Data processing method and device

Abstract

The embodiment of the invention provides a data processing method and device, and the method comprises the steps: obtaining a business plan table and a business operation table of a related part change business, the business plan table comprises business plan data of the part change business, and the business operation table comprises business operation data of the part change business; the business operation table comprises business operation data of the part change business; preprocessing the business plan data to obtain target business plan data, and selecting business operation sub-data in the business operation data according to a preset data selection strategy; screening target business plan sub-data from the target business plan data based on the business operation sub-data; and comparing the target business plan sub-data with the business operation sub-data, and determining part change monitoring information corresponding to the part change business according to a comparison result. The abnormal condition in the part change service is efficiently found out, and normal implementation of the part change service is guaranteed.

Description

Technical Field

[0001] The embodiments of the present specification relate to the field of data monitoring technology, and in particular, to a data processing method. Background Art

[0002] With the rapid development of the automotive industry, in the current vehicle model development process or mass production, when encountering vehicle change management, the change manager needs to monitor the key states and nodes of the entire change process, and manually compare the monitoring data to ensure that there are no abnormalities in the change process. However, due to the large amount of monitoring data and complex structure, the manual analysis and processing workload is large and difficult, resulting in the inability to quickly and effectively troubleshoot abnormalities in the change process, causing losses to the company. Therefore, how to achieve efficient comparison of change process monitoring data and rapid screening of abnormalities is an urgent problem to be solved. Summary of the invention

[0003] In view of this, an embodiment of this specification provides a data processing method. One or more embodiments of this specification also relate to a data processing device, a computing device, a computer-readable storage medium and a computer program to solve the technical defects existing in the prior art.

[0004] According to a first aspect of an embodiment of this specification, a data processing method is provided, including:

[0005] Acquire a business plan table and a business operation table for the associated parts change business, wherein the business plan table includes the business plan data for the parts change business, and the business operation table includes the business operation data for the parts change business;

[0006] Preprocessing the business plan data to obtain target business plan data, and selecting business operation sub-data from the business operation data according to a preset data selection strategy;

[0007] Filtering target business plan sub-data from the target business plan data based on the business operation sub-data;

[0008] The target business plan sub-data and the business operation sub-data are compared, and the part change monitoring information corresponding to the part change business is determined according to the comparison result.

[0009] According to a second aspect of an embodiment of this specification, there is provided a data processing device, including:

[0010] An acquisition module is configured to acquire a business plan table and a business operation table of an associated part change business, wherein the business plan table includes business plan data of the part change business, and the business operation table includes business operation data of the part change business;

[0011] A preprocessing module is configured to preprocess the business plan data to obtain target business plan data, and select business operation sub-data from the business operation data according to a preset data selection strategy;

[0012] A screening module, configured to screen target business plan sub-data in the target business plan data based on the business operation sub-data;

[0013] The comparison module is configured to compare the target business plan sub-data with the business operation sub-data, and determine the part change monitoring information corresponding to the part change business according to the comparison result.

[0014] According to a third aspect of an embodiment of this specification, a computing device is provided, including:

[0015] Memory and processor;

[0016] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the above data processing method are implemented.

[0017] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided, which stores computer-executable instructions, and when the instructions are executed by a processor, the steps of the above-mentioned data processing method are implemented.

[0018] According to a fifth aspect of the embodiments of this specification, a computer program is provided, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the above-mentioned data processing method.

[0019] An embodiment of the present specification realizes preprocessing of business plan data in the business plan table by obtaining a business plan table and a business operation table for a part change business, obtaining target business plan data, selecting business operation sub-data from the business operation data according to a preset data selection strategy, and then filtering out target business plan sub-data from the target business plan data based on the business operation sub-data, and more accurately obtaining data for subsequent comparison through business logic and data selection strategies, thereby improving the accuracy and timeliness of data monitoring and analysis, and determining the part change monitoring information corresponding to the part change business by comparing the target business plan sub-data and the business operation sub-data, thereby solving the problems of time waste and inaccurate comparison results caused by manual data comparison, thereby being able to efficiently find out abnormal situations in the part change business and ensure the normal implementation of the part change business. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a scenario diagram of a data processing method provided by an embodiment of this specification;

[0021] Figure 2 is a flow chart of a data processing method provided by an embodiment of this specification;

[0022] Figure 3 It is a display schematic diagram of a visual display interface of a data processing method provided by an embodiment of this specification;

[0023] Figure 4 is a processing flow chart of a data processing method provided by an embodiment of this specification;

[0024] Figure 5 is a structural schematic diagram of a data processing device provided by an embodiment of this specification;

[0025] Figure 6 It is a structural block diagram of a computing device provided by an embodiment of this specification. DETAILED DESCRIPTION

[0026] Many specific details are described in the following description to facilitate a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of this specification, so this specification is not limited to the specific implementation disclosed below.

[0027] The terms used in one or more embodiments of this specification are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of this specification. The singular forms of "a", "said" and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0028] It should be understood that although the terms first, second, etc. may be used to describe various information in one or more embodiments of this specification, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0029] In addition, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0030] At present, in the change management business for the whole vehicle, when an abnormal change case occurs in the change management business, the change manager needs to align and intervene reasonably to get it back on track. Therefore, the change manager needs to monitor the key status and nodes of the entire change process. The current monitoring method is that the change manager downloads the business plan table and the business operation table to the local client respectively, filters the change business data to be viewed from the business plan table and the business operation table, and manually checks and tracks the key nodes and data status of the current change business offline. However, due to the large volume of change management business and the large amount of business data, the accuracy of monitoring cannot be guaranteed, and the scope of manual monitoring is limited, and the timeliness of monitoring cannot be guaranteed. Change managers need to spend a lot of time to screen and integrate data, and the monitoring efficiency is very low. In addition, the change manager operates the data offline, and the transparency of monitoring cannot be achieved.

[0031] Based on this, in this specification, a data processing method is provided to screen and integrate the data contained in the business plan table and the business operation table according to the business logic, improve the data screening efficiency, and facilitate subsequent data comparison. This specification also relates to a data processing device, a computing device, and a computer-readable storage medium, which are described in detail one by one in the following embodiments.

[0032] See also Figure 1 , Figure 1A scenario diagram of a data processing method provided according to an embodiment of the present specification is shown, wherein the business plan table contains business plan data of a part change business, such as an automobile manufacturer, a part identification before change, a part identification after change, execution time information, etc. The business plan data is the relevant data for setting a plan before the enterprise executes the part change business. The business operation table contains business operation data of the part change business, such as a change start time, a change end time, etc. The business operation data is the data actually generated by the enterprise in the process of executing the part change business. Since there may be a lot of data that does not need to be paid attention to or is repeated in the business plan table, it is necessary to pre-process the business plan data in the business plan table to obtain target business plan data. There are many business data of different dates in the business operation table. In order to determine and compare the business operation data within a certain time period, it is necessary to select business operation sub-data from the business operation table, and then filter out the data to be compared from the target business plan data according to the operation sub-data, that is, the target business plan sub-data, and compare the target business plan sub-data with the business operation sub-data, so as to determine the part change monitoring information corresponding to the part change business. It realizes the integration, analysis and comparison of data in the business plan table and the business operation table, saving time for manual data sorting, analysis and comparison, improving data analysis efficiency, and improving the timeliness and accuracy of monitoring parts change business.

[0033] See also Figure 2 , Figure 2 A flow chart of a data processing method provided according to an embodiment of the present specification is shown, which specifically includes the following steps.

[0034] Step 202: Acquire a business plan table and a business operation table of an associated part change business, wherein the business plan table includes business plan data of the part change business, and the business operation table includes business operation data of the part change business.

[0035] Among them, the parts change business can be understood as the business of changing parts of the whole vehicle or auto parts in the car company, such as changing the hood, window, etc. used in the car. Before executing the parts change business, the car company will plan the entire change process of the parts change business and generate a business plan table. The business plan table includes the business plan data of the parts change business. The business plan data can be understood as the status and nodes of the change business process planned in advance, such as the start time of a certain part change process, the manufacturer of the parts, the release information of the process, etc. The business plan table is used as a basis for judging whether the parts change business is running normally. The change administrator can compare the business plan data in the business plan table with the actual operation data when the parts change business is executed, so as to determine whether there is any abnormality in the current parts change business. The actual operation data when the parts change business is executed will be stored in the business operation table, that is, the business operation data in the business operation table.

[0036] In actual applications, the change administrator needs to filter out the plan data and operation data that need to be compared from the business plan table and the business operation table, and then manually compare them one by one, which is inaccurate and inefficient. Therefore, in an embodiment of this specification, after obtaining the business plan table and the business operation table, the data that needs to be analyzed and compared can be automatically extracted from the business plan table and the business operation table according to the business operation logic, and then automatically compared, avoiding the problem of low efficiency of part change business monitoring and inability to accurately detect abnormal situations due to manual screening and comparison of data.

[0037] In a specific embodiment of this specification, a certain automobile enterprise needs to change parts for a certain automobile. In the process of executing the parts change business, the business data monitoring system can obtain the business plan table and business operation table of the business. The business data monitoring system can be understood as the system used by the enterprise to monitor whether the business is abnormal. The change administrator can observe the operation of the business from the business data monitoring system. After obtaining the business plan table and business operation table, the business data monitoring system can perform subsequent data comparison to determine whether there is an abnormality in the process node of the business.

[0038] Furthermore, there is change data outside the business monitoring scope in the planning data of the part change business. There is no need to pay attention to this part of data. In order to avoid wasting time and resources due to analysis and comparison on data that do not need to be paid attention to, this part of data can be removed when determining the business plan table of the part change business. Specifically, the business plan table of the associated part change business is obtained, including: obtaining the initial business plan table of the associated part change business, and determining the data identifier to be removed in the initial business plan table; determining the blank item corresponding to the data identifier to be removed, deleting the row data corresponding to the blank item in the business plan data, and obtaining the business plan table.

[0039] Among them, the initial business plan table can be understood as the original business plan table for the part change business. The initial business plan table contains change data outside the monitoring scope. For example, the data rows with empty part change identification numbers (ChangeContext-ID) in the initial business plan table are all change data outside the monitoring scope, that is, when the change context identifier is empty, all data in the row where the change context identifier is located does not need to be paid attention to, and this part of the data can be removed. That is, the data identifier to be removed can be understood as the identifier of data that does not need to be paid attention to. After determining the data identifier to be removed, the data that does not need to be paid attention to can be deleted from the business plan data according to the identifier to be removed.

[0040] In actual applications, when the data item corresponding to the data identifier to be removed is empty, it means that the data row where the data item is located does not need to be paid attention to and can be deleted. For example, Table 1, Table 1 is the initial business plan table provided in an embodiment of this specification, wherein PreECPresult represents the result of the pre-change process; MRCL represents the technical change of automobile parts; State represents the state of the part change; ECP represents the technical change file package; Run-in represents the part change date; ECPStatus represents the status of ECP; ChangeContext-ID represents the part change identification number. Determine that the data identifier to be removed is the part change identification number ChangeContext-ID. It can be seen that in the first row of data, the data item corresponding to ChangeContext-ID is a blank item, then the entire data row where the blank data item is located can be deleted. In the second row of data, the data item corresponding to ChangeContext-ID is not a blank item, then the data in this row is retained.

[0041] Table 1

[0042]

[0043] In a specific embodiment of the present specification, an initial business plan table for an associated parts change business is obtained, and a data identifier to be removed is determined in the initial business plan table, where the data identifier to be removed is ChangeContext-ID. A blank item corresponding to the data identifier to be removed is determined in the initial business plan table, and row data corresponding to the blank item is deleted from the business plan data to obtain a business plan table.

[0044] Based on this, by deleting unnecessary data in the initial business plan table, a business plan table is obtained, which is conducive to subsequent data comparison and improves data comparison efficiency.

[0045] Step 204: pre-process the business plan data to obtain target business plan data, and select business operation sub-data from the business operation data according to a preset data selection strategy.

[0046] Among them, the target business plan data can be understood as the business plan data after preprocessing the business plan data. The same data exists in the business plan data, so the business plan data can be simply screened and preprocessed to obtain the target business plan data, thereby improving the efficiency of subsequent data comparison. The preset data selection strategy can be understood as a pre-set strategy for selecting data from the business operation data, and the business operation sub-data can be understood as part of the data filtered out from the business operation according to the preset data selection strategy. Since the business operation data includes business operation data for multiple time periods, in order to improve the efficiency of subsequent data comparison, data can be filtered based on time points according to the preset data filtering strategy.

[0047] In a specific embodiment of the present specification, the business plan data is preprocessed, and the preprocessing includes classifying repeated data as the same data, so as to obtain target business plan data. The business operation sub-data within a required time period is selected from the business operation data according to a preset data selection strategy.

[0048] Furthermore, in order to avoid low efficiency of subsequent data comparison due to duplicate data in the business plan data, it is necessary to delete the duplicate data from the business plan data. Specifically, the business plan data is preprocessed to obtain target business plan data, including: determining the data identifier to be deleted and the data to be deleted corresponding to the data identifier to be deleted in the business plan data; if there is data duplication in the data to be deleted, deleting the duplicate data of the data to be deleted in the business plan data to obtain the target business plan data.

[0049] Among them, the data identifier to be deleted can be understood as the data identifier defined when deleting duplicate data. Since the business plan data contains multiple data identifiers, the data identifier to be deleted can be determined during business execution. The field composed of the data identifier to be deleted can be used as the data identification field used when deleting duplicate data. For example, it is determined that the data identifier to be deleted includes [data identifier 1], [data identifier 2], and [data identifier 3]. These three data identifiers are used as data identification fields, and the data to be deleted corresponding to these three data identifiers are determined. When the data fields composed of the data to be deleted corresponding to the three data identifiers are the same, this indicates that there is data duplication in the three data to be deleted. Two of the duplicate data can be deleted and one data can be retained as the data in the target business plan data.

[0050] In a specific embodiment of the present specification, the identifier of the data to be deleted is determined in the business plan data, and the identifier of the data to be deleted is [mat.No.old]...[Change context]. These identifiers of the data to be deleted are used as the identifier fields of the data to be deleted for determining duplicate data. When the data fields composed of these data to be deleted are the same, it is determined that there is data duplication in the data to be deleted, and the duplicate data of the data to be deleted is deleted in the business plan data, thereby obtaining the target business plan data.

[0051] Based on this, by deleting duplicate data in the business plan data, it is easier to perform subsequent data comparison and improve data comparison efficiency.

[0052] Furthermore, in order to avoid low efficiency of subsequent data comparison due to excessive data in the business operation sub-data, the business operation data can be screened according to a preset data selection strategy. Specifically, the business operation sub-data is selected from the business operation data according to the preset data selection strategy, including: obtaining target time information according to the preset data selection strategy, and determining screening time information based on the target time information; and selecting business operation sub-data from the business operation data based on the screening time information.

[0053] Among them, the preset data selection strategy can be understood as a strategy set in advance for screening the data to be compared in the business operation data. Since the business operation data includes operation data corresponding to multiple time periods, the preset data selection strategy can screen the data according to the time point. The target time information can be understood as the time reference point information. According to the target time information, the screening time information for time screening in the business operation data can be determined, and the business operation sub-data can be selected from the business operation data through the screening time information.

[0054] In actual applications, the target time information is obtained according to the preset data selection strategy. The target time information may be based on the time and date of the preset data selection strategy. For example, if the preset data selection strategy is executed on May 3, 2021, the target time information may be 2021.5.3. The filtering time information may be determined according to the target time information by searching the business operation data for the start time point and stop time point closest to the target time according to the target time information, using the determined start time point and stop time point as the filtering time information, and selecting the business operation sub-data from the business operation data according to the filtering time information.

[0055] In a specific embodiment of the present specification, target time information is obtained according to a preset data selection strategy, the target time information is 2021.4.8, and filtering time information is determined in the business operation data based on the target time information, the filtering time information is 2021.4.10 and 2021.5.3, and data in the time period from 2021.4.10 to 2021.5.3 is selected from the business operation data according to the filtering time information as business operation sub-data.

[0056] Based on this, the business operation sub-data is screened out from the business operation data according to the preset data selection strategy, so that data comparison can be performed according to time information later, thereby improving data comparison efficiency.

[0057] Step 206: Filter target business plan sub-data in the target business plan data based on the business operation sub-data.

[0058] Among them, the target business plan sub-data can be understood as part of the data filtered out from the target business plan data based on the business operation sub-data. Since the business operation sub-data is data filtered out from the business operation data through a preset data selection strategy, in order to perform subsequent data comparison, it is also necessary to filter out data with the same data identifier from the target business plan data before subsequent data comparison can be performed.

[0059] In actual applications, after filtering out the operation data within the time period of the filtering time information from the business operation data according to the preset data selection strategy, it is necessary to filter out the plan data with the same identifier from the target business plan data for subsequent data comparison.

[0060] In a specific embodiment of the present specification, target business plan sub-data are screened from target business plan data based on business operation sub-data.

[0061] Furthermore, in order to avoid the subsequent failure of normal data comparison, it is necessary to filter out the target business plan sub-data that needs to be compared from the target business plan data based on the filtered business operation sub-data. Specifically, the target business plan sub-data is filtered out in the target business plan data based on the business operation sub-data, including: determining a filtering data identifier in the business operation sub-data; and filtering the target business plan sub-data in the target business plan data based on the filtering data identifier.

[0062] Among them, a screening data identifier is determined in the business operation sub-data. The screening data identifier can be understood as a data identifier used for screening in the target business plan data. The screening data identifier is the data identifier in the business operation sub-data. The target business plan sub-data can be understood as data in the target business plan data used for comparison with the business operation sub-data.

[0063] In actual application, after the business operation sub-data is determined, the target business plan sub-data can be filtered from the target business plan data based on the filtering data identifier of the business operation sub-data. The filtering data identifier can be a release (release permission) data identifier in the business operation sub-data, and the data row related to the release data identifier is found in the target business plan data.

[0064] In a specific embodiment of the present specification, a screening data identifier is determined in the business operation sub-data, and target business plan sub-data is screened in the target business plan data based on the screening data identifier.

[0065] Based on this, the filtering data identifier is determined through the business operation sub-data, and the target business plan sub-data is filtered from the target business plan sub-data based on the filtering data identifier, so that the business operation sub-data and the target business plan sub-data can be compared subsequently to determine whether there are any abnormalities in the parts change business.

[0066] Step 208: Compare the target business plan sub-data with the business operation sub-data, and determine the part change monitoring information corresponding to the part change business according to the comparison result.

[0067] Among them, the parts change monitoring information can be understood as the monitoring information corresponding to the parts change business. Through the parts change monitoring information, it can be determined whether there are abnormal situations in the parts change business.

[0068] In actual applications, after comparing the target business plan sub-data and the business operation sub-data, it can be determined whether the actual business operation corresponding to the part change business meets the expected business plan, thereby judging whether the part change business is running according to plan.

[0069] In a specific embodiment of the present specification, the target business plan sub-data and the business operation sub-data are compared, and the part change monitoring information corresponding to the part change business is determined according to the comparison result.

[0070] Furthermore, in order to avoid erroneous comparison of plan data and operation data, data comparison can be performed based on a comparison identifier, specifically comparing the target business plan sub-data and the business operation sub-data, including: determining a comparison identifier, and based on the comparison identifier, determining a first comparison sub-data in the target business plan sub-data, and determining a second comparison sub-data in the business operation sub-data; and comparing the first comparison sub-data with the second comparison sub-data.

[0071] Among them, the comparison identifier can be understood as the data identifier of the data to be compared, and based on the comparison identifier, the data to be compared can be screened out from the target business plan sub-data and the business operation sub-data respectively. After determining the comparison identifier, the first comparison sub-data can be determined from the target business plan sub-data, and the second comparison sub-data can be determined from the business operation sub-data. The first comparison sub-data can be understood as the plan data to be compared selected from the target business plan sub-data, and the second comparison sub-data can be understood as the operation data to be compared selected from the business operation sub-data. By comparing the first comparison sub-data and the second comparison sub-data, the data comparison between the target business plan sub-data and the business operation sub-data is achieved.

[0072] In actual applications, the target business plan sub-data and the business operation sub-data respectively include data with multiple different data identifiers. In order to perform a one-to-one data comparison, it is necessary to determine the comparison identifier, and based on the comparison identifier, determine the first comparison sub-data and the second comparison sub-data from the target business plan sub-data and the business operation sub-data respectively, and then compare the first comparison sub-data with the second comparison sub-data.

[0073] In a specific embodiment of the present specification, a comparison identifier is determined, the comparison identifier is Plant, and the first comparison sub-data and the second comparison sub-data are determined from the target business plan sub-data and the business operation sub-data respectively according to the comparison identifier, and then the first comparison sub-data and the second comparison sub-data are compared to obtain whether the data under the comparison identifier dimension is normal.

[0074] Based on this, the data under the same data dimension can be determined by comparing the identifiers, ensuring normal comparison of the data.

[0075] Furthermore, in order to ensure that the administrator can correctly understand the business operation status of the part change business from the comparison results, the corresponding part change monitoring information can be reflected to the administrator based on the comparison results. Specifically, the part change monitoring information corresponding to the part change business is determined based on the comparison results, including: when the comparison result is inconsistent, the part change monitoring information corresponding to the part change business is determined to be an abnormal part change; when the comparison result is consistent, the part change monitoring information corresponding to the part change business is determined to be a normal part change.

[0076] In actual applications, when the comparison results of the operating data and the planned data are inconsistent, it means that there is an abnormality in the part change business, and the part change monitoring information is that the part change is abnormal; when the comparison results of the operating data and the planned data are consistent, it means that there is no abnormality in the part change business, and the part change monitoring information is that the part change is normal. The part change monitoring information can clearly show whether there is an abnormality in the part change business.

[0077] In a specific embodiment of the present specification, the first comparison sub-data and the second comparison sub-data are compared. If the comparison result is inconsistent, it means that an abnormality occurs in the part change business. In this case, the part change monitoring information is a part change abnormality.

[0078] In another specific embodiment of the present specification, the first comparison sub-data and the second comparison sub-data are compared, and if the comparison result is consistent, it means that there is no abnormality in the part change business, and the part change detection information is that the part change is normal.

[0079] Based on this, by determining different parts change monitoring information according to the comparison results, it is possible to determine whether there is any abnormality in the parts change business based on the parts change monitoring information, which makes it easier for administrators to manage the parts change business and ensure the normal operation of the business.

[0080] Furthermore, in order to avoid the situation where the administrator neglects the abnormality of the parts change business due to unclear data presentation, a visual display interface can be generated based on the target business plan sub-data and the business operation sub-data. Specifically, the method also includes: generating a visual display interface based on the target business plan sub-data and the business operation sub-data.

[0081] Among them, the visual display interface can be understood as an interface for displaying target business plan sub-data and business operation sub-data. Through the visual display interface, the target business plan sub-data and business operation sub-data can be clearly seen, which helps the administrator understand the implementation status of the parts change business.

[0082] In actual applications, the visual display interface can also include data comparison results, and display the current status of the parts change business to the administrator through different display controls, thereby realizing business operation visualization and facilitating the administrator to manage the parts change business.

[0083] Furthermore, in order to facilitate the administrator to view and compare data based on a visual display interface, data can also be displayed through different data levels. Specifically, a visual display interface is generated according to the target business plan sub-data and the business operation sub-data, including: determining a preset data level, layering the target business plan sub-data and the business operation sub-data according to the preset data level to obtain layered data; visualizing the layered data to generate a visual display interface.

[0084] The preset data level can be understood as the data level set in advance. Through the preset data level, the target business plan sub-data and business operation sub-data can be layered to obtain layered data. Layered data can be understood as data that has been layered according to the preset data level. The layered data is visualized to generate a visualization display interface, and the administrator can view data from different hierarchical dimensions.

[0085] In practical applications, by displaying data in layers, we can achieve multi-level data coordination and display the status distribution of changed data in multiple dimensions, making the data more transparent and enabling data-driven business decisions.

[0086] In a specific embodiment of the present specification, a preset data hierarchy is determined, and the preset data hierarchy is "1: SOP, 2: release, 3: Part Type, 4: Change Context". The target business plan sub-data and business operation sub-data are hierarchically divided according to the preset data hierarchy to obtain hierarchical data, and the hierarchical data is visualized to generate a visual display interface containing hierarchical display data.

[0087] Based on this, the data can be displayed in multiple dimensions by displaying it in layers, which helps administrators observe the status distribution of the data.

[0088] Furthermore, in the process of generating a visualization display interface, data can also be compared through different monitoring dimensions, and the display form of the monitoring controls can be adjusted in the visualization display interface. The specific method also includes: determining the monitoring data of the target monitoring dimension in the visualization display interface; adjusting the display form of the monitoring controls in the visualization display interface according to the monitoring data.

[0089] Among them, the target monitoring dimension can be understood as the determined monitoring dimension, the monitoring dimension can be understood as the dimension of monitoring data from different monitoring states, and the monitoring dimension includes the monitoring dimension before business operation, namely Pre-ECPvalidation, the verification monitoring dimension under business implementation, namely NRCL validation, and the monitoring dimension during business operation, namely Dating validation.

[0090] In actual applications, after determining the monitoring dimension, you can determine whether there is an abnormality in the part change business according to the monitoring data of the monitoring dimension, and display it in the form of monitoring controls in the visualization interface based on the determination result. The monitoring control can be understood as the display control in the visualization display interface. The display control allows the administrator to clearly observe the operation of the business. Figure 3 , Figure 3It is a display diagram of a visual display interface of a data processing method provided in an embodiment of this specification, which includes multi-dimensional hierarchical display data, such as SOP, release, PartType, and Change Context.

[0091] In a specific embodiment of the present specification, when the target monitoring dimension is Pre-ECP validation, the monitoring data corresponding to the target monitoring dimension is determined, and the [PreECP Result] status is checked. When [PreECP Result] = NOK, it means that the ECP pre-process has not passed and the formal ECP process cannot be executed. At this time, the display form of the monitoring control is adjusted to an alarm red light; in other cases, the display form of the monitoring control is a green light.

[0092] In another specific embodiment of the present specification, when the target monitoring dimension is NRCL validation, the monitoring data corresponding to the target monitoring dimension is determined, and the [NRCL State] status is checked. When [NRCL State] = KONZEPT / blank, it means that NRCL is empty or has no corresponding data. At this time, the display form of the monitoring control is adjusted to an alarm red light; in other cases, the display form of the monitoring control is a green light.

[0093] In another specific embodiment of the present specification, when the target monitoring dimension is Dating validation, the monitoring data corresponding to the target monitoring dimension is determined. When [Implementation Type] = HA, it means that a fixed switching date is set for the part switching time. At this time, it is necessary to check the [Run in] value of the material. [Run In] = [Start Interval] of the same release, which means that the part switching date meets the set switching time requirements. The display form of the monitoring control is adjusted to a green light. In other cases, it is an alarm red light. When [Implementation Type] = IN, it means that a fixed switching time period is set for the part switching time. Check the [Run In] value of the material to see if the [Run in] date falls between the [Start Interval] and [Start Pulk] corresponding to the same release. If so, it means that the part switching time falls within the set switching time period. If it meets the set switching time requirements, the display form of the monitoring control is adjusted to a green light. If not, the display form of the monitoring control is adjusted to a red light.

[0094] A data processing method provided in the present specification includes obtaining a business plan table and a business operation table for an associated part change business, wherein the business plan table includes business plan data for the part change business, and the business operation table includes business operation data for the part change business; preprocessing the business plan data to obtain target business plan data, and selecting business operation sub-data from the business operation data according to a preset data selection strategy; screening target business plan sub-data from the target business plan data based on the business operation sub-data; comparing the target business plan sub-data and the business operation sub-data, and determining the part change monitoring information corresponding to the part change business according to the comparison result. By obtaining the business plan table and business operation table of the part change business, pre-processing the business plan data in the business plan table to obtain the target business plan data, selecting the business operation sub-data in the business operation data according to the preset data selection strategy, and then filtering out the target business plan sub-data from the target business plan data based on the business operation sub-data, the subsequent comparison data can be obtained more accurately through business logic and data selection strategy, and the accuracy and timeliness of data monitoring and analysis can be improved. By comparing the target business plan sub-data and the business operation sub-data, the part change monitoring information corresponding to the part change business is determined, which solves the problems of time waste and inaccurate comparison results caused by manual data comparison, so that abnormal situations in the part change business can be efficiently found to ensure the normal implementation of the part change business.

[0095] The following combination Figure 4 , taking the application of the data processing method provided in this specification in the parts change business as an example, the data processing method is further explained. Figure 4 A processing flow chart of a part change service method provided in an embodiment of the present specification is shown, which specifically includes the following steps.

[0096] Step 402: Obtain a business plan table and a business operation table for the associated parts change business.

[0097] In one feasible method, an initial business plan table and a business operation table of the associated part change business are obtained, and the data identifiers to be removed are determined in the initial business plan table, the blank items corresponding to the data identifiers to be removed are determined, and the row data corresponding to the blank items are deleted in the business plan data to obtain the business plan table.

[0098] Step 404: pre-process the business plan data to obtain target business plan data.

[0099] In one feasible method, the data identifier to be deleted and the data identifier to be deleted [mat.No.old]+[mat.No.new]+[Release]+[Plant]+[Derivative]+[Changecontext], as well as the data to be deleted corresponding to the data identifier to be deleted are determined in the business plan data. If there is data duplication in the data to be deleted, the duplicate data to be deleted is deleted in the business plan data to obtain the target business plan data.

[0100] Step 406: Select business operation sub-data from the business operation data according to a preset data selection strategy.

[0101] In one feasible manner, the target time information is obtained as 2022-01-01 according to the preset data selection strategy, and the filtering time information is determined based on the target time information, including the starting time point 2022-01-03 and the ending time point 2022-02.02, and the business operation sub-data is selected from the business operation data based on the filtering time information.

[0102] Step 408: Determine a screening data identifier in the business operation sub-data, and screen the target business plan sub-data in the target business plan data based on the screening data identifier.

[0103] Step 410: Compare the target business plan sub-data and the business operation sub-data.

[0104] Step 412: Determine the part change monitoring information corresponding to the part change business according to the comparison result.

[0105] In one feasible manner, when the comparison result is inconsistent, the part change monitoring information corresponding to the part change business is determined to be an abnormal part change; when the comparison result is consistent, the part change monitoring information corresponding to the part change business is determined to be a normal part change.

[0106] Step 414: Generate a visual display interface according to the target business plan sub-data and the business operation sub-data.

[0107] In one achievable manner, a preset data hierarchy is determined, and the target business plan sub-data and the business operation sub-data are hierarchically processed according to the preset data hierarchy to obtain hierarchical data; the hierarchical data is visualized to generate a visualization display interface. The monitoring data of the target monitoring dimension is determined in the visualization display interface; and the display form of the monitoring control in the visualization display interface is adjusted according to the monitoring data.

[0108] A data processing method provided in this specification obtains a business plan table and a business operation table of a part change business, pre-processes the business plan data in the business plan table, obtains target business plan data, selects business operation sub-data from the business operation data according to a preset data selection strategy, and then filters out target business plan sub-data from the target business plan data based on the business operation sub-data, obtains data for subsequent comparison more accurately through business logic and data selection strategy, improves the accuracy and timeliness of data monitoring and analysis, determines the part change monitoring information corresponding to the part change business by comparing the target business plan sub-data with the business operation sub-data, solves the problem of time waste and inaccurate comparison results caused by manual data comparison, and can efficiently find out abnormal situations in the part change business and ensure the normal implementation of the part change business.

[0109] Corresponding to the above method embodiment, this specification also provides a data processing device embodiment, Figure 5 FIG. 1 is a schematic diagram showing the structure of a data processing device provided by an embodiment of the present specification. Figure 5 As shown, the device comprises:

[0110] An acquisition module 502 is configured to acquire a business plan table and a business operation table of an associated part change business, wherein the business plan table includes business plan data of the part change business, and the business operation table includes business operation data of the part change business;

[0111] A preprocessing module 504 is configured to preprocess the business plan data to obtain target business plan data, and select business operation sub-data from the business operation data according to a preset data selection strategy;

[0112] A screening module 506 is configured to screen target business plan sub-data in the target business plan data based on the business operation sub-data;

[0113] The comparison module 508 is configured to compare the target business plan sub-data with the business operation sub-data, and determine the part change monitoring information corresponding to the part change business according to the comparison result.

[0114] Optionally, the acquisition module 502 is further configured to: obtain an initial business plan table for the associated part change business, and determine the data identifiers to be removed in the initial business plan table; determine the blank items corresponding to the data identifiers to be removed, delete the row data corresponding to the blank items in the business plan data, and obtain the business plan table.

[0115] Optionally, the preprocessing module 504 is further configured to: determine the data identifier to be deleted and the data to be deleted corresponding to the data identifier to be deleted in the business plan data; if there is data duplication in the data to be deleted, delete the duplicate data of the data to be deleted in the business plan data to obtain the target business plan data.

[0116] Optionally, the preprocessing module 504 is further configured to: obtain target time information according to a preset data selection strategy, and determine screening time information based on the target time information; and select business operation sub-data from the business operation data based on the screening time information.

[0117] Optionally, the screening module 506 is further configured to: determine a screening data identifier in the business operation sub-data; and screen target business plan sub-data in the target business plan data based on the screening data identifier.

[0118] Optionally, the comparison module 508 is further configured to: determine a comparison identifier, and based on the comparison identifier, determine first comparison sub-data in the target business plan sub-data, and determine second comparison sub-data in the business operation sub-data; and compare the first comparison sub-data with the second comparison sub-data.

[0119] Optionally, the comparison module 508 is further configured to: when the comparison result is inconsistent, determine that the part change monitoring information corresponding to the part change business is an abnormal part change; when the comparison result is consistent, determine that the part change monitoring information corresponding to the part change business is a normal part change.

[0120] Optionally, the device further includes a display module configured to generate a visual display interface according to the target business plan sub-data and the business operation sub-data.

[0121] Optionally, the display module is further configured to: determine a preset data hierarchy, perform hierarchical processing on the target business plan sub-data and the business operation sub-data according to the preset data hierarchy to obtain hierarchical data; and perform visualization processing on the hierarchical data to generate a visualization display interface.

[0122] Optionally, the display module is further configured to: determine monitoring data of a target monitoring dimension in the visual display interface; and adjust a display format of monitoring controls in the visual display interface according to the monitoring data.

[0123] A data processing device provided in the present specification includes an acquisition module, which is configured to acquire a business plan table and a business operation table of an associated part change business, wherein the business plan table includes business plan data of the part change business, and the business operation table includes business operation data of the part change business; a preprocessing module, which is configured to preprocess the business plan data, obtain target business plan data, and select business operation sub-data from the business operation data according to a preset data selection strategy; a screening module, which is configured to screen target business plan sub-data from the target business plan data based on the business operation sub-data; and a comparison module, which is configured to compare the target business plan sub-data with the business operation sub-data, and determine the part change monitoring information corresponding to the part change business according to the comparison result. By obtaining the business plan table and business operation table of the part change business, pre-processing the business plan data in the business plan table to obtain the target business plan data, selecting the business operation sub-data in the business operation data according to the preset data selection strategy, and then filtering out the target business plan sub-data from the target business plan data based on the business operation sub-data, the subsequent comparison data can be obtained more accurately through business logic and data selection strategy, and the accuracy and timeliness of data monitoring and analysis can be improved. By comparing the target business plan sub-data and the business operation sub-data, the part change monitoring information corresponding to the part change business is determined, which solves the problems of time waste and inaccurate comparison results caused by manual data comparison, so that abnormal situations in the part change business can be efficiently found to ensure the normal implementation of the part change business.

[0124] The above is a schematic scheme of a data processing device of this embodiment. It should be noted that the technical scheme of the data processing device and the technical scheme of the above data processing method belong to the same concept, and the details of the technical scheme of the data processing device that are not described in detail can be referred to the description of the technical scheme of the above data processing method.

[0125] Figure 6 The block diagram of a computing device 600 according to an embodiment of the present specification is shown. The components of the computing device 600 include but are not limited to a memory 610 and a processor 620. The processor 620 is connected to the memory 610 via a bus 630, and the database 650 is used to store data.

[0126] The computing device 600 also includes an access device 640 that enables the computing device 600 to communicate via one or more networks 660. Examples of these networks include a public switched telephone network (PSTN), a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or a combination of communication networks such as the Internet. The access device 640 may include one or more of any type of network interface (e.g., a network interface card (NIC)) of wired or wireless, such as an IEEE 802.11 wireless local area network (WLAN) wireless interface, a world-wide interoperability for microwave access (Wi-MAX) interface, an Ethernet interface, a universal serial bus (USB) interface, a cellular network interface, a Bluetooth interface, and a near field communication (NFC).

[0127] In one embodiment of the present specification, the above components of the computing device 600 and Figure 6 Other components not shown in the figure may also be connected to each other, for example, via a bus. It should be understood that Figure 6 The computing device structure block diagram shown is only for the purpose of illustration, and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0128] The computing device 600 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable computing device (e.g., a smart watch, smart glasses, etc.), or other types of mobile devices, or a stationary computing device such as a desktop computer or a personal computer (PC). The computing device 600 may also be a mobile or stationary server.

[0129] The processor 620 is used to execute the following computer executable instructions, which implement the steps of the above data processing method when executed by the processor.

[0130] The above is a schematic scheme of a computing device of this embodiment. It should be noted that the technical scheme of the computing device and the technical scheme of the above data processing method belong to the same concept, and the details not described in detail in the technical scheme of the computing device can be referred to the description of the technical scheme of the above data processing method.

[0131] An embodiment of the present specification further provides a computer-readable storage medium storing computer-executable instructions, which can implement the steps of the above-mentioned data processing method when executed by a processor.

[0132] The above is a schematic scheme of a computer-readable storage medium of this embodiment. It should be noted that the technical scheme of the storage medium and the technical scheme of the above data processing method belong to the same concept, and the details not described in detail in the technical scheme of the storage medium can be referred to the description of the technical scheme of the above data processing method.

[0133] An embodiment of the present specification further provides a computer program, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the above-mentioned data processing method.

[0134] The above is a schematic scheme of a computer program of this embodiment. It should be noted that the technical scheme of the computer program and the technical scheme of the above data processing method belong to the same concept, and the details not described in detail in the technical scheme of the computer program can be referred to the description of the technical scheme of the above data processing method.

[0135] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0136] The computer instructions include computer program codes, which may be in source code form, object code form, executable files or some intermediate forms, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of patent practice. For example, in some regions, according to patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0137] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of this specification are not limited by the order of the actions described, because according to the embodiments of this specification, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of this specification.

[0138] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0139] The preferred embodiments of this specification disclosed above are only used to help explain this specification. The optional embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of the embodiments of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of this specification, so that technicians in the relevant technical field can well understand and use this specification. This specification is only limited by the claims and their full scope and equivalents.

Claims

1. A data processing method, characterized in that: include: Acquire a business plan table and a business operation table for the associated parts change business, wherein the business plan table includes the business plan data for the parts change business, and the business operation table includes the business operation data for the parts change business; Preprocessing the business plan data to obtain target business plan data, and selecting business operation sub-data from the business operation data according to a preset data selection strategy; Filtering target business plan sub-data from the target business plan data based on the business operation sub-data; The target business plan sub-data and the business operation sub-data are compared, and the part change monitoring information corresponding to the part change business is determined according to the comparison result.

2. The method according to claim 1, characterized in that Obtain the business plan for the associated parts change business, including: Obtaining an initial business plan table for the associated parts change business, and determining a data identifier to be removed in the initial business plan table; Determine a blank item corresponding to the data identifier to be removed, delete the row data corresponding to the blank item in the business plan data, and obtain a business plan table.

3. The method according to claim 1, characterized in that Preprocessing the business plan data to obtain target business plan data includes: Determining, in the business plan data, a to-be-deleted data identifier and the to-be-deleted data corresponding to the to-be-deleted data identifier; In the case where there are duplicate data in the data to be deleted, the duplicate data of the data to be deleted are deleted from the business plan data to obtain target business plan data.

4. The method according to claim 1, characterized in that Selecting business operation sub-data from the business operation data according to a preset data selection strategy includes: Acquire target time information according to a preset data selection strategy, and determine screening time information based on the target time information; Based on the screening time information, business operation sub-data is selected from the business operation data.

5. The method according to claim 1, characterized in that Filtering target business plan sub-data from the target business plan data based on the business operation sub-data includes: Determining a screening data identifier in the business operation sub-data; The target business plan sub-data is filtered in the target business plan data based on the filtering data identifier.

6. The method according to claim 1, characterized in that Comparing the target business plan sub-data with the business operation sub-data includes: Determine a comparison identifier, and determine first comparison sub-data in the target business plan sub-data based on the comparison identifier, and determine second comparison sub-data in the business operation sub-data; The first comparison sub-data and the second comparison sub-data are compared.

7. The method according to claim 1, characterized in that The part change monitoring information corresponding to the part change business is determined according to the comparison result, including: When the comparison result is inconsistent, determining that the part change monitoring information corresponding to the part change business is a part change abnormality; When the comparison result is consistent, the part change monitoring information corresponding to the part change business is determined to be normal.

8. The method according to any one of claims 1 to 7, characterized in that: The method further comprises: A visual display interface is generated according to the target business plan sub-data and the business operation sub-data.

9. The method according to claim 8, characterized in that Generate a visual display interface based on the target business plan sub-data and the business operation sub-data, including: Determine a preset data hierarchy, and perform hierarchical processing on the target business plan sub-data and the business operation sub-data according to the preset data hierarchy to obtain hierarchical data; The layered data is visualized to generate a visualization display interface.

10. The method according to claim 8, characterized in that The method further comprises: Determining monitoring data of a target monitoring dimension in the visual display interface; The display form of the monitoring controls in the visual display interface is adjusted according to the monitoring data.

11. A data processing device, characterized in that: include: An acquisition module is configured to acquire a business plan table and a business operation table of an associated part change business, wherein the business plan table includes business plan data of the part change business, and the business operation table includes business operation data of the part change business; A preprocessing module is configured to preprocess the business plan data to obtain target business plan data, and select business operation sub-data from the business operation data according to a preset data selection strategy; A screening module, configured to screen target business plan sub-data in the target business plan data based on the business operation sub-data; The comparison module is configured to compare the target business plan sub-data with the business operation sub-data, and determine the part change monitoring information corresponding to the part change business according to the comparison result.

12. A computing device comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method according to any one of claims 1 to 10 are implemented.

13. A computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by a processor, implement the steps of the method according to any one of claims 1 to 10.

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