Influence degree determination method and device, electronic equipment, storage medium and product

Abstract

The embodiment of the invention discloses an influence degree determination method and device, electronic equipment, a storage medium and a product. The method comprises the steps of obtaining to-be-analyzed data corresponding to at least one to-be-analyzed task executed by a business system in a historical time period; wherein the to-be-analyzed data is service data generated when the to-be-analyzed task is executed by each associated service subsystem used for executing the to-be-analyzed task; for each associated service subsystem, based on the to-be-analyzed data corresponding to the associated service subsystem, determining an execution result label generated when the associated service subsystem executes the to-be-analyzed task matched with the associated service subsystem; wherein the execution result label comprises an execution success label and an execution failure label; and based on the at least one execution result label corresponding to each associated service subsystem, determining the influence degree of the associated service subsystem on the execution result of the system task. According to the technical scheme provided by the embodiment of the invention, the accuracy and effectiveness of the determined influence degree are improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of data processing technology, and in particular, to a method, device, electronic device, storage medium and product for determining the degree of influence. Background Art

[0002] Each business subsystem in the financial industry is built relatively independently, but there will be interactions between different business subsystems due to business connections. Processing a complete task requires interaction between multiple interrelated business subsystems.

[0003] In the prior art, in order to better understand the execution of tasks by each business subsystem, the business data generated by each business subsystem when executing the task is usually obtained, and the obtained business data is directly displayed to the staff for analysis, so that the staff can determine the impact of each business subsystem on the task execution result. However, in the process of implementing the present invention, it is found that the prior art has at least the following technical problems: due to the complex association relationship between the business systems involved in the task, it is difficult for the staff to intuitively determine the impact of each business subsystem on the task execution result from the business data, resulting in the inability to accurately determine the impact of different business subsystems on the task; and the manual determination of the impact results in a waste of resources. Summary of the invention

[0004] Embodiments of the present invention provide a method, device, electronic device, storage medium and product for determining the degree of influence, so as to achieve the purpose of improving the accuracy and effectiveness of the determined degree of influence.

[0005] According to one aspect of the present invention, there is provided a method for determining an impact degree, comprising:

[0006] Acquire data to be analyzed corresponding to at least one task to be analyzed executed by the business system in a historical time period; wherein the data to be analyzed is business data generated by each associated business subsystem for executing the task to be analyzed when executing the task to be analyzed;

[0007] For each of the associated business subsystems, based on the to-be-analyzed data corresponding to the associated business subsystem, determining an execution result tag generated when the associated business subsystem executes a to-be-analyzed task matching the associated business subsystem; wherein the execution result tag includes an execution success tag and an execution failure tag;

[0008] Based on at least one of the execution result tags corresponding to each of the associated business subsystems, the degree of influence of the associated business subsystem on the execution result of the system task is determined.

[0009] According to another aspect of the present invention, there is provided an impact degree determination device, comprising:

[0010] The data acquisition module for analysis is used to acquire the data for analysis corresponding to at least one task for analysis executed by the business system in a historical time period; wherein the data for analysis is the business data generated by each associated business subsystem for executing the task for analysis when executing the task for analysis;

[0011] a label determination module, for each of the associated business subsystems, based on the to-be-analyzed data corresponding to the associated business subsystem, determining an execution result label generated when the associated business subsystem executes a to-be-analyzed task matching the associated business subsystem; wherein the execution result label includes an execution success label and an execution failure label;

[0012] The impact degree determination module is used to determine the impact degree of the associated business subsystem on the execution result of the system task based on at least one of the execution result tags corresponding to each of the associated business subsystems.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining the degree of influence described in any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for determining the degree of influence described in any embodiment of the present invention when executed.

[0018] According to another aspect of the present invention, a computer program product is provided, including a computer program, wherein when the computer program is executed by a processor, the method for determining the degree of influence described in any embodiment of the present invention is implemented.

[0019] The technical solution of the embodiment of the present invention obtains data to be analyzed corresponding to at least one task to be analyzed executed by a business system in a historical time period; wherein the data to be analyzed is business data generated by each associated business subsystem used to execute the task to be analyzed when executing the task to be analyzed; and, for each associated business subsystem, based on the data to be analyzed corresponding to the associated business subsystem, determines the execution result label generated when the associated business subsystem executes the task to be analyzed matching the associated business subsystem; wherein the execution result label includes an execution success label and an execution failure label; finally, based on at least one execution result label corresponding to each associated business subsystem, determines the degree of influence of the associated business subsystem on the execution result of the system task, so that in the process of determining the degree of influence, there is no need for staff participation, thereby avoiding waste of human resources; and, by determining the degree of influence through the execution result label, the accuracy and effectiveness of the determined degree of influence are improved.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 is a flow chart of a method for determining the degree of influence provided according to an embodiment of the present invention;

[0023] Figure 2 is a structural schematic diagram of an impact degree determination device provided according to an embodiment of the present invention;

[0024] Figure 3 It is a structural schematic diagram of an electronic device for implementing the method for determining the degree of influence of an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "etc." and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0027] It should be noted that the collection, collection, updating, analysis, processing, use, transmission, storage and other aspects of user personal information involved in the technical solution of this disclosure are in compliance with the provisions of relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. Necessary measures are taken for user personal information to prevent illegal access to user personal information data and maintain the security of user personal information and network security.

[0028] Figure 1 This is a flow chart of a method for determining the degree of influence provided according to an embodiment of the present invention. This embodiment can be applied to the case of determining the degree of influence of a business subsystem on the execution result of a system task. The method can be executed by an influence determination device, which can be implemented in the form of hardware and / or software.

[0029] like Figure 1 As shown, the method of this embodiment may specifically include:

[0030] S110: Obtain data to be analyzed corresponding to at least one task to be analyzed executed by the business system in a historical time period.

[0031] It should be noted that a business system may include multiple business subsystems. System tasks in a business system may be divided into multiple subtasks, and different subtasks are performed by different business subsystems. Exemplarily, a business system may be a system for processing banking business. System tasks may include a balance inquiry task, and the balance inquiry task may be divided into a login subtask, an account verification subtask, an information identification subtask, and an information inquiry subtask. Different subtasks may be operated by corresponding business subsystems.

[0032] In this embodiment, in order to determine the degree of influence of the business subsystem on the execution result of the system task, the data to be analyzed of at least one task to be analyzed can be obtained. Exemplarily, the tasks to be analyzed can be all system tasks generated on the business system in the historical time period; or, the tasks to be analyzed can be target type tasks generated on the business system in the historical time period. For example, the target type tasks can include at least one of the balance query task, information authentication task, or information change task. The historical time period can be a time period with a preset time length from the current time, for example, the preset time length can be 1 day, a week, a month, or a year.

[0033] Since the task to be analyzed can be divided into multiple subtasks, each subtask can be executed by a different business subsystem, the business subsystem that executes the same task to be analyzed can be regarded as an associated business subsystem, and the data to be analyzed is the business data generated by each associated business subsystem used to execute the task to be analyzed when executing the task to be analyzed.

[0034] S120 . For each associated business subsystem, based on the to-be-analyzed data corresponding to the associated business subsystem, determine an execution result label generated when the associated business subsystem executes a to-be-analyzed task matching the associated business subsystem.

[0035] In order to facilitate the execution result label in the acquired data to be analyzed, when determining that the associated business subsystem executes the task to be analyzed matching the associated business subsystem based on the data to be analyzed corresponding to the associated business subsystem, before the execution result label is generated, it also includes: performing data preprocessing operations on each group of data to be analyzed, and updating the data to be analyzed with the data obtained after data preprocessing; for each data to be analyzed, extracting the dimension data of each dimension of the data to be analyzed; splicing each dimension data into a preset large wide table to generate a target large wide table; wherein the target large wide table contains dimension fields and associated fields, the dimension fields are fields corresponding to the dimension data, and the dimension data includes execution result labels; loading the fact data in the data to be analyzed into the target large wide table, and updating the target large wide table based on the large wide table after the fact data is loaded.

[0036] In this embodiment, the data preprocessing operation includes a data conversion operation and / or a data cleaning operation. Through the data conversion operation, the dimensions and formats of the data to be analyzed can be unified, so as to facilitate the extraction of the execution result label in the data to be analyzed. Optionally, the data preprocessing operation is performed on each group of data to be analyzed, including: for each group of data to be analyzed, format conversion is performed on the data to be analyzed according to a preset format, and the data to be analyzed is updated based on the data after the format conversion; and / or, for each group of data to be analyzed, the data to be analyzed is converted into data of a preset data type, and the data obtained after the conversion is updated to the data to be analyzed.

[0037] The preset formats include pre-set formats for different types of data, for example, the types include date type, user identification type, serial number type, etc.

[0038] In this embodiment, different types of data in the data to be analyzed can be determined, and for each type of data, the data is format converted according to a preset format that matches the data of that type. For example, date type data is extracted from the data to be analyzed, and the preset format corresponding to the date type is "××××-××-××", then the date type data in each group of data to be analyzed is converted to the "××××-××-××" format. Based on the data obtained after the format conversion, the data to be analyzed is updated.

[0039] Furthermore, different types of data in the data to be analyzed have different data types. In order to facilitate data processing, the data types of the same type of data in different groups of data to be analyzed need to be unified. Optionally, the data types include integer type, character type, array type, etc. Different types of data in the data to be analyzed can be determined, and for each type of data, the data type is converted according to a preset data type that matches the type of data, and the data to be analyzed is updated based on the data obtained after the data type conversion.

[0040] In this embodiment, data types and data formats of different groups of data to be analyzed are converted, so that the data formats of different groups of data to be analyzed are unified, which provides convenience for subsequent data processing and data analysis operations.

[0041] In addition, in order to ensure the accuracy and validity of the obtained data to be analyzed, the obtained data to be analyzed may be cleaned. The data cleaning operation includes at least one of the operations of outlier removal, error data correction, missing value filling, and duplicate data removal.

[0042] In this embodiment, based on each group of data to be analyzed after the update, in order to facilitate viewing and analysis, a target large wide table can be generated based on the data to be analyzed, and the execution result label can be determined in the form of the large wide table. Specifically, the preset large wide table includes preset dimension fields and associated fields. The preset dimension fields can be determined based on the dimensions of the data to be analyzed; for example, the dimensions contained in the data to be analyzed can be used as preset dimension fields. For example, the dimensions include basic attributes, business-related attributes, statistical information, and timestamps, and the corresponding preset large wide table includes basic attribute fields, business-related attribute fields, statistical information fields, and timestamp fields. Among them, the basic attributes may include user identification; the business-related attributes include attribute information in the task to be analyzed, such as order status, payment information, and order value attribute values. Statistical information includes statistical indicators such as access volume and activity. The timestamp is used to record the time information of data creation and update. The associated field is a field used to establish an association between different dimensional data in the data to be analyzed, for example, the associated field may be at least one of a serial number, a user identification, and a session number.

[0043] Specifically, for each data to be analyzed, the dimension data of each dimension in the data to be analyzed can be extracted, each dimension data is added to the corresponding dimension field in the preset large wide table, and the preset large wide table after the dimension data is added is used as the target large wide table. In addition, the fact data in the data to be analyzed is loaded into the target large wide table, and the target large wide table is updated based on the large wide table after the fact data is loaded.

[0044] In this embodiment, by constructing a target large wide table, the data to be analyzed can be displayed more clearly and effectively, thereby facilitating the query of the execution result label.

[0045] In this embodiment, the data to be analyzed includes the sub-data to be analyzed generated by each associated business subsystem when executing the task to be analyzed. Exemplarily, the sub-data to be analyzed includes at least one of a session number, a serial number, an information collection image, a user identifier, an execution result content, and an execution result label. Among them, the execution result label includes an execution success label and an execution failure label. The execution success label is used to reflect that the execution is successful when the associated business subsystem executes the corresponding sub-task to be analyzed; the execution failure label is used to reflect that the execution fails when the associated business subsystem executes the corresponding sub-task to be analyzed. It should be noted that when any associated business subsystem in the task to be analyzed executes the sub-task to be analyzed, the execution result is failure, which means that the overall execution of the task to be analyzed has failed.

[0046] In the specific implementation, in order to understand the impact of each associated business subsystem on the execution process of the task to be analyzed, for each associated business subsystem, the sub-data to be analyzed that the associated business subsystem participates in processing are screened out from the data to be analyzed, and the execution result label is extracted from the sub-data to be analyzed that participates in the processing. The execution result label is the execution result label generated when the associated business subsystem processes the matching task to be analyzed.

[0047] S130: Determine the degree of influence of the associated business subsystem on the execution result of the system task based on at least one execution result tag corresponding to each associated business subsystem.

[0048] In this embodiment, the system task can be any task generated in the business system. The execution results include successfully executed tasks and failed executed tasks. Optionally, the method for determining the degree of influence of the associated business subsystem on the execution result of the system task can be: for each associated business system, determine the number of successes whose execution result label is the execution success label and the number of failures whose execution result label is the execution failure label; and use the ratio of the number of successes to the number of failures as the degree of influence of the associated business subsystem on the execution result of the system task.

[0049] Alternatively, based on at least one execution result tag corresponding to each associated business subsystem, determine the degree of influence of the associated business subsystem on the execution result of the system task, including: for each associated business system, determine the execution result tag as the number of successful execution success tags and the total number of execution result tags; and use the ratio of the number of successful executions to the total number as the degree of influence of the associated business subsystem on the execution result of the system task.

[0050] Specifically, the degree of influence can be used to reflect the degree of influence of the associated business subsystem on the successful execution of the system task. The ratio of the number of successes to the total number can be used as the degree of influence of the associated business subsystem on the successful execution of the system task. The higher the degree of influence, the more the associated business subsystem contributes to the successful execution of the system task; conversely, the lower the degree of influence, the more likely the associated business subsystem is to cause the failure of the system task execution.

[0051] Exemplarily, the task to be analyzed may be an information authentication task, and the associated business subsystems involved in the information authentication task are as follows: tracking subsystem A, client subsystem B, security authentication subsystem C and facial recognition subsystem D. The business trigger is triggered by the preset operation in the tracking subsystem A, which triggers the facial recognition authentication in the authentication method in the client subsystem B, and the authority authentication and facial image retrieval are performed in the security authentication subsystem C, and then matched by the facial recognition subsystem D, thereby completing the information authentication task. When determining the degree of influence given by each associated business subsystem, the authentication task data corresponding to multiple information authentication tasks can be obtained, and the execution result labels of the tracking subsystem A, client subsystem B, security authentication subsystem C and facial recognition subsystem D are determined based on the authentication task data each time the information authentication task is executed. For each associated business subsystem, the number of successful execution labels and the total number of execution result labels are determined, and the ratio of the successful number to the total number is used as the degree of influence on the execution result of the information authentication task.

[0052] In this embodiment, the ratio of the number of successes to the total number is equivalent to the success rate of each associated subsystem in executing the task. The success rate can more accurately and effectively reflect the impact of the associated business subsystem on the execution result.

[0053] Furthermore, this embodiment also includes: when the time between the current moment and the preset data acquisition moment is less than the preset time, determining the target business subsystem that has not sent the business data to be acquired; generating reminder information based on the business data to be acquired, and sending the reminder information to the target business subsystem.

[0054] In order to effectively determine the impact of the business subsystem, a preset data acquisition time can be pre-set; for example, 0:00 p.m. every day, the impact of the business subsystem is determined, and 0:00 p.m. every day can be used as the preset data acquisition time. In order to ensure that the data to be analyzed can be successfully acquired, the time from the current time to the preset data acquisition time can be detected. When the time is less than the preset time, the business subsystem needs to be reminded to provide business data. Exemplarily, the preset time can be several hours or a day.

[0055] Specifically, the business subsystems that generate the business data to be acquired can be pre-stored. When the time between the current moment and the preset data acquisition moment is less than the preset time, the business subsystem that has not sent the business data to be acquired will be taken as the target business subsystem. Reminder information is generated based on the unacquired business data to be acquired, and the reminder information is sent to the target business subsystem, so that the target business subsystem can provide the data to be acquired in time, ensuring that the operation with a determined impact degree can be effectively completed.

[0056] In this embodiment, after determining the impact of the associated business subsystem on the execution result of the system task, it also includes: generating a result analysis report based on the impact level corresponding to each associated business subsystem, and sending the result analysis report to the operation and maintenance terminal.

[0057] In order to facilitate staff to understand the working status of the business subsystem, a result analysis report can be generated based on the degree of impact. The result analysis report includes the degree of impact of each associated business subsystem on different tasks to be analyzed. In addition, the result analysis report can be sent to the operation and maintenance terminal so that staff can promptly view the impact of the associated business subsystem on the execution results of the system tasks.

[0058] The technical solution of the embodiment of the present invention obtains data to be analyzed corresponding to at least one task to be analyzed executed by a business system in a historical time period; wherein the data to be analyzed is business data generated by each associated business subsystem used to execute the task to be analyzed when executing the task to be analyzed; and, for each associated business subsystem, based on the data to be analyzed corresponding to the associated business subsystem, determines the execution result label generated when the associated business subsystem executes the task to be analyzed matching the associated business subsystem; wherein the execution result label includes an execution success label and an execution failure label; finally, based on at least one execution result label corresponding to each associated business subsystem, determines the degree of influence of the associated business subsystem on the execution result of the system task, so that in the process of determining the degree of influence, there is no need for staff participation, thereby avoiding waste of human resources; and, by determining the degree of influence through the execution result label, the accuracy and effectiveness of the determined degree of influence are improved.

[0059] The above describes in detail the embodiments corresponding to the method for determining the degree of impact. In order to make those skilled in the art further understand the technical solution of the present method, the following describes the system for determining the degree of impact that implements the method for determining the degree of impact. In this embodiment, the system for determining the degree of impact includes a data access module, a data processing module, a data application module, and a data detection module. The data access module is used to access the business data generated by each associated business subsystem. The business data includes structured data and unstructured data to form source layer data. The data application module performs data analysis based on the data obtained by the general layer and service layer of the data processing module, and forms a report to provide to the business system for business improvement. The data detection module is used to detect the progress of data acquisition, the quality of data file loading, the timeliness of the entire link of data processing, and the data application status, and finally generates a detection report based on the detection results.

[0060] The data processing module includes the basic layer, the general layer, and the service layer. The basic layer is used to standardize the acquired business data, perform consistency dimensioning, unstructured data parsing, and time zipper accumulation. The general layer splices the dimensions involved into the target large wide table according to the execution process of the system task, thereby intuitively displaying the entire execution process. The service layer determines the degree of influence of each associated subsystem based on the data of the target large wide table.

[0061] In a specific implementation, the execution process may include the following steps:

[0062] 1. The business data generated by each associated business subsystem is connected to the data access module in the form of files to form source layer data, which is used as the data to be analyzed. The data to be analyzed includes structured data and unstructured data.

[0063] 2. Reprocess the data to be analyzed through the data processing module. The reprocessing process is as follows: (1) Standardization processing: Use the same preset format and preset data type to convert the data to be analyzed. (2) Unify the dimensions between different data to be analyzed, that is, set the dimensional data with the same key, attribute name, attribute definition and domain value to the same dimension. (3) Unstructured data analysis: For the unstructured data in the acquired data to be analyzed, based on the pre-set target data dimension, a query request can be sent to the associated business subsystem that generates the unstructured data to query the data acquisition method of the target data field. Based on the acquisition method fed back by the associated business subsystem, the data of the target data field is acquired from the unstructured data, the queried data of the target data field is saved, and the acquired unstructured data is deleted. (4) Time zipper accumulation: In order to save storage space, the main file data in the data to be analyzed can be subjected to time zipper accumulation processing.

[0064] 3. Generate a target large wide table based on the data to be analyzed after the time zipper accumulation processing, and associate data of different dimensions through associated fields. Determine the impact of the associated business subsystem through the target large wide table, and generate a result analysis report based on the impact. Furthermore, based on the target large wide table, establish a corresponding relationship between different user portraits and the impact of the associated business subsystem, so that the staff can understand the impact of user attributes on the impact of the associated business subsystem.

[0065] 4. Check the progress of data acquisition, the quality of data file loading, the timeliness of the entire data processing chain, and the data application status. Finally, generate a test report based on the test results to ensure the reliability and sustainability of the reprocessing process.

[0066] In this embodiment, complex business data of associated subsystems are sorted into a target large wide table according to associated fields, and the impact of the associated business subsystems is determined through the execution result labels in the target large wide table, which is conducive to improving the task execution success rate of the business system.

[0067] Figure 2 1 is a schematic diagram of the structure of an impact determination device provided according to an embodiment of the present invention, and the device is used to execute the impact determination method provided in any of the above embodiments. The device and the impact determination method of the above embodiments belong to the same inventive concept, and the details not described in detail in the embodiment of the impact determination device can refer to the embodiment of the above impact determination method. Figure 2 As shown, the device comprises:

[0068] The to-be-analyzed data acquisition module 10 is used to acquire the to-be-analyzed data corresponding to at least one to-be-analyzed task executed by the business system in a historical time period; wherein the to-be-analyzed data is the business data generated by each associated business subsystem for executing the to-be-analyzed task when executing the to-be-analyzed task;

[0069] The tag determination module 11 is used to determine, for each associated business subsystem, based on the to-be-analyzed data corresponding to the associated business subsystem, the execution result tag generated when the associated business subsystem executes the to-be-analyzed task matching the associated business subsystem; wherein the execution result tag includes an execution success tag and an execution failure tag;

[0070] The impact degree determination module 12 is used to determine the impact degree of the associated business subsystem on the execution result of the system task based on at least one execution result tag corresponding to each associated business subsystem.

[0071] Based on any optional technical solution in the embodiments of the present invention, optionally, the method further includes:

[0072] A data preprocessing module is used to perform data preprocessing operations on each group of data to be analyzed before determining the execution result label generated when the associated business subsystem executes the task to be analyzed matching the associated business subsystem based on the data to be analyzed corresponding to the associated business subsystem, and update the data to be analyzed with the data obtained after the data preprocessing;

[0073] A data extraction module is used to extract dimension data of each dimension of each data to be analyzed;

[0074] A target large wide table generation module is used to splice each dimension data into a preset large wide table to generate a target large wide table; wherein the target large wide table includes dimension fields and associated fields, the dimension fields are fields corresponding to the dimension data, and the dimension data includes an execution result label;

[0075] The data loading module is used to load the fact data in the data to be analyzed into the target large wide table, and update the target large wide table based on the large wide table after the fact data is loaded.

[0076] Based on any optional technical solution in the embodiments of the present invention, optionally, the data preprocessing module includes:

[0077] A first updating unit is configured to perform format conversion on the data to be analyzed according to a preset format for each group of data to be analyzed, and update the data to be analyzed based on the data after the format conversion; and / or,

[0078] The second updating unit is used to convert the data to be analyzed into data of a preset data type for each group of data to be analyzed, and update the data to be analyzed with the data obtained after the conversion.

[0079] Based on any optional technical solution in the embodiment of the present invention, optionally, the impact degree determination module 12 includes:

[0080] A quantity determination unit, used for determining, for each associated business system, the number of successful executions whose execution result tags are execution success tags and the total number of execution result tags;

[0081] The impact degree determination unit is used to use the ratio of the success number to the total number as the impact degree of the associated business subsystem on the execution result of the system task.

[0082] Based on any optional technical solution in the embodiments of the present invention, optionally, the method further includes:

[0083] A target business subsystem determination module, used to determine a target business subsystem that has not sent the business data to be obtained when the time length from the current moment to the preset data acquisition moment is less than the preset time length;

[0084] The reminder information generation module is used to generate reminder information based on the business data to be acquired and send the reminder information to the target business subsystem.

[0085] Based on any optional technical solution in the embodiments of the present invention, optionally, the method further includes:

[0086] The result analysis report generation module is used to generate a result analysis report based on the corresponding impact degree of each associated business subsystem after determining the impact degree of the associated business subsystem on the execution result of the system task, and send the result analysis report to the operation and maintenance terminal.

[0087] The technical solution of the embodiment of the present invention obtains data to be analyzed corresponding to at least one task to be analyzed executed by a business system in a historical time period; wherein the data to be analyzed is business data generated by each associated business subsystem used to execute the task to be analyzed when executing the task to be analyzed; and, for each associated business subsystem, based on the data to be analyzed corresponding to the associated business subsystem, determines the execution result label generated when the associated business subsystem executes the task to be analyzed matching the associated business subsystem; wherein the execution result label includes an execution success label and an execution failure label; finally, based on at least one execution result label corresponding to each associated business subsystem, determines the degree of influence of the associated business subsystem on the execution result of the system task, so that in the process of determining the degree of influence, there is no need for staff participation, thereby avoiding waste of human resources; and, by determining the degree of influence through the execution result label, the accuracy and effectiveness of the determined degree of influence are improved.

[0088] It is worth noting that in the embodiment of the above-mentioned impact degree determination device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0089] Figure 3 1 is a schematic diagram of the structure of an electronic device that implements the method for determining the degree of influence of an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0090] like Figure 3As shown, the electronic device 20 includes at least one processor 21, and a memory connected to the at least one processor 21, such as a read-only memory (ROM) 22, a random access memory (RAM) 23, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 21 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 22 or the computer program loaded from the storage unit 28 to the random access memory (RAM) 23. In RAM23, various programs and data required for the operation of the electronic device 20 can also be stored. The processor 21, ROM22 and RAM23 are connected to each other through a bus 24. An input / output (I / O) interface 25 is also connected to the bus 24.

[0091] A number of components in the electronic device 20 are connected to the I / O interface 25, including: an input unit 26, such as a keyboard, a mouse, etc.; an output unit 27, such as various types of displays, speakers, etc.; a storage unit 28, such as a disk, an optical disk, etc.; and a communication unit 29, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 29 allows the electronic device 20 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0092] The processor 21 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 21 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 21 executes the various methods and processes described above, such as the impact degree determination method.

[0093] In some embodiments, the method for determining the degree of influence may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 28. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 20 via the ROM 22 and / or the communication unit 29. When the computer program is loaded into the RAM 23 and executed by the processor 21, one or more steps of the method for determining the degree of influence described above may be performed. Alternatively, in other embodiments, the processor 21 may be configured to perform the method for determining the degree of influence in any other appropriate manner (e.g., by means of firmware).

[0094] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0095] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0096] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0097] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0098] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0099] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0100] This embodiment also provides a computer program product, including a computer program, which, when executed by a processor, implements the method for determining the degree of influence provided in any embodiment of the present application.

[0101] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "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 separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0102] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0103] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for determining the degree of influence, characterized in that: include: Acquire data to be analyzed corresponding to at least one task to be analyzed executed by the business system in a historical time period; wherein the data to be analyzed is business data generated by each associated business subsystem for executing the task to be analyzed when executing the task to be analyzed; For each of the associated business subsystems, based on the to-be-analyzed data corresponding to the associated business subsystem, determining an execution result tag generated when the associated business subsystem executes the to-be-analyzed task matching the associated business subsystem; wherein the execution result tag includes an execution success tag and an execution failure tag; Based on at least one of the execution result tags corresponding to each of the associated business subsystems, the degree of influence of the associated business subsystem on the execution result of the system task is determined.

2. The method according to claim 1, characterized in that Before the execution result label generated when determining that the associated business subsystem executes the task to be analyzed matching the associated business subsystem based on the data to be analyzed corresponding to the associated business subsystem, the method further includes: Performing data preprocessing operations on each group of the data to be analyzed, and updating the data to be analyzed with the data obtained after the data preprocessing; For each of the data to be analyzed, extracting dimension data of each dimension of the data to be analyzed; Each dimension data is spliced ​​into a preset large wide table to generate a target large wide table; wherein the target large wide table contains dimension fields and associated fields, the dimension fields are fields corresponding to the dimension data, and the dimension data includes the execution result label; The fact data in the data to be analyzed is loaded into the target large wide table, and the target large wide table is updated based on the large wide table after the fact data is loaded.

3. The method according to claim 2, characterized in that The performing of a data preprocessing operation on each group of the data to be analyzed, and updating the data to be analyzed with the data obtained after the data preprocessing, comprises: For each group of the data to be analyzed, convert the data to be analyzed according to a preset format, and update the data to be analyzed based on the data after the format conversion; and / or, For each group of the data to be analyzed, the data to be analyzed is converted into data of a preset data type, and the data obtained after the conversion is used to update the data to be analyzed.

4. The method according to claim 1, characterized in that: The determining, based on at least one of the execution result tags corresponding to each of the associated business subsystems, the degree of influence of the associated business subsystem on the execution result of the system task includes: For each of the associated business systems, determining the number of successful execution tags and the total number of execution result tags for which the execution result tag is a successful execution tag; The ratio of the success number to the total number is used as the influence of the associated business subsystem on the execution result of the system task.

5. The method according to claim 1, characterized in that Also includes: When the time between the current moment and the preset data acquisition moment is less than the preset time, determining the target business subsystem that has not sent the business data to be acquired; Reminder information is generated based on the business data to be acquired, and the reminder information is sent to the target business subsystem.

6. The method according to claim 1, characterized in that After determining the influence degree of the associated business subsystem on the execution result of the system task, the method further includes: Based on the impact degree corresponding to each of the associated business subsystems, a result analysis report is generated, and the result analysis report is sent to the operation and maintenance terminal.

7. An impact degree determination device, characterized in that: include: The data acquisition module for analysis is used to acquire the data for analysis corresponding to at least one task for analysis executed by the business system in a historical time period; wherein the data for analysis is the business data generated by each associated business subsystem for executing the task for analysis when executing the task for analysis; a label determination module, for each of the associated business subsystems, based on the to-be-analyzed data corresponding to the associated business subsystem, determining an execution result label generated when the associated business subsystem executes a to-be-analyzed task matching the associated business subsystem; wherein the execution result label includes an execution success label and an execution failure label; The impact degree determination module is used to determine the impact degree of the associated business subsystem on the execution result of the system task based on at least one of the execution result tags corresponding to each of the associated business subsystems.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the influence degree determination method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for determining the degree of influence according to any one of claims 1 to 6 when executed.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method for determining the degree of influence according to any one of claims 1 to 6.

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