Big data-based editing and auditing management method and system
Through big data -based editing management methods and systems, the problem of low management efficiency of the existing review business processes was solved, and automated processing and management were realized, and the processing efficiency of the process was improved.
Patent Information
- Application Number
- CN202411244469.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-05
- Publication Date
- 2025-01-28
AI Technical Summary
The existing editorial business process management has problems with low management efficiency and a lack of a unified data management platform, resulting in manual execution and notification, which is not efficient.
Adopt the step -based editing management methods and systems, through the steps of data collection, information database construction, process queue sorting and distribution, real -time monitoring and notifications to achieve automated processing and management.
Improve the management efficiency of business processes. Through priority settings and real -time monitoring, the process is not processed in a timely manner, and early warning information is sent to the processing personnel to achieve automatic monitoring and management and improve the processing efficiency.
Smart Images
Figure CN119379186A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of data processing technology, and in particular to an editing and review management method and system based on big data. Background Art
[0002] The business process of an enterprise refers to a series of orderly and coordinated work steps and rules that an enterprise carries out to achieve its core value creation activities. These processes involve the interaction between various departments within the enterprise and external partners, including but not limited to product development, production, sales, service, logistics, finance and other aspects. The efficiency and effectiveness of the business process of an enterprise directly affect the competitiveness and profitability of the enterprise.
[0003] Some of these business processes are circulated on the computer intranet system. Relying on human labor to process them requires a lot of manpower, so RPA robots have emerged for automated processing. RPA robots are software-based automation tools that can simulate the operation behavior of human users and perform repetitive and regular tasks. RPA robots are usually used to automate business processes in enterprises, especially those involving large amounts of data input, processing, and transmission. In practice, it is found that the current editing and reviewing business process relies on manual execution and manual notification of the business flow of the next editing and reviewing link. There is a lack of a unified management platform for the data files generated during the editing and reviewing business process. It can be seen that the current editing and reviewing business process management has the problem of low management efficiency. Summary of the invention
[0004] The purpose of the present invention is to overcome the deficiencies of the above-mentioned prior art and to provide an editing and review management method and system based on big data.
[0005] A big data-based editing and review management method comprises the following steps:
[0006] Collect data from different departments to obtain process request data, and mark a start time and completion time for each process request data. Each process request data contains information about the processor, content information, and current status. Each process request data corresponds to a processing level.
[0007] Build an information database, which includes a list of processor information and a list of priority levels; a status database, in which the status information of each process request data after completion at different stages is stored in the status database to form a status list;
[0008] Obtain the process request data that needs to be processed currently, identify the processing level, start time, completion time, and processor information of each process request data, sort each process request data according to the processing level to form a process queue, and assign each process request data to the processor in the order of the process queue;
[0009] After receiving the process request data, the processor processes it according to the content he is responsible for. After the processing is completed, the completion status needs to be uploaded. The status database receives the status information and updates it in the status list;
[0010] Set the process completion trigger time, which is N minutes earlier than the completion time of the process request data, where N is a natural number;
[0011] Check in real time whether the completion time of each process request data has been reached. If reached, check the status of the process request data from the status database to confirm whether it has been completed; if not reached, continue to update.
[0012] If completed process request data is detected, check whether the processor of each stage of the process request data is correct, and compare it with the processor information list in the information database. If correct, the processing is completed; if incorrect, return for verification.
[0013] If the process request data has not been completed after the trigger time is reached, a notification message will be sent to remind the processor.
[0014] If the process request data is not processed after the completion time is reached, the process request data will be assigned to the designated person in charge, who will process or assign it.
[0015] The notification information includes call notification, short message notification, email notification and in-application notification.
[0016] Check in real time whether all process request data in the current process queue have been processed. If so, re-acquire new process request data; if not, continue monitoring.
[0017] A business process management system based on data processing, comprising:
[0018] An information acquisition unit, used for acquiring process request data and information of the process request data;
[0019] A detection unit, used to detect whether the process request data is completed;
[0020] A storage unit, used for storing information of the process request data in a database;
[0021] An information sending unit, used to send reminder information to the processor and the main person in charge;
[0022] The status reading unit is used to read the current status of the process request data.
[0023] Compared with the prior art, the present invention has the following beneficial technical effects:
[0024] By setting priorities for business processes, they can be processed in sequence according to priority and monitored in real time to prevent business processes from not being completed in a timely manner. Early warning information can be sent to processing personnel to achieve automatic monitoring and management, thereby improving processing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0025] Figure 1 Schematic diagram of the principle of the system of the present invention. DETAILED DESCRIPTION
[0026] In order to further understand the features, technical means, specific objectives and functions of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.
[0027] A big data-based editing and review management method comprises the following steps:
[0028] Collect data from different departments to obtain process request data, and mark a start time and completion time for each process request data. Each process request data contains information about the processor, content information, and current status. Each process request data corresponds to a processing level.
[0029] Build an information database, which includes a list of processor information and a list of priority levels; a status database, in which the status information of each process request data after completion at different stages is stored in the status database to form a status list;
[0030] Obtain the process request data that needs to be processed currently, identify the processing level, start time, completion time, and processor information of each process request data, sort each process request data according to the processing level to form a process queue, and assign each process request data to the processor in the order of the process queue;
[0031] After receiving the process request data, the processor processes it according to the content he is responsible for. After the processing is completed, the completion status needs to be uploaded. The status database receives the status information and updates it in the status list;
[0032] Set the process completion trigger time, which is N minutes earlier than the completion time of the process request data. N is a natural number, such as 5 minutes and 7 minutes. The timing starts from the time the process request data is dispatched. If the estimated completion time of a process request data is 2 hours and the trigger time N is 5 minutes, then it will check whether it has been completed at 1 hour and 55 minutes.
[0033] Check in real time whether the completion time of each process request data has been reached. If reached, check the status of the process request data from the status database to confirm whether it has been completed; if not reached, continue to update.
[0034] If a completed process request data is detected, check whether the processor of each stage of the process request data is correct, and compare it with the processor information list in the information database. If it is correct, the processing is completed; if it is incorrect, return for verification. In order to avoid the process request data being mistakenly assigned to other people, it can be corrected in time through detection.
[0035] If the process request data is not completed after the trigger time is reached, a notification message is sent to remind the processor. The notification message includes call notification, short message notification, email notification and in-application notification.
[0036] If the process request data is not processed after the completion time is reached, the process request data will be assigned to the designated person in charge, who will process or assign it.
[0037] Check in real time whether all process request data in the current process queue have been processed. If so, re-acquire new process request data; if not, continue monitoring.
[0038] Process according to a process queue. For example, if a process queue contains 5 process request data, after these 5 processes are completed, other process request data are obtained again and a new process queue is generated to avoid mixing of previous and later business processes.
[0039] A business process management system based on data processing, comprising:
[0040] A control unit for issuing and receiving instructions;
[0041] An information acquisition unit, used for acquiring process request data and information of the process request data;
[0042] A detection unit, used to detect whether the process request data is completed;
[0043] A storage unit, used for storing information of the process request data in a database;
[0044] An information sending unit, used to send reminder information to the processor and the main person in charge;
[0045] The status reading unit is used to read the current status of the process request data.
[0046] It should be noted that the above description is not a limitation of the present invention. Without departing from the creative concept of the present invention, any obvious replacement is within the protection scope of the present invention.
Claims
1. A big data-based editing and review management method, characterized in that: The following steps are involved: Collect data from different departments to obtain process request data, and mark a start time and completion time for each process request data. Each process request data contains information about the processor, content information, and current status. Each process request data corresponds to a processing level. Build an information database, which includes a list of processor information and a list of priority levels; a status database, in which the status information of each process request data after completion at different stages is stored in the status database to form a status list; Obtain the process request data that needs to be processed currently, identify the processing level, start time, completion time, and processor information of each process request data, sort each process request data according to the processing level to form a process queue, and assign each process request data to the processor in the order of the process queue; After receiving the process request data, the processor processes it according to the content he is responsible for. After the processing is completed, the completion status needs to be uploaded. The status database receives the status information and updates it in the status list; Set the process completion trigger time, which is N minutes earlier than the completion time of the process request data, where N is a natural number; Check in real time whether the completion time of each process request data has been reached. If reached, check the status of the process request data from the status database to confirm whether it has been completed; if not reached, continue to update.
2. The big data-based editing and review management method according to claim 1, characterized in that: If completed process request data is detected, check whether the processor of each stage of the process request data is correct, and compare it with the processor information list in the information database. If correct, the processing is completed; if incorrect, return for verification.
3. The editing and review management method based on big data according to claim 1 is characterized in that: If the process request data has not been completed after the trigger time is reached, a notification message will be sent to remind the processor.
4. The editing and review management method based on big data according to claim 1 is characterized in that: If the process request data is not processed after the completion time is reached, the process request data will be assigned to the designated person in charge, who will process or assign it.
5. The editing and review management method based on big data according to claim 3 is characterized in that: The notification information includes call notification, short message notification, email notification and in-application notification.
6. The editing and review management method based on big data according to claim 1 is characterized in that: Check in real time whether all process request data in the current process queue have been processed. If so, re-acquire new process request data; if not, continue monitoring.
7. An editorial management system based on big data, characterized in that: include: An information acquisition unit, used for acquiring process request data and information of the process request data; A detection unit, used to detect whether the process request data is completed; A storage unit, used for storing information of the process request data in a database; An information sending unit, used to send reminder information to the processor and the main person in charge; The status reading unit is used to read the current status of the process request data.