Data processing method, device, equipment and computer storage medium

Abstract

The present application discloses a data processing method, device, equipment and computer storage medium. The method comprises: obtaining at least one first data and at least one second data in a preset format; comparing the first data and the second data according to a preset rule based on a mapping relationship between at least one first identifier and at least one second identifier, and obtaining a comparison result corresponding to each second data; and determining that the second data corresponding to the comparison result is correct when the comparison result meets a preset condition. The data processing method, device, equipment and computer storage medium provided by the present application can improve work efficiency, quickly determine whether the migrated data is correct, and greatly reduce the probability of errors in the comparison result.

Description

Technical Field

[0001] The present application belongs to the field of data processing technology, and in particular, relates to a data processing method, device, equipment and computer storage medium. Background Art

[0002] In recent years, my country's economy and technology are in a stage of rapid development. In all walks of life, in order to achieve rapid business development, informatization and digitalization construction have become the best choices. Therefore, the upgrade of information systems has become an important project for all enterprises. When the information system is upgraded, in order to meet business continuity, it is necessary to migrate data from the old system to the new system, that is, to perform data migration.

[0003] After completing the data migration from the old system to the new system, it is usually necessary to verify the accuracy of the data in the new system after the migration. In the prior art, the data in the old system and the data in the new system are generally compared manually to determine whether the data in the new system is accurate.

[0004] However, due to the huge amount of data involved and the fact that the dimensions of the data in the new system are usually different from those in the old system, it is extremely difficult to manually compare the data in the new and old systems. This not only leads to inefficient data verification, but is also prone to errors. Summary of the invention

[0005] The embodiments of the present application provide a data processing method, apparatus, device and computer storage medium, which can at least solve the problem that data verification in the prior art is inefficient and prone to errors.

[0006] In a first aspect, an embodiment of the present application provides a data processing method, the method comprising:

[0007] Acquire at least one first data and at least one second data in a preset format, wherein the first data is data in the first system, and the second data is data after the first data is migrated from the first system to the second system, the first data and the first identifier correspond one-to-one, and the second data and the second identifier correspond one-to-one;

[0008] According to a preset mapping relationship between at least one first identifier and at least one second identifier, the first data and the second data are compared according to a preset rule to obtain a comparison result corresponding to each second data;

[0009] When the comparison result satisfies the preset condition, it is determined that the second data corresponding to the comparison result is correct.

[0010] In a second aspect, an embodiment of the present application provides a data processing device, the device comprising:

[0011] A first acquisition module, used to acquire at least one first data and at least one second data in a preset format, wherein the first data is data in the first system, and the second data is data after the first data is migrated from the first system to the second system, and the first data and the first identifier have a one-to-one correspondence, and the second data and the second identifier have a one-to-one correspondence;

[0012] A comparison module, configured to compare the first data and the second data according to a preset rule based on a mapping relationship between at least one first identifier and at least one second identifier, to obtain a comparison result corresponding to each second data;

[0013] The first determination module is used to determine that the second data corresponding to the comparison result is correct when the comparison result meets a preset condition.

[0014] In a third aspect, an embodiment of the present application provides an electronic device, the device comprising: a processor and a memory storing computer program instructions;

[0015] When the processor executes the computer program instructions, the data processing method as shown in any one of the embodiments of the first aspect is implemented.

[0016] In a fourth aspect, an embodiment of the present application provides a computer storage medium having computer program instructions stored thereon, and when the computer program instructions are executed by a processor, the data processing method shown in any one of the embodiments of the first aspect is implemented.

[0017] In a fifth aspect, an embodiment of the present application provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the data processing method shown in any one of the embodiments of the first aspect.

[0018] The data processing method, apparatus, device and computer storage medium of the embodiments of the present application can obtain at least one first data and at least one second data in a preset format, and then compare the first data and the second data according to preset rules based on the mapping relationship between at least one preset first identifier and at least one second identifier to obtain a comparison result corresponding to each second data. Then, if the comparison result meets the preset conditions, it can be determined that the second data corresponding to the comparison result is correct. In this way, it is possible to automatically determine whether the second data is correct without manually comparing the first data and the second data to determine whether the second data is correct. Therefore, work efficiency can be improved, whether the migrated data is correct can be quickly determined, and the probability of errors in the comparison results can be greatly reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] Figure 1 is a flow chart of a data processing method provided by an embodiment of the present application;

[0021] Figure 2 It is a process schematic diagram of a data processing method provided by an embodiment of the present application;

[0022] Figure 3 is a structural schematic diagram of a data processing device provided by an embodiment of the present application;

[0023] Figure 4 It is a structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0024] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0025] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0026] Figure 1 A flow chart of a data processing method provided by an embodiment of the present application is shown. It should be noted that the data processing method can be applied to a data processing device, such as Figure 1 As shown, the data processing method may include the following steps:

[0027] S110, acquiring at least one first data and at least one second data in a preset format;

[0028] S120, comparing the first data and the second data according to a preset rule according to a preset mapping relationship between at least one first identifier and at least one second identifier, to obtain a comparison result corresponding to each second data;

[0029] S130: When the comparison result satisfies a preset condition, determine that the second data corresponding to the comparison result is correct.

[0030] Therefore, by obtaining at least one first data and at least one second data in a preset format, and then comparing the first data and the second data according to preset rules based on the mapping relationship between at least one preset first identifier and at least one second identifier, a comparison result corresponding to each second data is obtained, and then, if the comparison result meets the preset conditions, it can be determined that the second data corresponding to the comparison result is correct. In this way, it is possible to automatically determine whether the second data is correct without manually comparing the first data and the second data to determine whether the second data is correct. Therefore, work efficiency can be improved, whether the migrated data is correct can be quickly determined, and the probability of errors in the comparison results can be greatly reduced.

[0031] In S110, the first data may be data in the first system, and the second data may be data after the first data is migrated from the first system to the second system. The first data may include a first identifier, and the second data may include a second identifier. The first data may correspond to the first identifier one-to-one, and the second data may correspond to the second identifier one-to-one.

[0032] In some implementations, in order to facilitate comparison of data in the first system and the second system, before S110, the method may further include:

[0033] Acquire first original data and second original data;

[0034] According to a preset format, the first original data and the second original data are standardized to obtain first data and second data.

[0035] Here, the first original data can be obtained from the first system, and the second original data can be obtained from the second system. The first original data and the second original data can be standardized respectively, so that the first original data and the second original data can be converted into data of the same format, that is, the first data and the second data.

[0036] In some examples, after migrating the general ledger balance data from the old system to the new system, in the process of verifying the accuracy of the migrated data, the preset format may be: institution number, account number, general ledger source number, currency, balance. The old general ledger balance data, i.e., the first original data, may be obtained from the old system, i.e., the first system, and the new general ledger balance data, i.e., the second original data, may be obtained from the new system, i.e., the second system. Then, the old general ledger balance data and the new general ledger balance data may be standardized according to the preset format to obtain an old general ledger balance file and a new general ledger balance file. The old general ledger balance file includes at least one old general ledger balance record, i.e., the first data, and the new general ledger balance file includes at least one new general ledger balance record, i.e., the second data.

[0037] Thus, through the above process, the data before migration and the data after migration are converted into the same format, which facilitates data comparison.

[0038] In S120, the corresponding relationship between the first data and the second data can be determined according to the mapping relationship between at least one preset first identifier and at least one second identifier, and then the second data and the first data corresponding to the second data are compared according to the preset rule to obtain the comparison result corresponding to each second data. The preset rule can be a way to compare the second data with the first data.

[0039] In some implementations, since the dimensions of the first data and the second data may be different, in order to compare data of different dimensions, S120 may specifically include:

[0040] According to a preset mapping relationship between at least one first identifier and at least one second identifier, grouping at least one first data and at least one second data to obtain at least one comparison group;

[0041] According to preset rules, the first data and the second data included in each comparison group are compared respectively to obtain a comparison result.

[0042] Here, the first data and the second data may be grouped according to the mapping relationship to obtain a comparison group, which may include at least one first data and second data corresponding to at least one second identifier that has a mapping relationship with a first identifier of the at least one first data.

[0043] In some implementations, the above mapping relationship may include at least one of the following:

[0044] A mapping relationship between a first identifier and a second identifier;

[0045] A mapping relationship between a first identifier and multiple second identifiers;

[0046] A mapping relationship between multiple first identifiers and one second identifier.

[0047] Here, according to the above mapping relationship, the data included in a comparison group can be one of the following three situations:

[0048] a first data and a second data;

[0049] a first data and a plurality of second data;

[0050] A plurality of first data and a second data.

[0051] The preset rule may be a specific method for comparing the first data and the second data included in each comparison group. The preset rule may include at least one sub-rule, and the sub-rules corresponding to different comparison groups may be different. For example, the first comparison group includes a first data and a second data, and the sub-rule corresponding to the first comparison group may be to compare the data of each dimension of the first data with the data of each dimension of the second data respectively; the second comparison group includes a first data and multiple second data, and the sub-rule corresponding to the second comparison group may be to add the data of the same dimension in the multiple second data to obtain the data sum of each dimension of the multiple second data, and then compare the data sum of each dimension of the multiple second data with the data of each dimension of the first data; the third comparison group includes multiple first data and a second data, and the sub-rule corresponding to the third comparison group may be to add the data of the same dimension in the multiple first data to obtain the data sum of each dimension of the multiple first data, and then compare the data sum of each dimension of the multiple first data with the data of each dimension of the second data.

[0052] According to the above preset rules, one first data can be compared with one second data, one first data can be compared with multiple second data, or multiple first data can be compared with one second data.

[0053] In some examples, since the first original data in the old system only has one dimension of "total balance" regarding balance, while the second original data in the new system has three dimensions of "type one balance", "type two balance" and "type three balance", the sum of "type one balance", "type two balance" and "type three balance" is the total balance. After standardization according to the preset format of "institution number, account number, general ledger source number, currency, balance", one old general ledger balance record and three new general ledger balance records will be obtained.

[0054] Among them, the old general ledger balance record is "XXX, MM, PPPP, K, 10000", and the new general ledger balance records are "XXX, FF, PPPP, K, 2000", "XXX, GG, PPPP, K, 3000" and "XXX, HH, PPPP, K, 5000". Here, the account number can be used as an identifier, so the identifier of the old general ledger balance record, that is, the first identifier, is "MM", and the identifiers of the three new general ledger balance records, that is, the second identifiers, are "FF", "GG" and "HH". The mapping relationship between "MM" and "FF", the mapping relationship between "MM" and "GG", and the mapping relationship between "MM" and "HH" can be pre-set. According to the mapping relationship, this old general ledger balance record and the three new general ledger balance records can be used as a comparison group. The preset rule may be: respectively compare the "institution number, account number, general ledger source number, currency" in the old general ledger balance record with the new general ledger balance record, and compare the "balance" in the old general ledger balance record with the sum of the three "balances" in the new general ledger balance record. According to the preset rule, "XXX, MM, PPPP, K" in the old general ledger balance record is compared with "XXX, FF, PPPP, K", "XXX, GG, PPPP, K" and "XXX, HH, PPPP, K" in the three new general ledger balance records respectively, and "10000" in the old general ledger balance record is compared with the sum of "2000", "3000" and "5000" in the three new general ledger balance records. The comparison results corresponding to the three new general ledger balance records are: "XXX, FF, (MM), PPPP, K, 2000, (10000), no difference", "XXX, GG, (MM), PPPP, K, 3000, (10000), no difference" and "XXX, MM, HH, (MM), PPPP, K, 5000, (10000), no difference".

[0055] In this way, by grouping the first data and the second data according to the mapping relationship, and then comparing the first data and the second data included in each comparison group according to a preset rule, the difficulty in comparing data of different dimensions is solved.

[0056] In some implementations, in order to determine whether there is erroneous data in the migrated data, after S120, the method may further include:

[0057] When the comparison result does not satisfy the preset condition, it is determined that an error exists in the second data corresponding to the comparison result.

[0058] Here, the preset condition may include at least one sub-condition, and the sub-conditions corresponding to the comparison results of different comparison groups may be different. For example, the first comparison group includes a first data and a second data, and each dimension of the two is the same. The sub-condition corresponding to the comparison result of the first comparison group may be that the data of each dimension of the first data is consistent with the data of each dimension of the second data; the second comparison group includes a first data and multiple second data, and the sub-condition corresponding to the comparison result of the second comparison group may be that the data of each dimension of the multiple second data is consistent with the data of each dimension of the first data; the third comparison group includes multiple first data and one second data, and the sub-condition corresponding to the comparison result of the third comparison group may be that the data of each dimension of the multiple first data is consistent with the data of each dimension of the second data. If the comparison result does not meet the preset condition, it can be determined that there is an error in the second data corresponding to the comparison result.

[0059] In some examples, since the dimension of the balance in the first original data in the old system is only "total balance", and the dimension of the balance in the second original data in the new system is divided into three dimensions: "type one balance", "type two balance" and "type three balance", the sum of "type one balance", "type two balance" and "type three balance" is the total balance. After standardization according to the preset format of "institution number, account number, general ledger source number, currency, balance", one old general ledger balance record and three new general ledger balance records will be obtained. According to the preset mapping relationship, the one old general ledger balance record and the three new general ledger balance records can be used as a comparison group, wherein the old general ledger balance record is "XXX, MM, PPPP, K, 10000", and the new general ledger balance records are "XXX, FF, PPPP, K, 2000", "XXX, GG, PPPP, K, 3000" and "XXX, HH, PPPP, K, 4000" respectively. According to the preset rule, "XXX, MM, PPPP, K" in the old general ledger balance record is compared with "XXX, FF, PPPP, K", "XXX, GG, PPPP, K" and "XXX, HH, PPPP, K" in the three new general ledger balance records respectively, and "10000" in the old general ledger balance record is compared with the sum of "2000", "3000" and "4000" in the three new general ledger balance records. The comparison results corresponding to the three new general ledger balance records are: "XXX, FF, (MM), PPPP, K, 2000, (10000), there are differences", "XXX, GG, (MM), PPPP, K, 3000, (10000), there are differences" and "XXX, MM, HH, (MM), PPPP, K, 4000, (10000), there are differences". Here, the preset conditions can be: the institution number, general ledger source number, currency and other data of the old general ledger balance record and the three new general ledger balance records are consistent, the account number of the old general ledger balance record and the account number of the three new general ledger balance records are mapped, and the balance of the old general ledger balance record and the sum of the balances of the three new general ledger balance records are equal. Since the institution number, general ledger source number, currency and other data of the old general ledger balance record and the three new general ledger balance records are all "XXX, PPPP, K", they are consistent, and the account number "MM" of the old general ledger balance record and the account numbers "FF", "GG", and "HH" of the three new general ledger balance records are mapped, the balance "10000" of the old general ledger balance record and the sum of the balances "2000", "3000", and "4000" of the three new general ledger balance records are not equal. Therefore, the comparison result does not meet the preset conditions, and there are erroneous data in the three new general ledger balance records.

[0060] Thus, through the above process, it can be determined that there is erroneous data in the migrated data.

[0061] In some implementations, in order to facilitate the user to view the comparison results, after S120, the method may further include:

[0062] Generate a comparison report based on the comparison results.

[0063] Here, the comparison report may include all or part of the first data and the second data, and may also include a comparison conclusion. The comparison conclusion may be a difference or no difference, and of course may be other conclusions, which are not limited here.

[0064] In some examples, the comparison results corresponding to the three new general ledger balance records in comparison group 1 may be "XXX, FF, (MM), PPPP, K, 2000, (10000), there are differences", "XXX, GG, (MM), PPPP, K, 3000, (10000), there are differences", and "XXX, HH, (MM), PPPP, K, 4000, (10000), there are differences". Since the dimensions of the comparison report may include: institution number, account number (new), account number (old), account group, general ledger source number, currency, balance (new), balance (old), and whether there is a difference. Therefore, the comparison report generated according to the comparison result may be shown in Table 1. Here, the old general ledger balance record and the new general ledger balance record are both identified by the account number, and comparison group 1 is obtained by grouping according to the mapping relationship between the account numbers. Therefore, the comparison group can be called an account group here.

[0065] Table 1-Comparison Report

[0066]

[0067] In this way, the comparison report generated through the above process brings convenience to the user to view the comparison results.

[0068] In some embodiments, in order to find the source of erroneous data when there is erroneous data in the second data, so as to analyze the cause of the error and correct the erroneous data, the above-mentioned comparison report may include data source information of the second data corresponding to the comparison report.

[0069] Here, the data source information is information indicating the source of the second data, and the data source information can be used to determine the source of the second data.

[0070] In some examples, the data source information may be an institution number and a general ledger source number. The source institution of the new general ledger balance record may be determined based on the institution number, and the business system of the new general ledger balance record may be determined based on the general ledger source number. If there is an error in the new general ledger balance record, and the institution number included in the comparison report corresponding to the new general ledger balance record is "XXX" and the general ledger source number is "PPPP", then the comparison report may be sent to the business system numbered "PPPP" in the institution numbered "XXX" so that the person in charge of the business can analyze the cause of the error and make corrections.

[0071] In this way, the comparison report includes the data source information of the second data. When there is erroneous data in the second data, the source of the erroneous data can be found, which makes it convenient to analyze the cause of the error and correct the erroneous data.

[0072] Regarding S130, if the comparison result satisfies the above-mentioned preset condition, it can be determined that the second data corresponding to the comparison result is correct.

[0073] In some examples, since the dimension of the balance in the first original data in the old system is only "total balance", and the dimension of the balance in the second original data in the new system is divided into three dimensions: "first category balance", "second category balance" and "third category balance", the sum of "first category balance", "second category balance" and "third category balance" is the total balance. After standardization according to the preset format of "institution number, account number, general ledger source number, currency, balance", one old general ledger balance record and three new general ledger balance records will be obtained. According to the preset mapping relationship, the one old general ledger balance record and the three new general ledger balance records can be used as a comparison group, wherein the old general ledger balance record is "XXX, MM, PPPP, K, 10000", and the new general ledger balance records are "XXX, FF, PPPP, K, 2000", "XXX, GG, PPPP, K, 3000" and "XXX, HH, PPPP, K, 5000" respectively. According to the preset rule, "XXX, MM, PPPP, K" in the old general ledger balance record is compared with "XXX, FF, PPPP, K", "XXX, GG, PPPP, K" and "XXX, HH, PPPP, K" in the three new general ledger balance records respectively, and "10000" in the old general ledger balance record is compared with the sum of "2000", "3000" and "5000" in the three new general ledger balance records. The comparison results corresponding to the three new general ledger balance records are: "XXX, FF, (MM), PPPP, K, 2000, (10000), no difference", "XXX, GG, (MM), PPPP, K, 3000, (10000), no difference" and "XXX, MM, HH, (MM), PPPP, K, 5000, (10000), no difference". Here, the preset conditions can be: the institution number, general ledger source number, currency and other data of the old general ledger balance record and the three new general ledger balance records are consistent, the account number of the old general ledger balance record and the account number of the three new general ledger balance records are mapped, and the balance of the old general ledger balance record and the sum of the balances of the three new general ledger balance records are equal. Since the institution number, general ledger source number, currency and other data of the old general ledger balance record and the three new general ledger balance records are all "XXX, PPPP, K", they are consistent, the account number "MM" of the old general ledger balance record and the account numbers "FF", "GG", and "HH" of the three new general ledger balance records are mapped, and the balance "10000" of the old general ledger balance record and the sum of the balances "2000", "3000", and "5000" of the three new general ledger balance records are equal. Therefore, the comparison result meets the preset conditions, and the three new general ledger balance records are correct.

[0074] In order to better describe the whole solution, based on the above embodiment, a specific example is given, such as Figure 2As shown, in a specific example, a standard format, i.e., preset format 210, can be preset to convert the old and new general ledger balance data obtained from the old and new systems into preset format 210 to obtain old general ledger balance records 220 and new general ledger balance records 230. According to the mapping relationship 240 between the account number of the old general ledger balance record and the account number of the new general ledger balance record, the old general ledger balance record and the new general ledger balance record are used as a comparison group 250, i.e., account group A. The old and new general ledger balance records in the comparison group 250 are compared to obtain comparison results, and a comparison report 260 is generated.

[0075] Therefore, by obtaining at least one first data and at least one second data in a preset format, and then comparing the first data and the second data according to preset rules based on the mapping relationship between at least one preset first identifier and at least one second identifier, a comparison result corresponding to each second data is obtained, and then, if the comparison result meets the preset conditions, it can be determined that the second data corresponding to the comparison result is correct. In this way, it is possible to automatically determine whether the second data is correct without manually comparing the first data and the second data to determine whether the second data is correct. Therefore, work efficiency can be improved, whether the migrated data is correct can be quickly determined, and the probability of errors in the comparison results can be greatly reduced.

[0076] In addition, in the prior art, the migrated data is manually checked, and no standard methods and tools are formed, which makes it difficult to reuse between different projects. The data processing method provided in the embodiment of the present application is applied to a data processing device, which can be reused between different projects, thereby reducing costs.

[0077] Based on the same inventive concept, the present application embodiment also provides a data processing device. Figure 3 The data processing device provided in the embodiment of the present application is described in detail.

[0078] Figure 3 A schematic structural diagram of a data processing device provided by an embodiment of the present application is shown.

[0079] like Figure 3 As shown, the data processing device may include:

[0080] A first acquisition module 301 is used to acquire at least one first data and at least one second data in a preset format, where the first data is data in the first system, and the second data is data after the first data is migrated from the first system to the second system, where the first data and the first identifier have a one-to-one correspondence, and the second data and the second identifier have a one-to-one correspondence;

[0081] A comparison module 302 is used to compare the first data and the second data according to a preset mapping relationship between at least one first identifier and at least one second identifier and a preset rule to obtain a comparison result corresponding to each second data;

[0082] The first determination module 303 is used to determine whether the second data corresponding to the comparison result is correct when the comparison result meets a preset condition.

[0083] Therefore, by obtaining at least one first data and at least one second data in a preset format, and then comparing the first data and the second data according to preset rules based on the mapping relationship between at least one preset first identifier and at least one second identifier, a comparison result corresponding to each second data is obtained, and then, if the comparison result meets the preset conditions, it can be determined that the second data corresponding to the comparison result is correct. In this way, it is possible to automatically determine whether the second data is correct without manually comparing the first data and the second data to determine whether the second data is correct. Therefore, work efficiency can be improved, whether the migrated data is correct can be quickly determined, and the probability of errors in the comparison results can be greatly reduced.

[0084] In some implementations, in order to facilitate the comparison of data in the first system and the second system, the data processing device may further include:

[0085] A second acquisition module, used for acquiring first original data and second original data before acquiring at least one first data and at least one second data in a preset format;

[0086] The standardization module is used to perform standardization processing on the first original data and the second original data according to a preset format to obtain the first data and the second data.

[0087] In some implementations, since the dimensions of the first data and the second data may be different, in order to compare data of different dimensions, the comparison module 302 may specifically include:

[0088] a grouping submodule, configured to group at least one first data and at least one second data according to a preset mapping relationship between at least one first identifier and at least one second identifier, to obtain at least one comparison group, each comparison group including at least one first data and second data corresponding to at least one second identifier having a mapping relationship with the first identifier of the at least one first data;

[0089] The comparison submodule is used to compare the first data and the second data included in each comparison group according to a preset rule to obtain a comparison result.

[0090] In some implementations, the mapping relationship includes at least one of the following:

[0091] A mapping relationship between a first identifier and a second identifier;

[0092] A mapping relationship between a first identifier and multiple second identifiers;

[0093] A mapping relationship between multiple first identifiers and one second identifier.

[0094] In some implementations, in order to determine whether there is erroneous data in the migrated data, the data processing device may further include:

[0095] The second determination module is used to compare the first data and the second data according to a preset rule based on a mapping relationship between at least one first identifier and at least one second identifier, and after obtaining a comparison result corresponding to each second data, if the comparison result does not meet a preset condition, determine that there is an error in the second data corresponding to the comparison result.

[0096] In some embodiments, in order to facilitate users to view the comparison results, the data processing device may further include:

[0097] The report generation module is used to compare the first data and the second data according to the preset rules based on the mapping relationship between at least one first identifier and at least one second identifier, obtain the comparison result corresponding to each second data, and then generate a comparison report based on the comparison result.

[0098] In some embodiments, in order to find the source of erroneous data when there is erroneous data in the second data, so as to analyze the cause of the error and correct the erroneous data, the comparison report includes data source information of the second data corresponding to the comparison report.

[0099] Figure 4 A schematic structural diagram of an electronic device provided by an embodiment of the present application is shown.

[0100] like Figure 4 As shown, the electronic device 4 is a block diagram of an exemplary hardware architecture of an electronic device that can implement the data processing method and data processing device in the embodiments of the present application. The electronic device may refer to the electronic device in the embodiments of the present application.

[0101] The electronic device 4 may include a processor 401 and a memory 402 storing computer program instructions.

[0102] Specifically, the processor 401 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0103] The memory 402 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 402 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 402 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 402 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 402 is a non-volatile solid-state memory. In a specific embodiment, the memory 402 may include a read-only memory (ROM), a random access memory (RAM), a disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. Therefore, typically, the memory 402 includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of the present disclosure.

[0104] The processor 401 implements any one of the data processing methods in the above embodiments by reading and executing computer program instructions stored in the memory 402 .

[0105] In one example, the electronic device may further include a communication interface 403 and a bus 404. Figure 4 As shown, the processor 401, the memory 402, and the communication interface 403 are connected via a bus 404 and communicate with each other.

[0106] The communication interface 403 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0107] Bus 404 includes hardware, software or both, and the parts of electronic equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 404 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the application considers any suitable bus or interconnection.

[0108] The electronic device can execute the data processing method in the embodiment of the present application, thereby realizing the combination Figures 1 to 3 The data processing method and device described.

[0109] In addition, in combination with the data processing method in the above embodiments, the present application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any one of the data processing methods in the above embodiments is implemented.

[0110] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0111] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0112] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0113] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0114] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A data processing method, characterized in that: include: Acquire at least one first data and at least one second data in a preset format, wherein the first data is data in a first system, and the second data is data after the first data is migrated from the first system to a second system, and the first data and the first identifier correspond one-to-one, and the second data and the second identifier correspond one-to-one; According to a preset mapping relationship between at least one first identifier and at least one second identifier, the first data and the second data are compared according to a preset rule to obtain a comparison result corresponding to each second data; When the comparison result satisfies a preset condition, determining that the second data corresponding to the comparison result is correct; The comparing the first data and the second data according to a preset rule based on a mapping relationship between at least one first identifier and at least one second identifier to obtain a comparison result corresponding to each second data specifically includes: According to a preset mapping relationship between at least one first identifier and at least one second identifier, the at least one first data and the at least one second data are grouped to obtain at least one comparison group, each comparison group including at least one first data and second data corresponding to at least one second identifier that has a mapping relationship with the first identifier of the at least one first data; According to a preset rule, the first data and the second data included in each comparison group are compared respectively to obtain the comparison result.

2. The method according to claim 1, characterized in that Before acquiring at least one first data and at least one second data in a preset format, the method further includes: Acquire first original data and second original data; According to the preset format, the first original data and the second original data are respectively standardized to obtain the first data and the second data.

3. The method according to claim 1, characterized in that The mapping relationship includes at least one of the following: a mapping relationship between a first identifier and a second identifier; a mapping relationship between one first identifier and multiple second identifiers; A mapping relationship between multiple first identifiers and one second identifier.

4. The method according to claim 1, characterized in that After comparing the first data and the second data according to a preset rule based on the mapping relationship between the at least one first identifier and the at least one second identifier to obtain a comparison result corresponding to each second data, the method further includes: When the comparison result does not satisfy a preset condition, it is determined that an error exists in the second data corresponding to the comparison result.

5. The method according to claim 1, characterized in that After comparing the first data and the second data according to a preset rule based on the mapping relationship between the at least one first identifier and the at least one second identifier to obtain a comparison result corresponding to each second data, the method further includes: A comparison report is generated according to the comparison results.

6. The method according to claim 5, characterized in that The comparison report includes data source information of the second data corresponding to the comparison report.

7. A data processing device, characterized in that: The device comprises: A first acquisition module, used to acquire at least one first data and at least one second data in a preset format, wherein the first data is data in a first system, and the second data is data after the first data is migrated from the first system to a second system, and the first data and the first identifier have a one-to-one correspondence, and the second data and the second identifier have a one-to-one correspondence; A comparison module, configured to compare the first data and the second data according to a preset rule based on a mapping relationship between at least one first identifier and at least one second identifier, to obtain a comparison result corresponding to each second data; A first determination module, configured to determine, when the comparison result satisfies a preset condition, that the second data corresponding to the comparison result is correct; The comparison module specifically includes: a grouping submodule, configured to group the at least one first data and the at least one second data according to a preset mapping relationship between the at least one first identifier and the at least one second identifier, to obtain at least one comparison group, each comparison group including at least one first data and second data corresponding to at least one second identifier having a mapping relationship with the first identifier of the at least one first data; The comparison submodule is used to compare the first data and the second data included in each comparison group according to a preset rule to obtain the comparison result.

8. An electronic device, characterized in that: The device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the data processing method according to any one of claims 1 to 6 is implemented.

9. A computer storage medium, characterized in that The computer storage medium stores computer program instructions, and when the computer program instructions are executed by the processor, the data processing method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the data processing method according to any one of claims 1 to 6.

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