CN115965326A

CN115965326A - Data processing method, device, equipment and storage medium

Info

Publication number: CN115965326A
Application number: CN202111181713.9A
Authority: CN
Inventors: 毛聪; 王飞; 徐茂红; 李团结; 张婷; 刘双; 王福江; 翟金亭
Original assignee: China United Network Communications Group Co Ltd
Current assignee: China United Network Communications Group Co Ltd
Priority date: 2021-10-11
Filing date: 2021-10-11
Publication date: 2023-04-14

Abstract

The application provides a data processing method, a device, equipment and a storage medium, wherein in the scheme, a first data table to be processed is obtained, and the first data table to be processed comprises a plurality of data to be processed; auditing the data table to be processed according to a first auditing index set, wherein the first auditing index set comprises a plurality of auditing indexes with relevance; judging whether the first to-be-processed data which does not finish auditing exist in the first to-be-processed data table; if the first to-be-processed data exists in the first to-be-processed data table, auditing the first to-be-processed data by using a first auditing index, wherein the first auditing index is an auditing index other than the first auditing index set, so that the aim of auditing the data by adding a new auditing index is fulfilled when the original auditing index set can not audit the data.

Description

Data processing method, device, equipment and storage medium

Technical Field

The present application relates to the field of computers, and in particular, to a data processing method, apparatus, device, and storage medium.

Background

With the development of mobile communication technology, mobile communication services are more and more, and service functions of a mobile communication system are more and more complex, so that the accuracy of production data generated in the operation process of the mobile communication system needs to be ensured, and thus the production data needs to be audited.

In the prior art, when production data is audited, all production data is audited through an automatic auditing platform according to each auditing index of a plurality of different auditing indexes after the production data is completely generated, but because the production data is large in quantity and various, the auditing indexes in the prior art can only audit one part of the production data, but cannot audit the other part of the production data, so that the audit data is missed, and further the inaccuracy and the incompleteness of the auditing result are caused.

In summary, the technical solutions for auditing data in the prior art have the problems of inaccurate and incomplete auditing results.

Disclosure of Invention

The embodiment of the application provides a data processing method, a data processing device, data processing equipment and a storage medium, and aims to solve the problems of inaccurate and incomplete audit results in a technical scheme for auditing data in the prior art.

In a first aspect, an embodiment of the present application provides a data processing method, where the method includes: acquiring a first data table to be processed, wherein the first data table to be processed comprises a plurality of data to be processed; auditing the first to-be-processed data table according to a first auditing index set, wherein the first auditing index set comprises a plurality of auditing indexes with relevance; judging whether the first to-be-processed data which does not finish auditing exist in the first to-be-processed data table; if the first to-be-processed data exists in the first to-be-processed data table, auditing the first to-be-processed data by using a first auditing index, wherein the first auditing index is an auditing index outside the first auditing index set.

The technical scheme provided by the embodiment of the application can have the following beneficial effects: whether first to-be-processed data which are not subjected to audit exist in a first to-be-processed data table or not is judged, so that new first audit indexes are added to audit the first to-be-processed data, all the to-be-processed data can be guaranteed to be audited, more comprehensive audit on the data is realized, missing of the data is avoided, potential data abnormity can be found in the data production process after the first audit index set is perfected, the hysteresis of finding data abnormity is avoided, meanwhile, due to the fact that a plurality of audit indexes in the first audit index set have relevance, the accuracy of finding data abnormity can be improved, and the accuracy and the integrity of audit results are improved.

In a second aspect, an embodiment of the present application provides a data processing apparatus, where the apparatus includes various functional modules for implementing the method according to the first aspect or any one of the possible implementation manners, and any functional module may be implemented by software and/or hardware.

For example, the apparatus may include an obtaining module, a first processing module, a second processing module, and a determining module.

The device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a first data table to be processed, and the first data table to be processed comprises a plurality of data to be processed; the first processing module is used for auditing the first to-be-processed data table according to a first auditing index set, wherein the first auditing index set comprises a plurality of auditing indexes with relevance; the judging module is used for judging whether the first to-be-processed data which do not finish auditing exist in the first to-be-processed data table; and the second processing module is used for auditing the first data to be processed by using the first auditing index if the first data to be processed exists in the first data table to be processed, wherein the first auditing index is an auditing index out of the first auditing index set.

In a third aspect, an embodiment of the present application provides an electronic device, including: a processor, a memory, an interactive interface; the memory is used for storing executable instructions of the processor; wherein the processor is configured to perform the data processing method of the first aspect via execution of the executable instructions.

In a fourth aspect, the present application provides a readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the data processing method of the first aspect.

In a fifth aspect, the present application provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the computer program is used to implement the data processing method of the first aspect.

In the data processing method, the device, the equipment and the storage medium provided by the embodiment of the application, when the first to-be-processed data table or the first to-be-processed flow is audited by using the first audit index set, if the first to-be-processed data table still has the first to-be-processed data which is not audited or cannot be audited, a new first audit index is required to be added to audit the first to-be-processed data, or a new second audit index is added to audit the to-be-processed flow, so that after the first audit index or the second audit index is added to the first audit index set, the first audit index set can be completed, so that more comprehensive audit on the data is realized through the completed first audit index set, data omission is avoided, potential abnormality of the data can be found in the data production process after the first audit index set is completed, the data abnormality finding is avoided, and meanwhile, because a plurality of audit indexes in the first audit index set have correlation, the accuracy and the data integrity are improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and those skilled in the art can obtain other drawings without inventive labor.

Fig. 1 is a flowchart of a first embodiment of a data processing method according to an embodiment of the present application;

fig. 2 is a flowchart of a second embodiment of a data processing method according to the present application;

fig. 3 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application;

fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by persons skilled in the art based on the embodiments in the present application in light of the present disclosure, are within the scope of protection of the present application.

The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the above-described drawings (if any) are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be implemented in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

In the prior art provided in the background art, at least the following technical problems exist when the accuracy of data is ensured:

after all production data are generated, all production data are audited through the automatic auditing platform according to each auditing index of a plurality of different auditing indexes, but because the production data are huge in quantity and various, the auditing indexes in the prior art only can audit one part of the production data, but cannot audit the other part of the production data, so that the condition that the auditing data are missed is caused, and the inaccuracy and the incompleteness of the auditing result are further caused.

In order to solve the above problems, the present application provides a data processing method, in which an audit index set is preset, the audit index set includes a plurality of audit indexes, the data table to be processed is audited by using the audit index set, if unfinished data to be processed still exists in the data table to be processed after the data table to be processed is audited by using the audit index set, the audit indexes in the audit index set are not perfect, and at this time, the unfinished data to be processed existing in the data table to be processed needs to be audited by using a new audit index, so that the audit indexes in the audit index set are perfect, and the purpose of more accurate and comprehensive audit of the data to be processed in the data table to be processed is achieved. Meanwhile, the auditing index set can also audit the flow of the service used by the user, so that the accuracy of the flow is ensured. After the first audit index set is perfected, potential data abnormity can be found in the data production process, hysteresis of finding data abnormity is avoided, and meanwhile, the efficiency and accuracy of finding data abnormity can be improved due to the fact that a plurality of audit indexes in the first audit index set have relevance. The terms referred to in the present application are explained first below.

Indexes are as follows: a collection of information describing the meaning, type, length, precision, scope of application, etc. of the data.

Auditing: the method refers to the whole activity of checking the work flow and production data of specific services according to the checking specification, proposing an amendment suggestion after problems are found, processing by related service responsible personnel and tracking the processing process and results.

The audit indexes are as follows: the items are items for guiding the auditors to conduct daily inspection work in the audit matrix, and are specific audit results corresponding to key links or operations which are easy to cause problems in a specific business process.

The data processing method provided by the application has the core idea that the data sheet to be processed is audited by using the preset audit index set, when the data sheet to be processed with unfinished audit is found, new audit indexes are added for carrying out audit processing again, so that the audit index set is perfected, in the subsequent data production process, the data can be audited through the perfected audit index set, if the data with unfinished audit is found again, the new audit indexes are continuously added for carrying out audit again, so that the audit index set is perfected, potential data abnormity can be found in the subsequent data production process, the hysteresis for finding data abnormity is avoided, meanwhile, the abnormity appearing in the data to be processed is really explained as the abnormity, the auditing indexes in the first audit index set have relevance, if the data to be processed with a certain audit index in the first audit index set and the indexes having relevance with the first audit indexes are abnormal, the correct audit efficiency of the data processing can be ensured, and the completeness of the data can be improved.

In a possible implementation, the data processing method of the embodiment may be applied to an application scenario, in which the data processing method may be implemented by a data processing system, where the data processing system at least includes an audit matrix management module and an audit index collection module, where the audit matrix management module is configured to set a balance formula according to different dimensions and distribute audit index collection tasks, and the audit index collection module is configured to receive a newly added audit index by using the audit index collection tasks distributed by the audit matrix management module, so as to perfect an audit index set. The data processing system can also comprise a database, the database comprises a plurality of to-be-processed data tables and an audit index table, the to-be-processed data tables record production data in the process that users use the business system, all audit indexes are recorded in the audit index table, and when the audit index collecting module collects the newly-added audit indexes, the newly-added audit indexes are recorded in the audit index table, so that the audit index table is completed.

In the above scenario, after the first audit index set is perfected, potential data anomalies can be found in the data production process, thereby avoiding the hysteresis of finding data anomalies, and meanwhile, because a plurality of audit indexes in the first audit index set have relevance, if the data to be processed is audited through one audit index in the first audit index set and the audit index having relevance with the audit index in the first audit index set, the anomalies appearing in the data to be processed are real anomalies, and the workload of the rechecker can be reduced by the method, thereby improving the work efficiency of the rechecker, ensuring the accuracy of determining whether the data to be processed is anomalous, and realizing the improvement of the correctness and the integrity of the audit data in the audit index set.

Based on the above scenario, the data processing method is described in detail below by way of several exemplary embodiments.

Fig. 1 is a flowchart of a first embodiment of a data processing method provided in an embodiment of the present application, and as shown in fig. 1, the data processing method includes the following steps:

s101: and acquiring a first data table to be processed.

In this step, the first to-be-processed data table includes a plurality of to-be-processed data, which may be data generated by the user during the process of using the service system, such as payment data of the user, ticket data of the user, and the like.

S102: and auditing the first to-be-processed data table according to the first auditing index set.

In this step, the first auditing index set includes a plurality of auditing indexes with relevance, such as service compliance, data mutual exclusion, data integrity, data consistency, and the like, and the data to be processed in the first data table to be processed is audited according to the plurality of auditing indexes with relevance in the first auditing index set, where the auditing process may be defined as determining whether the data to be processed in the first data table to be processed is abnormal through the plurality of auditing indexes, such as determining whether the data ordered by the tariff subscription is abnormal when the user uses the service system to perform the tariff subscription through the service compliance, or determining whether a package of a certain user in the first data table to be processed has a plurality of standards through the data mutual exclusion, or determining whether a package of a normal user does not exist through the data integrity, or determining whether the first data table to be processed and the second data table are consistent through the data consistency.

In the above scheme, a plurality of audit indexes in the first audit index set have correlation. When the first to-be-processed data table is audited according to the audit indexes, because one audit index is used for auditing the to-be-processed data, the abnormality of the to-be-processed data may be that the abnormality occurs only when the to-be-processed data is audited through the audit index, and the abnormality does not occur when other audit indexes are audited, in this case, the abnormality of the to-be-processed data may be a suspected abnormality, and actually, the to-be-processed data may not occur. At this time, in order to determine whether the exception occurring in the data to be processed is a real exception, manual review is usually required, which undoubtedly increases the workload of the review personnel. However, when the plurality of auditing indexes in the first auditing index set have relevance, if the data to be processed is audited to be abnormal through one of the auditing indexes in the first auditing index set and the auditing index having relevance with the auditing index in the first auditing index set, the abnormality of the data to be processed is indicated to be real abnormality.

S103: and judging whether the first to-be-processed data table has the first to-be-processed data which does not finish auditing.

In this step, in step S102, the data to be processed is already audited through the audit indicator, and if the data to be processed is not audited through the audit indicator, it is indicated that an audit result cannot be obtained when the data to be processed is audited through the audit indicator, that is, whether the data to be processed is abnormal or not cannot be determined.

For example, when the first to-be-processed data table includes data of the current account period of the user, and whether the data of the current account period is abnormal is judged, the data of the current account period needs to be compared with the historical account period data to determine whether the data of the current account period meets the requirements of a certain fluctuation rate, a threshold value and a balance formula, so that the accuracy of the data of the current account period is judged. However, since the auditing indexes such as service compliance, data mutual exclusion, data integrity, data consistency, etc. included in the first auditing index set cannot audit the data accuracy, when the current first auditing index set is used to audit the data in the current accounting period, the auditing result cannot be obtained, and therefore, the data in the current accounting period is the first to-be-processed data whose auditing is not completed.

In the above solution, if the first to-be-processed data table does not have the first to-be-processed data that does not complete auditing, it indicates that the current first auditing index set can complete auditing the first to-be-processed data table.

S104: and if the first data to be processed exists in the first data table to be processed, auditing the first data to be processed by using the first auditing index.

In this step, if the first to-be-processed data table has the first to-be-processed data that is not finished with the audit, it indicates that the current first audit index set cannot finish the audit processing on the first to-be-processed data table, and therefore, a new first audit index needs to be added to perform the audit processing on the first to-be-processed data, so that more comprehensive audit processing on the to-be-processed data in the first to-be-processed data table can be realized, and therefore, data missing during the audit data is avoided, and the integrity and accuracy of the combination result are improved.

In the data processing method provided by this embodiment, when the first to-be-processed data table is audited by using the first audit index set, if the first to-be-processed data table still has the first to-be-processed data that is not audited, a new first audit index needs to be added to audit the first to-be-processed data, so that after the first audit index is added to the first audit index set, the first audit index set can be completed, thereby implementing more comprehensive audit on the data through the completed first audit index set, avoiding missing data, and after the first audit index set is completed, potential data abnormality can be found in the data production process, so that hysteresis for finding data abnormality is avoided, and meanwhile, because a plurality of audit indexes in the first audit index set have relevance, efficiency and accuracy for finding data abnormality can be improved, and further accuracy and integrity of audit results are improved.

The method for determining whether there is unfinished audit first to-be-processed data in the first to-be-processed data table will be described in detail below.

In one possible implementation, the determining whether there is first to-be-processed data that does not complete audit in the first to-be-processed data table includes: acquiring a first quantity of to-be-processed data which is subjected to audit in a first to-be-processed data table; acquiring a second quantity of all data to be processed in the first data table to be processed; and if the first quantity is not equal to the second quantity, determining that the first data to be processed exists in the first data table to be processed.

In the scheme, when the first auditing index set is used for auditing the data to be processed in the first data table to be processed, each pair of data to be processed is audited, a corresponding auditing result is recorded, the data to be processed with the auditing result is finally determined, namely the first quantity of the data to be processed which is already audited in the first data table to be processed, and if the first quantity of the data to be processed which is already audited is not equal to the second quantity of all the data to be processed, the first data to be processed which is not already audited exists in the first data table to be processed. When the to-be-processed data which is already audited is audited through the audit indexes, the data of the audit result can be obtained.

In the foregoing solution, if the first quantity of the to-be-processed data that has been audited is equal to the second quantity of all the to-be-processed data, it indicates that the audit indicator that has been included in the first audit indicator set can satisfy that the audit is completed for all the data in the first to-be-processed data table, and at this time, it indicates that the first to-be-processed data that has not been audited does not exist in the first to-be-processed data table.

In the above scheme, whether the first quantity of the to-be-processed data which has completed the audit is equal to the second quantity of all the to-be-processed data can be determined through a balance formula. The balancing formula may be established according to a plurality of dimensions, for example, (1) determined according to the number of data pieces received by the system, in this case, the balancing formula may be: the number of the received data is = the number of the normal data + the number of the abnormal data, and the number of the normal data and the number of the abnormal data can be determined by the audit index; (2) As determined by the gains in the system, the balance formula may then be: revenue-expenditure = revenue, whether revenue and expenditure are abnormal or not can be determined by audit metrics; (3) As determined by the total revenue of the system, the balance formula may then be: system revenue + C system revenue + … … = total revenue, and whether subsystem revenue and system total revenue are abnormal may be determined by an audit trail.

In the above solution, the balancing formulas in (1), (2) and (3) may be applied to each service system and the module corresponding to each service system, for example, for the subsystem a, the balancing formula may be: number of data received = number of normal data pieces + number of abnormal data pieces, revenue-expenditure = revenue, and a-module revenue + b-module revenue + … … = a system total revenue.

The second audit index set obtained after adding the first audit index to the first audit index set is described in detail below.

Fig. 2 is a flowchart of a second embodiment of a data processing method provided in the embodiment of the present application, and as shown in fig. 2, the data processing method includes the following steps:

s201: and adding the first audit index to the first audit index set to obtain a second audit index set.

In this step, since the first audit index is determined according to the first to-be-processed data which is not finished to be audited in the first to-be-processed data table, if the first to-be-processed data which is not finished to be audited exists in the first to-be-processed data table, after the first to-be-processed data is audited by using the first audit index, the first audit index is added to the first audit index set, so that the audit indexes in the second audit index set can be more perfect, potential data abnormality can be found in the subsequent data production process, and the problem of hysteresis for finding data abnormality in the prior art is avoided.

S202: and acquiring a second data table to be processed.

In this step, the second to-be-processed data table is a data table different from the first to-be-processed data table, and the second to-be-processed data table also includes a plurality of to-be-processed data.

S203: and auditing the data to be processed in the second data table to be processed according to the second auditing index set.

In this step, the second audit index set is an audit index set that has completed the audit indexes. The first data sheet to be processed is audited by using the first auditing index set, so that new auditing indexes needing to be added are determined and added to the first auditing index set, and therefore, the data to be processed in the second data sheet to be processed can be audited by using the second auditing index set which is completed in the production process, abnormal data can be found earlier and faster, the accuracy and the integrity of auditing the data are improved, meanwhile, the abnormality of the data can be found in the data production process, and the efficiency of finding the abnormal data is further improved.

In the data processing method provided by the embodiment, a second audit index set is obtained by adding the first audit index to the first audit index set; acquiring a second data table to be processed, wherein the second data table to be processed comprises a plurality of data to be processed; and auditing the data to be processed in the second data sheet to be processed according to the second auditing index set, so that the data to be processed in the second data sheet to be processed can be audited by using the second auditing index set which is completed in the production process, abnormal data can be found earlier and faster, the accuracy and the integrity of auditing the data are improved, the abnormality of the data can be found in the data production process, and the efficiency of finding the abnormal data is further improved.

The method for obtaining the second audit trail set is described in detail below.

In one possible implementation, the method further comprises: acquiring a third quantity of second to-be-processed data which is not finished to be audited in the first to-be-processed data after the first audit indicator is used for auditing the first to-be-processed data; adding the first audit index to the first audit index set to obtain a second audit index set, comprising: and if the third quantity is smaller than the preset quantity threshold value, adding the first auditing index into the first auditing index set to obtain a second auditing index set.

In the scheme, after the added new first audit index is used for auditing the first to-be-processed data, if the first to-be-processed data still contains the second to-be-processed data which is not finished to be audited and the third quantity of the second to-be-processed data which is not finished to be audited is smaller than the preset quantity threshold, the new first audit index can audit most of the first to-be-processed data, at the moment, the first audit index is added to the first audit index set, and the obtained second audit index set can be more accurate and comprehensive, so that the accuracy of the audit data can be improved by auditing the data through the second audit index set, potential data abnormity can be found in the subsequent data production process, and the problem of hysteresis for finding data abnormity in the prior art is avoided.

The method for auditing the process flow to be processed is described in detail below.

In one possible implementation, a first flow to be processed is obtained; auditing the first to-be-processed flow according to the first auditing index set; judging whether the first auditing index set finishes auditing the first flow to be processed or not; and if the first auditing index set does not finish auditing the first to-be-processed flow, auditing the first to-be-processed flow by using a second auditing index, wherein the second auditing index is an auditing index out of the first auditing index set.

In the scheme, the first audit index set can audit the data sheet to be processed and also can audit the flow generated by the user in the process of using the business system, so that abnormal problems in the flow to be processed can be found in time, for example, the problem that the user does not operate properly in a certain link in the process of using the business system can be found out, and if the operation in the flow to be processed of the user can be determined to be proper through the first audit index set, the first audit index set can finish auditing the first flow to be processed; if the first auditing index set can not determine whether the operation in the to-be-processed flow of the user is proper, the first auditing index set does not finish auditing the first to-be-processed flow.

In the above scheme, if the first auditing index set does not complete auditing for the first to-be-processed flow, the second auditing index is used to audit the first to-be-processed flow, so that the accuracy of the auditing result for auditing the first to-be-processed flow can be improved. Similarly, the first to-be-processed data sheet is audited through the plurality of auditing indexes with relevance, and because the plurality of auditing indexes in the first auditing index set have relevance, the workload of the rechecker can be reduced, so that the working efficiency of the rechecker is improved, and the accuracy of determining whether the to-be-processed flow is abnormal is also ensured.

In one possible implementation, the method further comprises: adding the second auditing index to the first auditing index set to obtain a third auditing index set; acquiring a second flow to be processed; and auditing the second to-be-processed flow according to the third auditing index set.

In the scheme, the second auditing index can audit the first to-be-processed flow, the third auditing index set obtained after the second auditing index is added into the first auditing index set can be more perfect, and the accuracy and the comprehensiveness of auditing the new second to-be-processed flow can be improved when the new second to-be-processed flow is audited. Moreover, after the first audit index set is perfected to obtain the third audit index set, when the second to-be-processed flow is audited subsequently, the auditing can be completed in the production process of the second to-be-processed flow for the operation process and the plurality of data tables, and the problem of abnormal hysteresis can be avoided.

In one possible implementation, auditing a plurality of data tables and a plurality of processes through auditing indexes of multiple dimensions such as service compliance, data mutual exclusion, data integrity, data consistency and the like can be exemplified by the following table 1:

TABLE 1 correspondence table for multi-dimensional audit index and multi-data audit process

In the data processing method provided by the embodiment of the application, when the first data table to be processed or the first flow to be processed is audited by using the first audit index set, if the first data table to be processed still has the first data to be processed which is not audited completely or cannot be audited completely, a new first audit index needs to be added to audit the first data to be processed, or a new second audit index is added to audit the flow to be processed, so that after the first audit index or the second audit index is added to the first audit index set, the first audit index set can be completed, so that more comprehensive data auditing is realized by the completed first audit index set, data omission is avoided, after the first audit index set is completed, potential data abnormity can be found in a data production process, hysteresis for finding data abnormity is avoided, and meanwhile, because a plurality of audit indexes in the first audit index set have relevance, the efficiency and the accuracy of data abnormity can be improved, and the audit result can be improved.

In summary, in the technical scheme provided by the application, in the data auditing process, whether the existing auditing indexes in the existing auditing index set can complete auditing processing on data or a flow is determined, and if the existing auditing indexes in the existing auditing index set cannot complete auditing processing on the data or the flow, a new auditing index is added, so that the aim of perfecting and optimizing the auditing index set is fulfilled, the capability of timely discovering known risks and unknown risks in the system is realized, and the technical implementation method can improve the accuracy and integrity of auditing processing on data and the efficiency of discovering abnormal data.

Fig. 3 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application, and as shown in fig. 3, the data processing apparatus 30 includes:

the acquiring module 31 is configured to acquire a first to-be-processed data table, where the first to-be-processed data table includes a plurality of to-be-processed data;

the first processing module 32 is configured to audit the first to-be-processed data table according to a first audit index set, where the first audit index set includes a plurality of audit indexes with relevance;

the judging module 33 is configured to judge whether there is a first to-be-processed data that does not complete audit in the first to-be-processed data table;

the second processing module 34 is configured to, if the first to-be-processed data exists in the first to-be-processed data table, perform audit processing on the first to-be-processed data by using a first audit indicator, where the first audit indicator is an audit indicator other than the first audit indicator set.

Optionally, the determining module 33 is further configured to obtain a first quantity of the to-be-processed data that has been audited in the first to-be-processed data table; acquiring a second quantity of all data to be processed in the first data table to be processed; and if the first quantity is not equal to the second quantity, determining that the first data to be processed exists in the first data table to be processed.

Optionally, the apparatus is further configured to add the first audit index to the first audit index set to obtain a second audit index set; acquiring a second data table to be processed, wherein the second data table to be processed comprises a plurality of data to be processed; and auditing the data to be processed in the second data table to be processed according to the second auditing index set.

Optionally, the device is further configured to obtain a third amount of second to-be-processed data that is not finished to be audited in the first to-be-processed data after the first audit indicator is used to audit the first to-be-processed data; and if the third quantity is smaller than the preset quantity threshold value, adding the first auditing index into the first auditing index set to obtain a second auditing index set.

Optionally, the apparatus is further configured to obtain a first to-be-processed flow; auditing the first to-be-processed flow according to the first auditing index set; judging whether the first auditing index set completes auditing on the first to-be-processed flow or not; and if the first auditing index set does not finish auditing the first to-be-processed flow, auditing the first to-be-processed flow by using a second auditing index, wherein the second auditing index is an auditing index out of the first auditing index set.

Optionally, the apparatus is further configured to add the second audit index to the first audit index set to obtain a third audit index set; acquiring a second flow to be processed; and auditing the second to-be-processed flow according to the third auditing index set.

The data processing apparatus provided in this embodiment is configured to implement the technical solution of the data processing method in the foregoing method embodiments, and the implementation principle and the technical effect are similar, which are not described herein again.

Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application, and as shown in fig. 4, the electronic device 400 includes:

a processor 411, a memory 412, and an interaction interface 413;

the memory 412 is used for storing executable instructions executable by the processor 411;

wherein, the processor 411 is configured to execute the technical solution of the data processing method provided by the foregoing method embodiment through executing the executable instruction.

Alternatively, the memory 412 may be separate or integrated with the processor 411.

Optionally, when the memory 412 is a device separate from the processor 411, the electronic device 400 may further include:

and the bus is used for connecting the devices.

The electronic device is configured to execute the technical solution provided by the foregoing method embodiment, and the implementation principle and technical effect of the electronic device are similar to those in the foregoing method embodiment, which are not described herein again.

Embodiments of the present application further provide a readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the data processing method provided by the foregoing method embodiments.

The embodiment of the present application further provides a computer program product, which includes a computer program, and the computer program is used for implementing the data processing method provided by the foregoing method embodiment when being executed by a processor.

Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method of data processing, comprising:

acquiring a first data table to be processed, wherein the first data table to be processed comprises a plurality of data to be processed;

auditing the first to-be-processed data table according to a first auditing index set, wherein the first auditing index set comprises a plurality of auditing indexes with relevance;

judging whether the first to-be-processed data table has the first to-be-processed data which does not finish auditing;

and if the first to-be-processed data exists in the first to-be-processed data table, auditing the first to-be-processed data by using a first auditing index, wherein the first auditing index is an auditing index outside the first auditing index set.

2. The method of claim 1, wherein the determining whether there is pending data in the first pending data table comprises:

acquiring a first quantity of the to-be-processed data which is subjected to audit in the first to-be-processed data table;

acquiring a second quantity of all data to be processed in the first data table to be processed;

and if the first quantity is not equal to the second quantity, determining that the first data to be processed exists in the first data table to be processed.

3. The method of claim 1, further comprising:

adding the first audit index to the first audit index set to obtain a second audit index set;

acquiring a second data table to be processed, wherein the second data table to be processed comprises a plurality of data to be processed;

and auditing the data to be processed in the second data table to be processed according to a second auditing index set.

4. The method of claim 3, further comprising:

acquiring a third quantity of second to-be-processed data which is not finished to be audited in the first to-be-processed data after the first to-be-processed data is audited by using a first auditing index;

adding the first audit index to the first audit index set to obtain a second audit index set, including:

and if the third quantity is smaller than a preset quantity threshold value, adding the first audit index to the first audit index set to obtain the second audit index set.

5. The method of claim 1, further comprising:

acquiring a first flow to be processed;

auditing the first to-be-processed flow according to the first auditing index set;

judging whether the first auditing index set completes auditing on the first to-be-processed flow or not;

and if the first auditing index set does not finish auditing the first process to be processed, using a second auditing index to audit the first process to be processed, wherein the second auditing index is an auditing index out of the first auditing index set.

6. The method of claim 5, further comprising:

adding the second audit index to the first audit index set to obtain a third audit index set;

acquiring a second flow to be processed;

and auditing the second to-be-processed flow according to the third auditing index set.

7. A data processing apparatus, characterized by comprising:

the device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a first data table to be processed, and the first data table to be processed comprises a plurality of data to be processed;

the first processing module is used for auditing the first to-be-processed data table according to a first auditing index set, wherein the first auditing index set comprises a plurality of auditing indexes with relevance;

the judging module is used for judging whether the first to-be-processed data which do not finish auditing exist in the first to-be-processed data table;

and the second processing module is used for auditing the first data to be processed by using a first auditing index if the first data to be processed exists in the first data table to be processed, wherein the first auditing index is an auditing index out of the first auditing index set.

8. An electronic device, comprising:

a processor, a memory, an interactive interface;

the memory is used for storing executable instructions executable by the processor;

wherein the processor is configured to perform the data processing method of any of claims 1 to 6 via execution of the executable instructions.

9. A readable storage medium on which a computer program is stored, which computer program, when being executed by a processor, carries out the data processing method of any one of claims 1 to 6.

10. A computer program product comprising a computer program for implementing a data processing method according to any one of claims 1 to 6 when the computer program is executed by a processor.