Supervision data processing method and device, equipment, storage medium and product

Abstract

The invention discloses a supervision data processing method and device, equipment, a storage medium and a product, and relates to the technical field of data processing, and the supervision data processing method comprises the steps: obtaining process basic data and instance operation data of a process business during the processing of the process business, and obtaining the process basic data and instance operation data of the process business based on a preset data specification; and cleaning abnormal data in the instance operation data, and processing the instance operation data and the process basic data based on service element configuration and preset processing rule configuration in a register book of a process service to obtain scene atomic data. The instance operation data is business data corresponding to the process basic data, and the process data and the business data can be associated through processing. And the service element configuration corresponds to the service scene, so that the scene atomic data can comprise the corresponding service scene through processing. Therefore, when supervision analysis is carried out based on the scene atomic data, the quality supervision analysis effect can be improved.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to methods, apparatus, equipment, storage media, and products for monitoring data processing. Background Technology

[0002] In the process-oriented work of bank counters, quality supervision and analysis are often required using process data. Currently, when supervising specific business scenarios, the business data and process data used for supervision are independent, making it impossible for quality supervision and analysis to segment scenarios based on process data and correlate them with business system data, resulting in poor quality supervision and analysis effectiveness. Summary of the Invention

[0003] The main objective of this application is to provide a method, apparatus, equipment, storage medium, and product for monitoring data processing, aiming to solve the technical problem of poor quality monitoring and analysis results.

[0004] To achieve the above objectives, this application proposes a supervised data processing method, the method comprising: When processing business processes, the process basic data and instance operation data of the business processes are obtained, wherein the instance operation data are business data that are changed and / or created during the execution of an instance of the business processes. Based on preset data specifications, abnormal data in the instance operation data is cleaned, wherein the abnormal data includes data fields and / or data formats that do not conform to the data specifications; Based on the business element configuration and preset processing rule configuration in the register of the process business, the instance operation data and the process basic data are processed to obtain scenario atomic data for supervision, wherein the business element configuration corresponds to the business scenario of the process business.

[0005] In one embodiment, the step of processing the instance operation data and the process basic data based on the business element configuration in the register of the process business and the preset processing rule configuration to obtain scenario atomic data for supervision includes: Based on the processing rule configuration, the corresponding process basic data and instance operation data in the process business are associated, and the associated data is converted into target associated data that conforms to the preset data standard; Based on the configuration of the business elements, the corresponding register business data is obtained, wherein the register business data is pre-uploaded data associated with the business scenario; The target-related data and the register business data are filtered to obtain the scene atomic data used for supervision.

[0006] In one embodiment, the instance operation data includes first instance operation data and second instance operation data, wherein the second instance operation data is obtained by inheriting from the first instance operation data or by querying from a database. The step of associating the corresponding process basic data and the instance operation data in the process business based on the processing rule configuration, and converting the associated data into target associated data that conforms to a preset data standard, includes: Based on the operation events of the process business, data operations are performed on the first instance operation data to obtain instantaneous instance data; Based on the processing rule configuration, the data content of the corresponding process basic data in the process business is associated with the data content of the instance transient data, and the associated data is converted into transient associated data that conforms to the preset data standard; Based on the processing rule configuration, the data operations of the transient associated data and the second instance operation data are associated, and the associated data is converted into target associated data that conforms to the preset data standard. The second instance operation data includes the operation event, and the operation event includes operation content and operation time.

[0007] In one embodiment, the step of performing data operations on the first instance operation data based on the operation events of the process business to obtain instantaneous instance data includes: Based on the operation event, determine the operation content and the operation time corresponding to the operation event; Based on the order of the event creation time, update start time, and update end time of the operation event, determine whether the prerequisite operation requirements of the operation event have been met; If satisfied, then based on the operation content and operation time, data operations are performed on the first instance operation data to obtain the instance instantaneous data. The operation content includes operation methods and operation fields, and the operation methods include data creation and data modification.

[0008] In one embodiment, the step of determining whether the prerequisite operation requirements of the operation event are met according to the order of the event creation time, update start time, and update end time of the operation event includes: At the event creation time, it is determined whether the instance exists. If it does not exist, the process waits until the instance is detected. At the start time of the update, it is determined whether the instance and the operation event exist. If they do not exist, the process waits until the instance and the operation event are detected. At the end time of the update, it is determined whether the instance and the start time of the update exist. If they do not exist, the process waits until the instance and the start time of the update are detected.

[0009] In one embodiment, the step of filtering the target associated data and the register business data to obtain the scene atomic data for supervision includes: Query the downstream configuration information of the downstream use scenarios of the target associated data and the register business data; Based on the downstream configuration information, the target associated data and the register business data are filtered and format converted to obtain the scene atomic data in a unified format.

[0010] Furthermore, to achieve the above objectives, this application also proposes a supervisory data processing apparatus, which includes: The data acquisition module is used to acquire the basic process data and instance operation data of the process business when processing the process business, wherein the instance operation data is the business data that is changed and / or created during the execution of an instance of the process business; The data cleaning module is used to clean abnormal data in the instance operation data based on preset data specifications, wherein the abnormal data includes data fields and / or data formats that do not conform to the data specifications; The data processing module is used to process the instance operation data and the process basic data based on the business element configuration in the register of the process business and the preset processing rule configuration to obtain scenario atomic data for supervision, wherein the business element configuration corresponds to the business scenario of the process business.

[0011] In addition, to achieve the above objectives, this application also proposes a supervisory data processing apparatus, the apparatus comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the supervisory data processing method as described above.

[0012] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and which, when executed by a processor, implements the steps of the supervised data processing method described above.

[0013] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the supervisory data processing method described above.

[0014] One or more technical solutions proposed in this application have at least the following technical effects: When processing process business, this application obtains the basic process data and instance operation data of the process business, cleans abnormal data in the instance operation data based on preset data specifications, and processes the instance operation data and the basic process data based on the business element configuration in the register of the process business and the preset processing rule configuration to obtain scene atomic data.

[0015] Currently, when monitoring segmented business scenarios, the business data and process data used for monitoring are independent, making it impossible for quality supervision analysis to segment scenarios and correlate business system data based on process data, resulting in poor quality supervision analysis effectiveness. This application addresses this issue by acquiring corresponding basic process data and instance operation data during process business processing, and processing the basic process data and cleaned instance operation data into scenario atomic data based on business element configuration. Since the instance operation data represents business data that is modified and / or created during the execution of an instance of the process business, and belongs to the same process as the basic process data, data processing can correlate the corresponding basic process data and instance operation data. Furthermore, because the business element configuration corresponds to the business scenario of the process business, data processing based on the business element configuration allows the obtained scenario atomic data to be correlated with the scenario of the process business. Therefore, supervision analysis based on scenario atomic data enables quality supervision analysis to segment scenarios and correlate business system data based on process data, thereby improving the effectiveness of quality supervision analysis. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating an embodiment of the data processing method for monitoring in this application. Figure 2 This is a schematic diagram of the first scenario provided for the first embodiment of the data processing method for supervision in this application; Figure 3 This is a schematic diagram of the second scenario provided in Embodiment 1 of the data processing method for supervision in this application; Figure 4 This is a schematic diagram of the third scenario provided in Embodiment 1 of the data processing method for supervision in this application; Figure 5 This is a flowchart illustrating Embodiment 2 of the data processing method for monitoring in this application; Figure 6 This is a schematic diagram of the first scenario provided for Embodiment 2 of the data processing method for supervision in this application; Figure 7 This is a schematic diagram of the second scenario provided in Embodiment 2 of the data processing method for supervision in this application; Figure 8 This is a schematic diagram of the third scenario provided in Embodiment 2 of the data processing method for supervision in this application; Figure 9 This is a schematic diagram of the fourth scenario provided in Embodiment 2 of the data processing method for supervision in this application; Figure 10 This is a schematic diagram of the module structure of the monitoring data processing device according to an embodiment of this application; Figure 11 This is a schematic diagram of the device structure of the hardware operating environment involved in the supervised data processing method in the embodiments of this application; Figure 12 This is a schematic diagram illustrating the data acquisition consent process involved in the data processing method described in this application.

[0019] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0021] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0022] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or a monitoring data processing device capable of performing the above functions. The following description uses a monitoring data processing device as an example to illustrate this embodiment and the subsequent embodiments.

[0023] In current bank counter service processes, quality supervision and analysis often require the use of process data. Currently, the business data available for quality supervision mainly consists of image attachments and receipts, representing a general supervisory task. However, when supervising specific business scenarios, the business data and process data used for supervision are independent. This prevents quality supervision analysis from segmenting scenarios based on process data and correlating them with business system data. This leads to limitations in monitoring scope, monitoring and auditing capabilities, and sampling accuracy, ultimately resulting in poor quality supervision and analysis effectiveness.

[0024] Furthermore, traditional data analysis typically involves downloading source table data from a data warehouse before conducting data analysis, which usually takes T+1 delivery and has a low timeliness.

[0025] Based on this, embodiments of this application provide a method for supervising data processing, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the data processing method for monitoring in this application.

[0026] In this embodiment, the supervisory data processing method includes steps S10 to S30: Step S10: When processing the process business, obtain the process basic data and instance operation data of the process business, wherein the instance operation data is the business data that is changed and / or created during the execution of an instance of the process business. It should be noted that process-based business operations refer to a type of business operation that needs to be executed according to a predetermined process in bank counters or other business systems. Basic process data refers to data generated during the implementation of the process-based business operation, such as customer identity information, account information, product type, business type, institution number, and process initiation time. Instance operation data refers to the business data created or modified by various business systems during the actual operation of the process instance.

[0027] It should also be noted that this embodiment implements the supervised data processing by constructing a process data analysis-based system. This system is primarily deployed at the application layer and includes three main services: data processing service, configuration management service, and data scenario adaptation service. The storage layer it relies on is primarily MySQL (My Structured Query Language). In this embodiment, data is acquired by capturing changed data from database tables through the data processing system and synchronizing the changed data into memory for subsequent processing. The structure of the process data analysis system described above in this embodiment can be referenced. Figure 2 , Figure 2 This includes different levels of the process data analysis system, as well as the components within each level.

[0028] It is understood that this embodiment obtains basic process data and instance operation data synchronously during the process business processing. Since the instance operation data is business data that is changed and / or created during the execution of the instance of the process business, this embodiment provides complete and comprehensive process business-related data for data processing through the above-mentioned synchronous acquisition operation.

[0029] Step S20: Based on preset data specifications, clean the abnormal data in the instance operation data, wherein the abnormal data includes data fields and / or data formats that do not conform to the data specifications; It should be noted that the preset data specifications refer to a set of standardized data rules predefined during the system design phase, used to unify the representation and structure of data. In this embodiment, the standardized rules include data format validation, non-empty validation, and field integrity validation. Abnormal data refers to data in the instance operation data that does not conform to the preset data specifications. In this embodiment, this specifically includes data with missing fields or other field anomalies, data with incorrect format, and data with empty values.

[0030] It is understandable that this embodiment uses a cleaning mechanism based on preset data specifications to standardize and preprocess instance operation data, directly eliminating abnormal data caused by system errors, human input mistakes, or interface compatibility issues. This avoids misjudgments or calculation errors caused by erroneous data entering subsequent analysis stages, significantly improving the accuracy, consistency, and usability of instance operation data. Furthermore, by simultaneously acquiring basic process data and instance operation data during process flow analysis and cleaning this data, the system can perform analysis based on data that meets both format and content requirements, improving the accuracy of subsequent data supervision and analysis.

[0031] Step S30: Based on the business element configuration and preset processing rule configuration in the register of the process business, process the instance operation data and the process basic data to obtain scenario atomic data for supervision, wherein the business element configuration corresponds to the business scenario of the process business.

[0032] It should be noted that the business element configurations in the register are pre-reported by the business scenario parties and are a collection of configuration information related to specific process business and its business scenario. Business elements are key fields or data items related to the scenario. Pre-defined processing rule configurations refer to data processing logic rules pre-set to achieve specific supervision objectives, including field concatenation rules, conditional judgment rules, and data aggregation rules. Scenario atomic data refers to the smallest granular, standardized data unit generated after processing, oriented towards a specific supervision scenario, and directly usable for analysis.

[0033] It should also be noted that the atomic scenario data processed in this embodiment is ultimately provided to downstream data users through three methods: data warehouse, API (Application Programming Interface), and MQ (Message Queue). Downstream data users can pull the corresponding data from the data warehouse, API, and MQ, and perform post-event supervision and analysis based on the pulled data.

[0034] It is understood that this embodiment, by introducing business element configurations from the register and preset processing rule configurations, transforms general process basic data and instance operation data into scenario atomic data with business scenario information according to the semantic requirements of different supervision scenarios. Since the scenario atomic data is processed based on the process basic data and the corresponding instance operation data, it allows the process basic data to be associated with the instance operation data. Furthermore, because this embodiment also processes data based on the business element configurations in the register, the scenario atomic data obtained in this embodiment also includes scenario information provided by the business scenario provider.

[0035] Therefore, this embodiment can efficiently complete the analysis and processing of post-supervision data by mixing process operation data with business data from various business systems. This not only improves the standardization and uniformity of the data, but also lowers the threshold for using the data.

[0036] Furthermore, this embodiment can provide data in near real-time by collecting process operation data and data from various business systems. Compared with the traditional method of downloading source table data from a data warehouse and then performing data analysis, the method of this embodiment is more timely.

[0037] In one feasible implementation, the specific implementation of processing the instance operation data and the process basic data based on the business element configuration in the register of the process business and the preset processing rule configuration to obtain the scene atomic data for supervision can also be: Based on the processing rule configuration, the corresponding process basic data and instance operation data in the process business are associated, and the associated data is converted into target associated data that conforms to the preset data standard. Based on the business element configuration, the corresponding register business data is obtained, wherein the register business data is pre-uploaded data associated with the business scenario. The target associated data and the register business data are filtered to obtain the scenario atomic data for supervision.

[0038] It should be noted that the preset data standard refers to the final data format that the system needs to conform to, used to unify the data representation and structure. In this embodiment, the preset data standard is the PETSC standard (Product, Event, Task, Step, Container). Target-related data refers to intermediate data with a PETSC data structure generated after the process basic data and instance operation data are associated and standardized according to processing rules. It includes business content and operation processes and can be used for subsequent processing of atomic data in the scenario. Register business data is data related to the business scenario generated based on the configuration information reported by the business scenario party. In this embodiment, the register business data is used to supplement the target-related data.

[0039] It is understood that this embodiment completes the synchronous collection of basic process data and instance operation data through the above operations, and ensures the integrity and consistency of the key fields on which the association depends by cleaning the instance operation data. Based on this, this specific implementation first deeply integrates the two types of data according to processing rules and standardizes them into target associated data of the PETSC standard, realizing the association between basic process data and instance operation data. Furthermore, by processing the data into PETSC standard data, data analysis can be performed at different levels during subsequent data supervision and analysis, thereby improving the effectiveness of data supervision and analysis. The scenario diagram of data fusion processing in this embodiment can be referred to... Figure 3 , Figure 3 This embodiment includes the functions of the Kaiyang system (a process processing system), various business systems, managers, and post-construction quality inspection. The data fusion and processing flow described above in this embodiment can be referenced... Figure 4 , Figure 4 This includes all steps in this embodiment, from data acquisition to post-event monitoring and analysis by downstream data users using the retrieved data.

[0040] After standardizing the data into target-related data according to the PETSC standard, this embodiment uses register business data as scenario data to supplement the target-related data, and retains the data related to the target scenario in the target-related data and instance operation data through filtering operations. Thus, in addition to associating process data and business data, it also associates the final data with the specific business scenario.

[0041] In one feasible implementation, the specific implementation of filtering the target associated data and the register business data to obtain the scene atomic data for supervision can also be: Query the downstream configuration information of the downstream use scenarios of the target associated data and the register business data. Based on the downstream configuration information, perform data field filtering and format conversion on the target associated data and the register business data to obtain the scenario atomic data in a unified format.

[0042] It should be noted that downstream use cases refer to the specific business or technical applications that the generated atomic data will be used for. Different downstream use cases have different requirements for data fields and formats. Downstream configuration information refers to the data output specifications pre-configured for each downstream use case, including the fields required by the downstream use case.

[0043] It is understandable that different downstream use scenarios require different ranges of fields for input data. Therefore, this embodiment queries downstream configuration information, performs field filtering and format conversion, so that the final atomic data of the scenario meets the needs of the downstream use scenario. Thus, when performing data quality supervision and analysis, it can be combined with specific business scenarios for analysis, thereby improving the effectiveness of quality supervision and analysis.

[0044] In summary, this embodiment obtains the basic process data and instance operation data of the process business when processing the process business. Based on the preset data specifications, abnormal data in the instance operation data is cleaned. Based on the business element configuration in the register of the process business and the preset processing rule configuration, the instance operation data and the basic process data are processed to obtain scene atomic data.

[0045] Currently, when monitoring segmented business scenarios, the business data and process data used for monitoring are independent, making it impossible for quality supervision analysis to segment scenarios and correlate business system data based on process data, resulting in poor quality supervision analysis effectiveness. This application addresses this issue by acquiring corresponding basic process data and instance operation data during process business processing, and processing the basic process data and cleaned instance operation data into scenario atomic data based on business element configuration. Since the instance operation data represents business data that is modified and / or created during the execution of an instance of the process business, and belongs to the same process as the basic process data, data processing can correlate the corresponding basic process data and instance operation data. Furthermore, because the business element configuration corresponds to the business scenario of the process business, data processing based on the business element configuration allows the obtained scenario atomic data to be correlated with the scenario of the process business. Therefore, supervision analysis based on scenario atomic data enables quality supervision analysis to segment scenarios and correlate business system data based on process data, thereby improving the effectiveness of quality supervision analysis.

[0046] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 5 The instance operation data includes first instance operation data and second instance operation data. The second instance operation data is obtained by inheriting from the first instance operation data or by querying from the database. The step of associating the corresponding process basic data and instance operation data in the process business based on the processing rule configuration, and converting the associated data into target associated data that conforms to the preset data standard, further includes steps S100~S300: Step S100: Based on the operation events of the process business, perform data operations on the first instance operation data to obtain instance instantaneous data; It should be noted that an operation event refers to a specific behavior in a process instance that triggers data changes or data creation, which will cause data changes. Instance transient data refers to the data of the process instance at the time the operation event is completed after the operation event occurs.

[0047] It is understandable that in business processes, instance operation data is generated in stages. That is, at different stages of the business process, different operation events will occur to modify and / or create instance operation data. Therefore, this embodiment performs operations on instance operation data based on operation events, thereby accurately obtaining the instance data corresponding to the current business process and achieving a precise correspondence between the basic process data and the instance operation data.

[0048] In one feasible implementation, the specific implementation of performing data operations on the first instance operation data based on the operation events of the process business to obtain the instance instantaneous data can also be: Based on the operation event, the operation content and operation time corresponding to the operation event are determined. According to the order of the event creation time, update start time, and update end time of the operation event, it is determined whether the prerequisite operation requirements of the operation event are met. If they are met, data operations are performed on the first instance operation data based on the operation content and operation time to obtain the instance instantaneous data. The operation content includes operation method and operation field, and the operation method includes data creation and data modification.

[0049] It should be noted that the event creation time, start time, and end time are three key timestamps in the lifecycle of an operation event. The event creation time is the time when the operation event is generated, the event start time is the starting moment when the operation is actually executed, and the event end time is the moment when the operation is completed.

[0050] It is understandable that in high-concurrency or asynchronous processing systems, the order in which data arrives may be disordered. If the preconditions for each time point are not checked, logical errors such as state confusion and time reversal may occur, affecting the accuracy of supervisory analysis. Therefore, this embodiment determines whether the preconditions for the operation event are met, thereby achieving temporal consistency control of process state changes and generating instantaneous instance data that conforms to the actual execution logic.

[0051] In one feasible implementation, the specific implementation of determining whether the prerequisite operation requirements of the operation event are met according to the order of the event creation time, update start time, and update end time of the operation event can also be: At the event creation time, it is determined whether the instance exists. If it does not exist, the process waits until the instance is detected. At the update start time, it is determined whether the instance and the operation event exist. If they do not exist, the process waits until the instance and the operation event are detected. At the update end time, it is determined whether the instance and the update start time exist. If they do not exist, the process waits until the instance and the update start time are detected.

[0052] It is understandable that in high-concurrency or asynchronous business systems, data generation at different stages may be delayed or out of order. Without synchronization control, this can lead to missing states or logical breaks, making it impossible to accurately reconstruct the process execution. Therefore, this embodiment performs pre-condition checks at three crucial event points of the operation event: the event creation time, the update start time, and the update end time. This ensures that the state update only proceeds after all pre-conditions are met, thereby generating instance transient data that conforms to the actual business execution order. This improves the accuracy of subsequent data supervision and analysis. The process of processing operation data into instance transient data in this embodiment can be referred to... Figure 6 , Figure 6 This includes the various processes in this embodiment, such as acquiring operation events, judging prerequisites, and executing operation events.

[0053] Step S200: Based on the processing rule configuration, associate the corresponding process basic data in the process business with the data content of the instance instantaneous data, and convert the associated data into instantaneous associated data that conforms to the preset data standard; It should be noted that transient correlated data refers to data conforming to the PETSC standard generated after successfully associating and standardizing process base data with instance transient data, i.e., PETSC transient data. The PETSC data includes process base data at different levels and instance transient data corresponding to the process base data.

[0054] Understandably, current methods often suffer from fragmented process data and operational data across different systems, lacking effective correlation and hindering effective analysis of processes and their corresponding results. This embodiment addresses this by linking instantaneous instance data of operational events with basic process data, generating instance instantaneous data that integrates process business and operational results. This allows for direct correlation between process business and corresponding operational results during data analysis, improving data analyzability in quality supervision analysis. The processing order of PETSC instantaneous data can be referenced... Figure 7 , Figure 7 This includes the processing sequence from instance operation data to scenario analysis. The overall data processing flow can be referenced... Figure 8 , Figure 8 This includes a detailed processing flow from instance operation data to scenario analysis data.

[0055] The final transient correlation data (PETSC transient data) generated in this embodiment is shown in the table below:

[0056] Step S300: Based on the processing rule configuration, associate the data operations of the transient associated data and the second instance operation data, and convert the associated data into target associated data that conforms to the preset data standard. The second instance operation data includes the operation event, and the operation event includes operation content and operation time.

[0057] It should be noted that the operation data in the second instance corresponds to the same basic process data as the operation data in the first embodiment. The operation data in the second embodiment can be obtained by inheriting the operation data in the first embodiment, or it can be obtained by querying the database.

[0058] It is understandable that when the operation data in the first embodiment is associated with the basic process data, the generated PETSC instantaneous data integrates the process business and the corresponding operation results. The process business can perform various operations on the data, such as updating and creating, and can be performed at multiple event points during the execution of the process business. Therefore, this embodiment obtains the operation data of the second embodiment corresponding to the process business through inheritance or querying. Since the operation data of the second embodiment contains both operation content and operation time, a secondary association and fusion process is performed between the operation data of the second embodiment and the obtained PETSC data. In addition to merging the operation results of the process business with the process business itself, the operation content of the process business can also be associated and merged with the process business, thus giving the final target associated data (PETSC data) richer association information, thereby enhancing the effectiveness of subsequent data quality supervision and analysis. The overall system data framework of this embodiment can be referred to... Figure 9 , Figure 9 This includes the status of data during data collection and data usage.

[0059] In summary, this embodiment performs data operations on the first instance operation data based on the operation events of the process business to obtain instance instantaneous data. Based on the processing rule configuration, the corresponding process basic data in the process business is associated with the data content of the instance instantaneous data, and the associated data is converted into instantaneous associated data that conforms to a preset data standard. Based on the processing rule configuration, the instantaneous associated data is associated with the data operations of the second instance operation data, and the associated data is converted into target associated data that conforms to a preset data standard. The second instance operation data includes the operation events, and the operation events include operation content and operation time.

[0060] In high-concurrency or asynchronous business systems, data generation at different stages may be delayed or out of order, making it impossible to accurately reconstruct the process execution. This embodiment performs pre-condition checks at three key event points of the operation event, ensuring that state updates only proceed after all pre-conditions are met, thereby generating instance transient data that conforms to the actual business execution order. By associating and fusing the generated instance transient data with the basic process data, the generated instance transient data (PETSC transient data) can integrate process business and process business operation results. A second instance operation data obtained through inheritance or querying is then further associated and fused with the instance transient data, resulting in target associated data (PETSC data) that also associates process business with business operation content, ultimately yielding target associated data with rich association information. Subsequent processing of scene atomic data using this target associated data allows the processed scene atomic data to possess rich association information in addition to scene information, thereby improving the effectiveness of data supervision and analysis through scene atomic data.

[0061] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the data processing method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0062] This application also provides a supervisory data processing apparatus; please refer to [reference needed]. Figure 10 The supervisory data processing device includes: The data acquisition module 10 is used to acquire the basic process data and instance operation data of the process business when processing the process business, wherein the instance operation data is the business data that is changed and / or created during the execution of an instance of the process business. The data cleaning module 20 is used to clean abnormal data in the instance operation data based on preset data specifications, wherein the abnormal data includes data fields and / or data formats that do not conform to the data specifications; The data processing module 30 is used to process the instance operation data and the process basic data based on the business element configuration in the register of the process business and the preset processing rule configuration to obtain scenario atomic data for supervision, wherein the business element configuration corresponds to the business scenario of the process business.

[0063] In one embodiment, the data processing module includes: The data association submodule is used to associate the corresponding process basic data and instance operation data in the process business based on the processing rule configuration, and to convert the associated data into target associated data that conforms to the preset data standard. The data acquisition submodule is used to acquire corresponding register business data based on the business element configuration, wherein the register business data is pre-uploaded data associated with the business scenario; The data filtering submodule is used to filter the target associated data and the register business data to obtain the scene atomic data for supervision.

[0064] In one embodiment, the data association submodule includes: The data processing unit is used to perform data operations on the first instance operation data based on the operation events of the process business to obtain instantaneous instance data; The first data association unit is configured to associate the data content of the corresponding process basic data and the instance transient data in the process business with the data content of the process business based on the processing rule configuration, and convert the associated data into transient associated data that conforms to the preset data standard. The second data association unit is configured to associate the data operations of the instantaneous associated data and the second instance operation data based on the processing rule configuration, and to convert the associated data into target associated data that conforms to the preset data standard. The second instance operation data includes the operation event, and the operation event includes operation content and operation time.

[0065] In one embodiment, the data processing unit includes: An operation determination unit is used to determine the operation content and the operation time corresponding to the operation event based on the operation event; The pre-judgment unit is used to determine whether the pre-operation requirements of the operation event are met according to the order of the event creation time, update start time, and update end time of the operation event. A data operation unit is configured to perform data operations on the first instance operation data based on the operation content and operation time, if the conditions are met, to obtain the instantaneous data of the instance. The operation content includes operation methods and operation fields, and the operation methods include data creation and data modification.

[0066] In one embodiment, the pre-judgment unit includes: A time point determination subunit is created to determine whether the instance exists at the event creation time. If it does not exist, the process waits until the instance is detected. The start time point determination subunit is used to determine whether the instance and the operation event exist at the update start time point. If they do not exist, the unit waits until the instance and the operation event are detected. The end time point determination subunit is used to determine whether the instance and the update start time point exist at the update end time point. If they do not exist, the unit waits until the instance and the update start time point are detected.

[0067] In one embodiment, the step of filtering the target associated data and the register business data to obtain the scene atomic data for supervision includes: Query the downstream configuration information of the downstream use scenarios of the target associated data and the register business data; Based on the downstream configuration information, the target associated data and the register business data are filtered and format converted to obtain the scene atomic data in a unified format.

[0068] The supervisory data processing apparatus provided in this application, employing the supervisory data processing method in the above embodiments, can solve the technical problem of poor quality supervision and analysis results. Compared with the prior art, the beneficial effects of the supervisory data processing apparatus provided in this application are the same as those of the supervisory data processing method provided in the above embodiments, and other technical features in the supervisory data processing apparatus are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0069] This application provides a supervisory data processing apparatus, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the supervisory data processing method in Embodiment 1 above.

[0070] The following is for reference. Figure 11 The diagram illustrates a structural schematic of a supervisory data processing device suitable for implementing embodiments of this application. The supervisory data processing device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, tablets, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 11 The supervisory data processing device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0071] like Figure 11As shown, the supervisory data processing device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.) that can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the supervisory data processing device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. The communication device 1009 allows the supervisory data processing equipment to communicate wirelessly or wiredly with other devices to exchange data. Although the figures show supervisory data processing equipment with various systems, it should be understood that it is not required to implement or possess all of the systems shown. More or fewer systems may be implemented alternatively.

[0072] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0073] The supervisory data processing equipment provided in this application, employing the supervisory data processing method in the above embodiments, can solve the technical problem of poor quality supervision and analysis results. Compared with the prior art, the beneficial effects of the supervisory data processing equipment provided in this application are the same as those of the supervisory data processing method provided in the above embodiments, and other technical features of the supervisory data processing equipment are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0074] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0075] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0076] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the supervised data processing method in the above embodiments.

[0077] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0078] The aforementioned computer-readable storage medium may be included in the supervisory data processing device; or it may exist independently and not assembled into the supervisory data processing device.

[0079] The aforementioned computer-readable storage medium carries one or more programs, which, when executed by the supervised data processing device, cause the supervised data processing device to perform the aforementioned supervised data processing method.

[0080] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0081] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0082] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0083] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described supervisory data processing method, thereby solving the technical problem of poor quality supervision and analysis results. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the supervisory data processing method provided in the above embodiments, and will not be repeated here.

[0084] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the supervisory data processing method described above.

[0085] The computer program product provided in this application can solve the technical problem of poor quality supervision and analysis results. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the supervision data processing method provided in the above embodiments, and will not be repeated here.

[0086] All user-related data involved in this application was obtained with the user's permission or consent. (See reference...) Figure 12 In other words, when this application is applied to specific products or technologies, user permission is required to acquire and process the relevant data, and the processing of the relevant data must comply with the relevant laws, regulations, and regulatory standards of the relevant countries and regions.

[0087] The above description is only a part of the embodiments of this application and does not limit the scope of protection of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for supervising data processing, characterized in that, The method includes: When processing business processes, the process basic data and instance operation data of the business processes are obtained, wherein the instance operation data are business data that are changed and / or created during the execution of an instance of the business processes. Based on preset data specifications, abnormal data in the instance operation data is cleaned, wherein the abnormal data includes data fields and / or data formats that do not conform to the data specifications; Based on the business element configuration and preset processing rule configuration in the register of the process business, the instance operation data and the process basic data are processed to obtain scenario atomic data for supervision, wherein the business element configuration corresponds to the business scenario of the process business.

2. The method as described in claim 1, characterized in that, The step of processing the instance operation data and the process basic data to obtain scenario atomic data for supervision, based on the business element configuration in the register of the process business and the preset processing rule configuration, includes: Based on the processing rule configuration, the corresponding process basic data and instance operation data in the process business are associated, and the associated data is converted into target associated data that conforms to the preset data standard; Based on the configuration of the business elements, the corresponding register business data is obtained, wherein the register business data is pre-uploaded data associated with the business scenario; The target-related data and the register business data are filtered to obtain the scene atomic data used for supervision.

3. The method as described in claim 2, characterized in that, The instance operation data includes first instance operation data and second instance operation data. The second instance operation data is obtained by inheriting from the first instance operation data or by querying from the database. The step of associating the corresponding process basic data and the instance operation data in the process business based on the processing rule configuration, and converting the associated data into target associated data that conforms to the preset data standard, includes: Based on the operation events of the process business, data operations are performed on the first instance operation data to obtain instantaneous instance data; Based on the processing rule configuration, the data content of the corresponding process basic data in the process business is associated with the data content of the instance transient data, and the associated data is converted into transient associated data that conforms to the preset data standard; Based on the processing rule configuration, the data operations of the transient associated data and the second instance operation data are associated, and the associated data is converted into target associated data that conforms to the preset data standard. The second instance operation data includes the operation event, and the operation event includes operation content and operation time.

4. The method as described in claim 3, characterized in that, The step of performing data operations on the first instance operation data based on the operation events of the process business to obtain the instance instantaneous data includes: Based on the operation event, determine the operation content and the operation time corresponding to the operation event; Based on the order of the event creation time, update start time, and update end time of the operation event, determine whether the prerequisite operation requirements of the operation event have been met; If satisfied, then based on the operation content and operation time, data operations are performed on the first instance operation data to obtain the instance instantaneous data. The operation content includes operation methods and operation fields, and the operation methods include data creation and data modification.

5. The method as described in claim 4, characterized in that, The step of determining whether the prerequisite operation requirements of the operation event are met according to the order of the event creation time, update start time, and update end time includes: At the event creation time, it is determined whether the instance exists. If it does not exist, the process waits until the instance is detected. At the start time of the update, it is determined whether the instance and the operation event exist. If they do not exist, the process waits until the instance and the operation event are detected. At the end time of the update, it is determined whether the instance and the start time of the update exist. If they do not exist, the process waits until the instance and the start time of the update are detected.

6. The method as described in claim 2, characterized in that, The step of filtering the target associated data and the register business data to obtain the scene atomic data for supervision includes: Query the downstream configuration information of the downstream use scenarios of the target associated data and the register business data; Based on the downstream configuration information, the target associated data and the register business data are filtered and format converted to obtain the scene atomic data in a unified format.

7. A supervisory data processing device, characterized in that, The device includes: The data acquisition module is used to acquire the basic process data and instance operation data of the process business when processing the process business, wherein the instance operation data is the business data that is changed and / or created during the execution of an instance of the process business; The data cleaning module is used to clean abnormal data in the instance operation data based on preset data specifications, wherein the abnormal data includes data fields and / or data formats that do not conform to the data specifications; The data processing module is used to process the instance operation data and the process basic data based on the business element configuration in the register of the process business and the preset processing rule configuration to obtain scenario atomic data for supervision, wherein the business element configuration corresponds to the business scenario of the process business.

8. A supervisory data processing device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the supervisory data processing method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the supervisory data processing method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the supervisory data processing method as described in any one of claims 1 to 6.

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