respond and process based on customer consultation records and problem types in the customer service data. By integrating business data into a unified data warehouse, digital employees can understand the business needs of the enterprise more comprehensively and accurately, thereby playing a greater role in various business links, improving the efficiency of the enterprise's business operations and optimizing the use of resources.

[0056] In a specific embodiment, organizational data, user data, digital employee talent data and business data are stored in a unified data format to establish a unified data warehouse, providing solid data support for subsequent operational analysis management, digital human resource management, operation and maintenance management and other functions.

[0057] S104, determining the work information data of the digital employee based on the unified data warehouse, and determining the position information and work assignment information of the digital employee according to the work information data.

[0058] Work information data includes but is not limited to basic information, performance parameters and task execution records.

[0059] The basic information of digital employees includes but is not limited to identity, creation time and category.

[0060] The identity identifier can be understood as a unique number, which makes it easy to quickly locate specific digital employees in massive data and complex business processes.

[0061] The creation time is used to reflect the "seniority" of digital employees, which is of great significance for the analysis of some business scenarios involving version iteration and experience accumulation effects.

[0062] The categories reflect the functional positioning of digital employees, such as data processing, process automation, and intelligent decision-making assistance. Data processing digital employees are good at cleaning, organizing, and analyzing data; process automation digital employees can accurately and efficiently perform repetitive tasks according to preset business process rules; intelligent decision-making assistance digital employees can provide valuable reference suggestions for corporate management in key decision-making links such as strategic planning and risk assessment based on complex algorithm models and data analysis results.

[0063] Performance parameters are the core indicators for measuring the work ability and efficiency of digital employees. Performance parameters include but are not limited to task processing speed, accuracy and resource utilization. Task processing speed indicates the number of tasks that digital employees can complete or the amount of data processed in a unit of time. Accuracy is used to reflect the reliability of digital employees' work. Resource utilization is used to reflect the consumption of computer hardware resources by digital employees in the process of executing tasks. Reasonable resource utilization can ensure that digital employees work efficiently without affecting the normal operation of other systems or digital employees due to excessive resource occupation.

[0064] Task execution records include, but are not limited to, task type, task timestamp, and task result data.

[0065] Task types refer to the types of business that digital employees have handled. By analyzing task types, we can more accurately assess the adaptability and proficiency of digital employees in different business areas, providing a strong reference for subsequent job deployment.

[0066] The task timestamp is the start time, end time, and execution duration of each task of the digital employee.

[0067] Task result data is used to visually reflect the completion status of each task of the digital employee, whether it is successfully completed, partially completed or failed.

[0068] The job information of digital employees can be scientifically and reasonably determined based on the work information data. After the job information is determined, the work assignment information is further determined based on factors such as the current business needs of the enterprise, task priorities, and the real-time status of digital employees.

[0069] This data processing method can achieve the optimal allocation of digital employee resources, maximize the value of digital employees in enterprise operations and management, and improve the overall operational efficiency and competitiveness of the enterprise.

[0070] S106, scheduling digital employees according to the position information and work allocation information, and generating scheduling information.

[0071] Example of scheduling digital employees: Digital employees who process tasks quickly and accurately can be assigned to core data processing positions if they have an outstanding record of executing data processing tasks.

[0072] Scheduling information includes but is not limited to timestamp information, original position information, new position information, and task progress information.

[0073] The timestamp information includes the scheduled start time.

[0074] The original position information and the new position information are used to reflect the position transfer of digital employees.

[0075] The task progress information includes the progress data of the original task, the requirement information of the newly assigned task, and the required target information.

[0076] By flexibly allocating digital employee resources, we ensure that each digital employee can handle the most appropriate task in the most appropriate position, thereby achieving efficient and automated operation of the company's business processes, improving the company's overall operational efficiency and competitiveness, and also providing strong data support and decision-making basis for the continuous optimization of the platform and the management of the digital employee team.

[0077] S108, performing data analysis on the position information, work allocation information and scheduling information, and generating an operation analysis report.

[0078] Analysis of job information: Job information is used to reflect the functional positioning structure of digital employees in the enterprise business system. By analyzing job information, we can understand the distribution of the number of different jobs.

[0079] Analysis of work assignment information: Work assignment information is used to reflect the specific work content and workload of each digital employee.

[0080] Analysis of scheduling information: Scheduling information is used to reflect the process and reasons for the deployment of digital employees between different positions.

[0081] The operation analysis report covers key indicators and analysis conclusions in multiple dimensions.

[0082] In terms of the efficiency of digital employee resource utilization, the operation analysis report includes indicators such as the overall digital employee utilization rate (the ratio of actual working time to available working time), the idle rate and overload rate of digital employees in each position, etc.

[0083] In terms of business process execution effectiveness, the operation analysis report includes data such as the average processing time and error rate of the business process.

[0084] Optionally, the operational analysis report includes information on improvement suggestions and optimization strategies for the problems found. For example, if a business process is found to be inefficient due to unreasonable digital employee task allocation, the operational analysis report should propose a specific task reallocation plan or a digital employee skill improvement plan.

[0085] Through operational analysis reports, enterprise managers and platform operators can fully understand the operational status of digital employees, identify problems in a timely manner and take effective improvement measures, thereby continuously improving the efficiency of the digital employee operation management platform and promoting the continuous progress of enterprise digital transformation and business development.

[0086] S110, early warning and repair of abnormal data in the operation analysis report.

[0087] Abnormal data in the operation analysis report is automatically warned and work orders are dispatched through SMS, email, OA (Office Automation), etc., forming a closed-loop management of risk warnings to ensure the high availability and stability of digital employees.

[0088] Optionally, the operation analysis report is used to record the repair information of the abnormal data. The repair information includes but is not limited to the repair time, repair measures, digital employees involved in the repair, and repair result verification information.

[0089] The present invention aims to provide a data processing method, which determines the work information data of digital employees based on a unified data warehouse, determines the position information, work allocation information and scheduling information based on the work information data, and generates an operation analysis report. This method can manage the entire life cycle of digital employees and realize efficient, intelligent and closed-loop management of digital employees.

[0090] It should be noted that the scope of scheduling digital employees includes but is not limited to job recruitment, department onboarding, work assignment, performance appraisal and capacity improvement management.

[0091] In the related art, digital employee operation management methods or platforms mainly simulate the operations of human users on computers through predefined scripts to complete highly repetitive and standardized business processes. However, these methods or platforms lack digital employee management mechanisms and cannot manage the entire life cycle of digital employees.

[0092] The present invention relates to the field of enterprise automation and intelligent management technology, and more specifically, to a digital employee operation management method (i.e., data processing method) based on RPA (Robotic Process Automation) technology. The data processing method has multiple functions (including but not limited to basic data management, digital human resource management, operation analysis management, and operation and maintenance management). Through visual monitoring of digital employees (reflected in operation analysis reports), digital intelligence (the fusion of "digitalization" and "intelligence") management, and centralized interaction, the closed-loop control of the entire life cycle of digital employees is achieved, aiming to optimize enterprise resource utilization and improve business operation efficiency.

[0093] In some embodiments, optionally, Figure 2 As shown, the steps of S102 (establishing a unified data warehouse based on source data) include: S1022, obtaining source data through a database system.

[0094] Database systems include, but are not limited to, MySQL (an open source relational database management system), Oracle (a powerful commercial relational database management system), and SQL Server (a relational database management system).

[0095] In another embodiment, the database system includes but is not limited to an enterprise management information system storing organizational data, an identity authentication system storing user data, a database of a digital employee management platform storing digital employee talent data, and a business system database recording business data.

[0096] When the source data is of one type, the source data includes only one of organizational data, user data, digital employee talent data, and business data. When the source data is of multiple types, the source data includes any combination of organizational data, user data, digital employee talent data, and business data.

[0097] S1024, establish a unified data warehouse based on source data.

[0098] Store organizational data, user data, digital employee talent data and business data in a unified data format to establish a unified data warehouse, providing solid data support for subsequent operational analysis management, digital human resources management, operation and maintenance management and other functions.

[0099] In some embodiments, optionally, Figure 3 As shown, before S1024 (establishing a unified data warehouse according to source data), S102 (establishing a unified data warehouse according to source data) further includes: S1023, perform data cleaning, data error correction and data deduplication on the source data.

[0100] The purpose of this step is to preprocess different types of source data, including but not limited to data cleaning, data error correction, and data deduplication.

[0101] Among them, data cleaning can remove noise and erroneous information in the source data. Data cleaning is used to remove irrelevant, redundant and inconsistently formatted problematic data in the source data, making the source data more regular and easier to process.

[0102] Optionally, data cleaning includes removing invalid department name data in the organizational data.

[0103] In the organizational data, there may be some outdated or invalid department name data, which may be left over after the enterprise organizational structure adjustment. The data cleansing process will identify and delete this invalid information to ensure that the organizational data can accurately reflect the current enterprise's real structure.

[0104] Optionally, data cleaning includes deleting identity information data in the user data that is used for testing or has not been used for a long time. The purpose of this step is to improve the accuracy and availability of the user data.

[0105] Data error correction is used to correct erroneous information in source data to ensure data accuracy and consistency.

[0106] Data error correction includes, but is not limited to: correcting incorrect contact information in user data and correcting entry errors in business data.

[0107] Data deduplication aims to eliminate duplicate records in source data, reduce data redundancy and improve data processing efficiency. Data deduplication includes but is not limited to: removing duplicate user data.

[0108] By preprocessing different types of source data (data cleaning, data error correction, and data deduplication), a high-quality unified data warehouse can be established, so that data processing methods can operate efficiently based on accurate and reliable data, ultimately achieving optimal allocation of enterprise resources and significantly improving business operation efficiency.

[0109] In some embodiments, optionally, the operational analysis report includes utilization, idle rate, and overload rate of digital workers, as well as average processing time and error rate.

[0110] In terms of the efficiency of digital employee resource utilization, the operation analysis report includes indicators such as the overall digital employee utilization rate (the ratio of actual working time to available working time), the idle rate and overload rate of digital employees in each position, etc.

[0111] In terms of business process execution effectiveness, the operation analysis report includes data such as the average processing time and error rate of the business process.

[0112] By analyzing the utilization rate, idle rate and overload rate of digital employees, as well as the average processing time and error rate, enterprise managers and platform operators can fully understand the operational status of digital employees, identify problems in a timely manner and take effective improvement measures, thereby continuously improving the efficiency of the digital employee operation management platform and promoting the continuous progress of enterprise digital transformation and business development.

[0113] In some embodiments, optionally, Figure 4 As shown, the steps of S110 (early warning and repairing abnormal data in the operation analysis report) include: S1102, monitor the operation analysis report.

[0114] The various data indicators in the operation analysis report are continuously scanned and compared according to the pre-defined monitoring rules and thresholds, so as to realize the monitoring of the operation analysis report.

[0115] Determine whether there is abnormal data in the operation analysis report and generate a first determination result; if the first determination result is yes, execute S1104; if the first determination result is no, continue to monitor the operation analysis report.

[0116] It should be noted that abnormal data includes but is not limited to: average task processing time that exceeds the normal threshold.

[0117] S1104, sending the abnormal data in the operation analysis report to the control terminal via SMS or email.

[0118] This method can timely alert the platform or management personnel, thereby realizing automatic early warning of abnormal data. Enterprises can receive reminder signals at the first time and take effective response measures in time, thereby minimizing the negative impact of abnormal situations on business operations.

[0119] In some embodiments, optionally, Figure 5 As shown, after S1104 (sending the abnormal data in the operation analysis report to the control terminal via SMS or email), S110 (warning and repairing the abnormal data in the operation analysis report) also includes: S1105, dispatching work orders to digital employees based on the abnormal data to repair the abnormal data.

[0120] While automatically issuing warnings, work orders are dispatched to digital employees to form a closed-loop management of risk warnings, ensuring the high availability and stability of digital employees.

[0121] Optionally, the operation analysis report is used to record the repair information of the abnormal data. The repair information includes but is not limited to the repair time, repair measures, digital employees involved in the repair, and repair result verification information.

[0122] In some embodiments, optionally, Figure 6 As shown, before S110 (warning and repairing abnormal data in the operation analysis report), the steps of the data processing method also include: S109, displaying the operation analysis report through a visualization device.

[0123] By adopting an intuitive visual interface, real-time monitoring of digital employees can be achieved, which helps improve management efficiency.

[0124] In one embodiment according to the present invention, Figure 7 As shown, the data processing system 200 includes a basic data management module 210 , a digital human resources management module 220 , an operation analysis management module 230 and an operation and maintenance management module 240 .

[0125] The basic data management module 210 is used to establish a unified data warehouse based on source data, wherein the source data includes one or a combination of the following: organizational data, user data, digital employee talent data, and business data.

[0126] The basic data management module 210 is connected to various database systems through API (Application Programming Interface) and RPA (Robotic Process Automation) automation technology to obtain various types of source data.

[0127] It should be noted that database systems include but are not limited to MySQL (an open source relational database management system), Oracle (a powerful commercial relational database management system) and SQL Server (a relational database management system).

[0128] When the source data is of one type, the source data includes only one of organizational data, user data, digital employee talent data, and business data. When the source data is of multiple types, the source data includes any combination of organizational data, user data, digital employee talent data, and business data.

[0129] As an important part of source data, organizational data includes the structural information of various departments within the enterprise. Organizational data includes but is not limited to department name data, department hierarchy data, and department function description data. These data or information help to clarify the positioning and collaborative relationship of digital employees in the enterprise organizational system. For example, by analyzing the flow of business processes between departments, the paths and rules for data interaction between digital employees in different departments can be determined, thereby providing a basis for their task allocation and process automation.

[0130] User data includes but is not limited to identity information data, operation authority data and operation history. Identity information data includes user name, user ID and contact information.

[0131] User data is essential for achieving personalized digital employee services and accurate permission management. For example, based on the operation history in user data, the usage preferences and frequency of digital employee functions of different users can be analyzed, and then digital employee services that better meet their needs can be recommended to users or the task execution strategies of digital employees can be optimized. In addition, through the effective management of user permission data, the security and compliance of enterprise data can be guaranteed, and unauthorized access and operation can be prevented.

[0132] Digital employee talent data covers information related to the characteristics and capabilities of digital employees themselves. Digital employee talent data includes but is not limited to the types of digital employees, algorithm models, work efficiency index data, and training and growth record data.

[0133] The types of digital employees include data processing and business process execution. Work efficiency indicator data include task processing time and accuracy.

[0134] With the help of digital employee talent data, enterprises can optimize the configuration of digital employee teams just like managing human resources. For example, when faced with complex business tasks, they can reasonably arrange the division of tasks based on the skills and expertise of digital employees (the algorithm models they possess) to improve the quality and efficiency of overall task completion. At the same time, through the analysis of digital employee training and growth records, they can plan further capacity improvement paths for them in a targeted manner and achieve the continuous development and evolution of digital employees.

[0135] Business data is used to reflect various business activity information during the actual operation of the enterprise. Business data includes but is not limited to sales data, production data and customer service data.

[0136] Business data is an important basis and operation object for digital employees to perform tasks. For example, when digital employees are processing sales order process automation tasks, they need to read order details, customer information and other content in the sales data; when automating customer service responses, they need to intelligently respond and process based on customer consultation records and problem types in the customer service data. By integrating business data into a unified data warehouse, digital employees can understand the business needs of the enterprise more comprehensively and accurately, thereby playing a greater role in various business links, improving the efficiency of the enterprise's business operations and optimizing the use of resources.

[0137] In a specific embodiment, the basic data management module 210 stores organizational data, user data, digital employee talent data and business data in a unified data format to establish a unified data warehouse, providing solid data support for subsequent functional modules such as operation analysis management, digital human resource management, and operation and maintenance management, and realizing efficient circulation and value mining of data in the entire digital employee operation management platform (data processing system 200).

[0138] The digital human resource management module 220 is used to determine the work information data of the digital employees based on the unified data warehouse, and determine the position information and work assignment information of the digital employees according to the work information data.

[0139] Work information data includes but is not limited to basic information, performance parameters and task execution records.

[0140] The basic information of digital employees includes but is not limited to identity, creation time and category.

[0141] The identity identifier can be understood as a unique number, which makes it easy to quickly locate specific digital employees in massive data and complex business processes.

[0142] The creation time is used to reflect the "seniority" of digital employees, which is of great significance for the analysis of some business scenarios involving version iteration and experience accumulation effects.

[0143] The categories reflect the functional positioning of digital employees, such as data processing, process automation, and intelligent decision-making assistance. Data processing digital employees are good at cleaning, organizing, and analyzing data; process automation digital employees can accurately and efficiently perform repetitive tasks according to preset business process rules; intelligent decision-making assistance digital employees can provide valuable reference suggestions for corporate management in key decision-making links such as strategic planning and risk assessment based on complex algorithm models and data analysis results.

[0144] Performance parameters are the core indicators for measuring the work ability and efficiency of digital employees. Performance parameters include but are not limited to task processing speed, accuracy and resource utilization. Task processing speed indicates the number of tasks that digital employees can complete or the amount of data processed in a unit of time. Accuracy is used to reflect the reliability of digital employees' work. Resource utilization is used to reflect the consumption of computer hardware resources by digital employees in the process of executing tasks. Reasonable resource utilization can ensure that digital employees work efficiently without affecting the normal operation of other systems or digital employees due to excessive resource occupation.

[0145] Task execution records include, but are not limited to, task type, task timestamp, and task result data.

[0146] Task types refer to the types of business that digital employees have handled. By analyzing task types, we can more accurately assess the adaptability and proficiency of digital employees in different business areas, providing a strong reference for subsequent job deployment.

[0147] The task timestamp is the start time, end time, and execution duration of each task of the digital employee.

[0148] Task result data is used to visually reflect the completion status of each task of the digital employee, whether it is successfully completed, partially completed or failed.

[0149] The job information of digital employees can be scientifically and reasonably determined based on the work information data. After the job information is determined, the work assignment information is further determined based on factors such as the current business needs of the enterprise, task priorities, and the real-time status of digital employees.

[0150] This data processing method can achieve the optimal allocation of digital employee resources, maximize the value of digital employees in enterprise operations and management, and improve the overall operational efficiency and competitiveness of the enterprise.

[0151] The digital human resource management module 220 is used to schedule digital employees according to job information and work assignment information, and generate scheduling information.

[0152] Example of scheduling digital employees: Digital employees who process tasks quickly and accurately can be assigned to core data processing positions if they have an outstanding record of executing data processing tasks.

[0153] Scheduling information includes but is not limited to timestamp information, original position information, new position information, and task progress information.

[0154] The timestamp information includes the scheduled start time.

[0155] The original position information and the new position information are used to reflect the position transfer of digital employees.

[0156] The task progress information includes the progress data of the original task, the requirement information of the newly assigned task, and the required target information.

[0157] By flexibly allocating digital employee resources, we ensure that each digital employee can handle the most appropriate task in the most appropriate position, thereby achieving efficient and automated operation of the company's business processes, improving the company's overall operational efficiency and competitiveness, and also providing strong data support and decision-making basis for the continuous optimization of the platform and the management of the digital employee team.

[0158] The operation analysis management module 230 is used to perform data analysis on position information, work allocation information and scheduling information, and generate an operation analysis report.

[0159] Analysis of job information: Job information is used to reflect the functional positioning structure of digital employees in the enterprise business system. By analyzing job information, we can understand the distribution of the number of different jobs.

[0160] Analysis of work assignment information: Work assignment information is used to reflect the specific work content and workload of each digital employee.

[0161] Analysis of scheduling information: Scheduling information is used to reflect the process and reasons for the deployment of digital employees between different positions.

[0162] The operation analysis report covers key indicators and analysis conclusions in multiple dimensions.

[0163] In terms of the efficiency of digital employee resource utilization, the operation analysis report includes indicators such as the overall digital employee utilization rate (the ratio of actual working time to available working time), the idle rate and overload rate of digital employees in each position, etc.

[0164] In terms of business process execution effectiveness, the operation analysis report includes data such as the average processing time and error rate of the business process.

[0165] Optionally, the operational analysis report includes information on improvement suggestions and optimization strategies for the problems found. For example, if a business process is found to be inefficient due to unreasonable digital employee task allocation, the operational analysis report should propose a specific task reallocation plan or a digital employee skill improvement plan.

[0166] Through operational analysis reports, enterprise managers and platform operators can fully understand the operational status of digital employees, identify problems in a timely manner and take effective improvement measures, thereby continuously improving the efficiency of the digital employee operation management platform and promoting the continuous progress of enterprise digital transformation and business development.

[0167] The operation and maintenance management module 240 is used to warn and repair abnormal data in the operation analysis report.

[0168] Abnormal data in the operation analysis report is automatically warned and work orders are dispatched through SMS, email, OA (Office Automation), etc., forming a closed-loop management of risk warnings to ensure the high availability and stability of digital employees.

[0169] Optionally, the operation analysis report is used to record the repair information of the abnormal data. The repair information includes but is not limited to the repair time, repair measures, digital employees involved in the repair, and repair result verification information.

[0170] The present invention aims to provide a data processing system 200, which determines the work information data of digital employees based on a unified data warehouse, determines the position information, work allocation information and scheduling information based on the work information data, and generates an operation analysis report. This method can manage the entire life cycle of digital employees and achieve efficient, intelligent and closed-loop management of digital employees.

[0171] It should be noted that the scope of scheduling digital employees includes but is not limited to job recruitment, department onboarding, work assignment, performance appraisal and capacity improvement management.

[0172] In the related art, digital employee operation management methods or platforms mainly simulate the operations of human users on computers through predefined scripts to complete highly repetitive and standardized business processes. However, these methods or platforms lack digital employee management mechanisms and cannot manage the entire life cycle of digital employees.

[0173] The present invention relates to the field of enterprise automation and intelligent management technology, and specifically, to a digital employee operation management platform (i.e., data processing system 200) based on RPA (Robotic Process Automation) technology. The data processing system 200 integrates multiple modules (including but not limited to a basic data management module 210, a digital human resources management module 220, an operation analysis management module 230, and an operation and maintenance management module 240), and realizes closed-loop control of the entire life cycle of digital employees through visual monitoring, digital intelligence (the abbreviation of the integration of "digitalization" and "intelligence") management, and centralized interaction of digital employees, aiming to optimize enterprise resource utilization and improve business operation efficiency.

[0174] In a specific embodiment, Figure 8 As shown, the integrated RPA digital employee operation management platform (i.e., data processing system 200) includes a basic data management module 210, a digital human resources management module 220, an operation analysis management module 230, an operation and maintenance management module 240 and an interface service management module 250.

[0175] Among them, the basic data management module 210 connects with various database systems through API interfaces (Application Programming Interface) and RPA automation technology to obtain various types of source data. It cleans, corrects errors, removes duplicates, and synchronizes organizational information, user information, digital employee talent information or business data to establish a unified data warehouse and provide data support for subsequent operation management.

[0176] It should be noted that database systems include but are not limited to MySQL (an open source relational database management system), Oracle (a powerful commercial relational database management system) and SQL Server (a relational database management system).

[0177] The basic data management module 210 is used to establish a unified data warehouse to centrally store basic information, performance parameters, and task execution records of digital employees.

[0178] The basic data management function is implemented through the basic data management module 210. The basic data management function includes organizational management and synchronization, supports custom roles, supports user management, digital employee expert management, digital employee talent management, supports import and export query functions, supports user authority configuration, supports R&D team management, and provides data support for subsequent operation management.

[0179] The digital human resources management module 220 is based on an anthropomorphic management model and, starting from the needs of enterprise construction, implements the management process of digital employees' job recruitment, department onboarding, work assignment, performance appraisal, and capacity improvement, and conducts closed-loop management and control of the entire life cycle of digital employees, ensuring that the digital employee team is highly matched with business needs and that business tasks are completed efficiently.

[0180] The digital human resource management module 220 supports the full life cycle management of digital employees, including recruitment, training, deployment, and upgrading, and supports closed-loop management of the entire life cycle of digital employees. It is used for digital employee resource planning (including scenario planning, employee planning, resource planning, job planning processes, etc.), demand acceptance, resource assessment, online deployment, assessment or evaluation, to ensure that the digital employee team is highly matched with business needs.

[0181] The operation analysis management module 230 uses big data analysis technology to monitor and track the operating status of digital employees, conduct in-depth mining and analysis of the operation data of digital employees, display the operating efficiency and key indicators of digital employees from different dimensions such as efficiency, benefits, scenarios, and fields, identify operational bottlenecks, and generate operation analysis reports to assist in continuous optimization and improvement.

[0182] Based on big data analysis technology, the operation data (scheduling information) of digital employees is deeply mined, including digital employee efficiency analysis, system usability analysis, demand scenario analysis, demand construction analysis, planning map, and professional talent construction analysis. It supports the data presentation of digital employees in different professional fields (through visualization devices, such as large, medium and small screens), and provides operational analysis reports such as business trend forecasts and performance bottleneck identification.

[0183] The operation and maintenance management module 240 realizes intelligent control and early warning management of digital employees, monitors digital employees in real time, and automatically warns and dispatches work orders for faults that occur during operation (abnormal data in the operation analysis report) through SMS, email, OA (Office Automation), etc., forming a closed-loop management of risk warnings to ensure the high availability and stability of digital employees.

[0184] The operation and maintenance management module 240 is used to realize functions such as real-time monitoring, fault warning, automatic repair, and intelligent scheduling of digital employees, ensuring the high availability and stability of digital employees.

[0185] The interface service management module 250 is used to provide a rich API interface, support connection with other business systems or cloud platforms, and realize data interconnection.

[0186] Optionally, the basic data management module 210 is connected to the database system through the interface service management module 250 to obtain source data.

[0187] The present invention aims to provide an integrated RPA digital employee operation and management platform (i.e., data processing system 200), which realizes efficient, intelligent, and closed-loop management of digital employees by introducing a full life cycle optimization algorithm.

[0188] It should be noted that the full life cycle optimization algorithm runs through the entire life cycle of digital employees. It achieves continuous improvement of digital employees' performance and maximum utilization of resources by dynamically adjusting resource allocation, optimizing task execution paths, and intelligently recommending optimization strategies.

[0189] The following is a code example of the full life cycle optimization algorithm (simplified version): function OptimizeDigitalEmployeeLifecycle(): while True: data = CollectPerformanceData() analysis = PerformAnalytics(data) if analysis.indicatesImprovementNeeded(): plan = GenerateOptimizationPlan(analysis) ApplyPlan(plan) monitorResult = MonitorResults(plan) if monitorResult.isSuccess(): updateModels(monitorResult) else: rollbackPlan() sleep(interval).

[0190] The advantages of the data processing system 200 of the present invention are: first, it adopts a full life cycle optimization algorithm to achieve continuous improvement of digital employee performance through dynamic optimization and intelligent decision-making; second, it adopts an integrated management platform, which integrates multiple functional modules (including but not limited to basic data management module 210, digital human resources management module 220, operation analysis management module 230 and operation and maintenance management module 240) to form a complete digital employee management system; third, it adopts visual monitoring and centralized management, provides an intuitive visual interface, and realizes real-time monitoring of digital employees, which is conducive to improving management efficiency.

[0191] It should be emphasized that the data processing system 200 realizes full life cycle management from planning to assessment or evaluation, making up for the shortcomings of existing technologies in this regard; by introducing a full life cycle optimization algorithm, it realizes the intelligence and automation of digital employee management, reduces human intervention, and improves management efficiency; it integrates multiple functional modules and provides a rich API interface to facilitate integration and expansion with other systems.

[0192] In one embodiment according to the present invention, Fig. 9 As shown, the electronic device 300 includes a memory 310 and a processor 320. The memory 310 stores a program or instruction that can be run on the processor 320, and the processor 320 implements the steps of the data processing method in any of the above embodiments when executing the program or instruction. Therefore, the electronic device 300 has the beneficial effects of any of the above embodiments, which will not be repeated here.

[0193] In one embodiment of the present invention, the readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of the data processing method in any of the above embodiments are implemented. Therefore, the readable storage medium has the beneficial effects of any of the above embodiments, which will not be repeated here.

[0194] In the present invention, the terms "first", "second", and "third" are used for descriptive purposes only and should not be understood as indicating or implying relative importance; the term "plurality" refers to two or more, unless otherwise clearly defined. The terms "installed", "connected", "connected", "fixed", etc. should be understood in a broad sense. For example, "connected" can be a fixed connection, a detachable connection, or an integral connection; "connected" can be a direct connection or an indirect connection through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0195] In the description of the present invention, it is necessary to understand that the directions or positional relationships indicated by terms such as “upper”, “lower”, “left”, “right”, “front” and “back” are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or unit referred to must have a specific direction, be constructed and operated in a specific orientation, and therefore, cannot be understood as a limitation on the present invention.

[0196] In the description of this specification, the description of the terms "one embodiment", "some embodiments", "specific embodiments", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0197] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A data processing method, characterized in that: include: Establishing a unified data warehouse based on source data; wherein the source data includes one or a combination of the following: organizational data, user data, digital employee talent data, and business data; Determine the work information data of the digital employee based on the unified data warehouse, and determine the position information and work assignment information of the digital employee according to the work information data; Scheduling the digital employee according to the position information and the work assignment information, and generating scheduling information; Performing data analysis on the position information, the work assignment information and the scheduling information, and generating an operation analysis report; Provide early warning and repair for abnormal data in the operation analysis report.

2. The data processing method according to claim 1, characterized in that: The step of establishing a unified data warehouse based on source data includes: Acquire the source data through a database system; The unified data warehouse is established according to the source data.

3. The data processing method according to claim 2, characterized in that: The establishing of a unified data warehouse according to the source data also includes: Before establishing the unified data warehouse based on the source data, the source data is cleaned, corrected and deduplicated.

4. The data processing method according to any one of claims 1 to 3, characterized in that: The operational analysis report includes utilization rate, idle rate and overload rate of the digital worker, as well as average processing time and error rate.

5. The data processing method according to any one of claims 1 to 3, characterized in that: The early warning and repair of abnormal data in the operation analysis report includes: Monitoring the operational analysis report; The abnormal data in the operation analysis report is sent to the control terminal via SMS or email.

6. The data processing method according to claim 5, characterized in that: The early warning and repair of abnormal data in the operation analysis report also includes: After the abnormal data in the operation analysis report is sent to the control terminal via SMS or email, a work order is dispatched to the digital employee according to the abnormal data to repair the abnormal data.

7. The data processing method according to any one of claims 1 to 3, characterized in that: Also includes: Before issuing an early warning and repairing abnormal data in the operation analysis report, the operation analysis report is displayed through a visualization device.

8. A data processing system, characterized in that: include: A basic data management module (210) is used to establish a unified data warehouse based on source data; wherein the source data includes one or a combination of the following: organizational data, user data, digital employee talent data and business data; A digital human resource management module (220) is used to determine the work information data of the digital employee based on the unified data warehouse, and determine the position information and work assignment information of the digital employee according to the work information data; schedule the digital employee according to the position information and the work assignment information, and generate scheduling information; An operation analysis management module (230), used to perform data analysis on the position information, the work assignment information and the scheduling information, and generate an operation analysis report; The operation and maintenance management module (240) is used to issue early warning and repair abnormal data in the operation analysis report.

9. An electronic device, characterized in that: include: A memory (310) and a processor (320), wherein the memory (310) stores a program or instruction that can be run on the processor (320), and when the processor (320) executes the program or the instruction, the steps of the data processing method according to any one of claims 1 to 7 are implemented.

10. A readable storage medium, characterized in that: The readable storage medium stores a program or an instruction, and when the program or the instruction is executed by a processor, the steps of the data processing method according to any one of claims 1 to 7 are implemented.

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