CN112215692A - Data checking method, device, terminal equipment and storage medium - Google Patents
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Abstract
The application provides a method, a device, a terminal device and a storage medium for checking data, wherein the method comprises the following steps: predefining a checking rule, wherein the checking rule comprises a checking priority; drawing two target data, and defining one target data as a first target data and the other target data as a second target data; and checking the second target data according to the checking priority by taking the first target data as a reference. By adopting the method provided by the invention, the user can self-define the checking priority according to the actual requirement, thereby meeting the requirements of various data checking scenes. Moreover, the method provided by the invention can also automatically check, thereby reducing the error rate of manual checking and improving the efficiency of data checking.
Description
Technical Field
The application belongs to the field of data processing, and particularly relates to a method and device for checking data, terminal equipment and a storage medium.
Background
In daily life and in the production and operation activities of enterprises, data is often checked. For example, checking bills in daily life, checking invoices in enterprise production and management activities, and the like. Particularly in the production and operation activities of enterprises, various data may need to be checked, for example, checking of distributed photovoltaic invoices, checking of settlement data of electricity charge settlement and invoice data, checking of subsidy data and invoice data in renewable subsidy settlement and checking of imported data and existing data in distributed settlement.
These data have a common feature, and are huge in data size. At present, a manual checking mode is generally adopted to check data, however, the manual checking mode not only consumes a large amount of manpower and financial resources, but also is easy to make mistakes; in addition, there is another problem in the manual collation method, that is, the flexibility of collating data is low, and the collation rule cannot be customized, and the manual collation method cannot collate data according to the customized priority.
Disclosure of Invention
The application provides a method and a device for checking data, terminal equipment and a storage medium, which are used for solving the problems of low efficiency of checking data, high possibility of error and incapability of customizing a checking rule.
In a first aspect, the present invention provides a method of collating data, including the steps of:
predefining a checking rule, wherein the checking rule comprises a checking priority;
drawing two target data, and defining one target data as a first target data and the other target data as a second target data;
and checking the second target data according to the checking priority by taking the first target data as a reference.
As another optional aspect of the present invention, the checking rule further includes one or more of a difference range, a checking manner, or a data item.
As another optional scheme of the present invention, the checking priorities specifically include a first priority, a second priority, a third priority and a fourth priority;
wherein the first priority is expressed as equality of a value of the first target data and a value of the second target data; the second priority is expressed as the sum of the numerical values of the plurality of pieces of the first target data being equal to the numerical value of the second target data; the third priority is expressed as a sum of a value of the first target data and a value of a plurality of pieces of the second target data; the fourth priority is expressed as a sum of values of a plurality of pieces of the first target data being smaller than a value of one piece of the second target data.
As another optional scheme of the present invention, the step of pulling the target data, and defining one of the target data as the first target data, and defining the other of the target data as the second target data specifically includes:
filtering the target data according to a preset condition to obtain a corresponding filtering result;
pulling target data from the filtering result;
and defining one part of target data as first target data and defining the other part of target data as second target data according to preset definition rules.
As another optional aspect of the present invention, after the step of checking the second target data according to the checking priority with reference to the first target data, the method further includes:
and receiving a query instruction input by a user to query the successfully checked data in the target data.
As another optional aspect of the present invention, after the step of checking the second target data according to the checking priority with reference to the first target data, the method further includes:
and recording the matching relation and the data difference value of the two successfully checked target data.
As another optional aspect of the present invention, after the step of checking the second target data according to the checking priority with reference to the first target data, the method further includes:
when the data in the target data is successfully checked, marking the successfully checked data;
when the data in the target data fails to be checked, prompt information of the checking failure is displayed for the data which fails to be checked, and the prompt information contains the reason of the checking failure.
In a second aspect, the present invention also provides an apparatus for collating data, including:
a definition module for defining a collation rule including a collation priority;
the pull module is used for pulling two pieces of target data, and defining one piece of target data as first target data and the other piece of target data as second target data;
and the checking module is used for checking the second target data by taking the first target data as a reference according to the checking priority.
In a third aspect, the present invention further provides a terminal device, where the terminal device includes a processor, a memory, and a computer program stored on the memory and operable on the processor, and the processor implements the method for checking data when executing the computer program.
In a fourth aspect, the present invention is also a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program comprising program instructions which, when executed by a processor, cause the processor to perform the method of collating data.
The method provided by the invention can self-define the check rule and check the data according to the self-defined check rule, thereby effectively improving the data checking efficiency and reducing the error rate. Specifically, the user may first customize the collation rules including the collation priorities; when data needs to be checked, pulling two target data to be checked, and defining one of the target data as first target data and the other target data as second target data; finally, the second target data is collated with the collation priority with the first target data as a reference (standard), thereby completing the collation of the target data. By adopting the method provided by the invention, the user can define the checking rule according to the actual requirement, thereby meeting the requirements of various data checking scenes. Moreover, the method provided by the invention can also automatically check, thereby reducing the error rate of manual checking and improving the efficiency of data checking.
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 description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flowchart of a method for checking data according to a preferred embodiment of the present invention.
FIG. 2 is a block diagram of an apparatus for checking data according to a preferred embodiment of the present invention.
Fig. 3 is a block diagram of a terminal device according to a preferred embodiment of the present invention.
Detailed Description
In order to make the features and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only a part of the embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the application, as detailed in the appended claims.
In the description of the embodiments of the present application, it is to be understood that, in the description of the present application, "a plurality" means two or more unless otherwise specified. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.
Referring to fig. 1, fig. 1 is a flow chart of a preferred embodiment of a method for collating data, the method comprising:
s1, pre-defining a checking rule, wherein the checking rule comprises a checking priority.
In the above step, the collation rule includes a collation priority, a deficit range, a collation manner, and a data item. The checking priority refers to a priority order adopted when data is checked, namely, data with high priority is checked first, and then data with low priority is checked, or one checking priority can be automatically selected to check the data; the difference range refers to the range of data difference allowed when checking data, such as the difference range of money amount, the difference range of tax amount, and the like; the checking mode is to select which mode to check the data, and the checking mode can include all matching checking, partial matching checking and the like; the data item is a specific item in the selection required data, for example, a selected item for checking tax amount, a selected item for checking commodity value or a selected item for checking commodity name.
In order to better check data, the invention divides the checking priority into four levels: a first priority, a second priority, a third priority, and a fourth priority; wherein the first priority is expressed as equality of a value of the first target data and a value of the second target data; the second priority is expressed as the sum of the numerical values of the plurality of pieces of the first target data being equal to the numerical value of the second target data; the third priority is expressed as a sum of a value of the first target data and a value of a plurality of pieces of the second target data; the fourth priority is expressed as a sum of values of a plurality of pieces of the first target data being smaller than a value of one piece of the second target data. The first target data and the second target data and the association relationship will be described in detail later. In the fourth priority, the fact that the sum of the values of the plurality of pieces of first target data is smaller than the value of one piece of second target data means that the sum of the values of the plurality of pieces of first target data is smaller than the value of the second target data. For example, if the value of the first piece of data in the first target data is 10, the value of the second piece of data in the first target data is 50, the value of the third piece of data in the first target data is 30, and the value of the fourth piece of data in the first target data is 10, the summation result of the values of the first target data is 100; the value of a second target datum may be 120, and in this state, the match is checked against the largest permitted first target datum, i.e., the second datum (value 50) in the first target datum is permitted to be checked against the second target datum.
In the first priority, the second priority, and the third priority, the numerical values equal to each other or the sum of the numerical values equal to each other means that the numerical values are equal to each other within an allowable difference range. That is, a difference range is set, and the difference between the value of the first target data and the value of the second target data is within the difference range, then the first target data or the second target data check is judged to be passed; if the difference value of the numerical value of the first target data and the numerical value of the second target data is not within the difference range, judging that the first target data or the second target data fails to be checked; the same logic applies to the second priority and the third priority. As another possible implementation, the definition of the priority order of the collation priorities may be arranged interchangeably.
Referring again to fig. 1, the method includes:
and S2, pulling two pieces of target data, and defining one piece of target data as first target data and the other piece of target data as second target data.
In the above step, when data needs to be checked, two pieces of target data (i.e., data to be checked) are pulled (called) first, and then one piece of target data of the two pieces of target data is used as first target data, and the rest is used as second target data. In other words, the first target data and the second target data are both part of the data to be checked, and the user can freely divide or define the target data according to actual needs, so as to obtain the corresponding first target data and the second target data. Of course, there needs to be some correlation between the first target data and the second target data, or there needs to be comparability and verifiability. For example, the first target data is settlement data of a certain client, and the second data is invoice data corresponding to the client; the first target data is contract amount data of a certain user, and the second data is invoice data of the certain user; the first target data is theoretical power consumption data of a certain user, and the second target data is actual power consumption data of the certain user and the like.
As another optional aspect of the present invention, the step S2 specifically includes: filtering the target data according to a preset condition to obtain a corresponding filtering result; pulling two pieces of target data from the filtering result; and defining one target data as a first target data and the other target data as a second target data according to a preset definition rule.
In the above step, the preset condition refers to a rule that can filter the target data. For example, the preset conditions are: a value greater than 100; or the preset conditions are as follows: the data contains decimal fraction; or the preset conditions are as follows: the value is less than 50. Of course, the user can freely set the preset conditions according to actual needs, and then filter the target data according to the preset conditions to obtain corresponding filtering results. For example, if the user adopts a preset condition of "the value is greater than 100", the filtering result is data with data greater than 100. After the filtering result is obtained, a part or all of the filtering result can be used as the target data. And then, freely defining the target data according to a preset definition rule, thereby determining the first target data and the second target data. For example, the definition rule is that the first 100 settlement data are used as the first target data, and the first 20 invoice data are used as the second target data; or the definition rule is: every interval, one settlement data is used as the first target data, and the rest settlement data is used as the second target data, namely, the first target data with the odd serial number and the second target data with the even serial number. Of course, the above definition rules are only examples, and in practical applications, a user can set the definition rules according to his own needs.
Referring again to fig. 1, the method includes:
and S3, checking the second target data according to the checking priority by taking the first target data as a reference.
After the first target data and the second target data are determined, the second target data may be checked based on the checking priority and the first target data, so as to complete the data checking operation.
The checking of the second target data according to the checking priority specifically means that one of the checking priorities is automatically selected according to actual conditions of the first target data and the second target data for checking.
By the method provided by the invention, the data can be checked according to the user-defined checking priority, so that the problem that the checking rule cannot be defined by the prior art is solved. Compared with a manual checking mode, the method has the characteristics of high efficiency and low possibility of errors.
As another alternative of the present invention, the step S3 includes the following steps: and recording the matching relation and the data difference value of the two successfully checked target data.
And after the data verification is successful, automatically recording the matching relation between the first target data and the second target data and the data difference value between the first target data and the second target. Therefore, the user can conveniently perform subsequent operations such as tracing, inquiring and the like.
As another optional aspect of the present invention, after step S3, the method further includes: when the data in the target data is successfully checked, marking the successfully checked data; when the data in the target data fails to be checked, prompt information of the checking failure is displayed for the data which fails to be checked, and the prompt information contains the reason of the checking failure.
In the above step, if the target data is successfully checked, marking the successfully checked data in the target data, for example, marking the color of the successfully checked data as red, or setting the format of the font of the successfully checked data as bold and black, etc., and of course, the above marking manner is merely an example, and in the actual application process, a marking manner such as enlargement, etc. may also be adopted; if the target data is failed to be checked, corresponding prompt information is popped up, and the prompt information contains the reason of the checking failure, and then the user can perform data checking again according to the prompt information. Note that, the marking of the successfully collated data in the target data may be performed only on the second target data, or may be performed on the first and second target data.
As another optional aspect of the present invention, after step S3, the method further includes: and receiving a query instruction input by a user to query the checked data.
After the collation of the data is completed, the user inquires the data which has been successfully collated by the inquiry instruction (inquiry information). More specifically, the user can use a table (Excel worksheet) to query and display data matching successfully, and display corresponding matching relations and the like through the table.
As another alternative of the present invention, the step S3 includes the following steps: and receiving an instruction of canceling the checking input by the user, and canceling the checking on the checked target data.
In the above steps, the user who has successfully checked the data can cancel the check, and the data whose check is canceled can be checked again next time. But if the successfully collated data has been used (e.g., exported, marked, etc.) by the user, the collation cannot be canceled.
As another optional aspect of the present invention, after the step S3, the method further includes the steps of: and counting or analyzing the data of the verification success. The statistical or analytical mode may be in a chart format, so that the specific situation of the checked data can be intuitively known.
Compared with the prior art, the method and the device can customize the checking rule according to the self requirement, reduce the error rate of the checked data, improve the checking efficiency, label the successfully checked data and inquire the successfully checked data.
Referring to fig. 2, the present invention also provides a device 10 for checking data, which includes:
a defining module 110 for defining a collation rule including a collation priority;
a pulling module 120, configured to pull the target data, and define one of the target data as a first target data and another target data as a second target data;
and the checking module 130 is configured to check the second target data according to the checking priority by using the first target data as a reference.
It should be noted that, when the apparatus 10 for the method of collating data provided in the above embodiment executes the method of collating data, only the division of each functional module is illustrated, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the apparatus may be divided into different functional modules, so as to complete all or part of the functions described above. In addition, the apparatus 10 for collating data and the method embodiment for collating data belong to the same concept, and the implementation process is discussed in detail in the steps of the method embodiment, so that the detailed description is omitted here.
Referring to fig. 3, the present invention further provides a terminal device 20, which includes a processor 210, a memory 220, and a computer program stored in the memory 220 and operable on the processor, wherein the processor 210 implements the method for counting the inventory of goods when executing the computer program.
The processor 210 may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a single chip, an arm (acorn RISC machine) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination of these components. Also, processor 210 may be any conventional processor, microprocessor, or state machine. Processor 210 may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
The memory 220, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as program instructions corresponding to the method of collating data in the embodiments of the present invention. The processor 210 executes various functional applications of collation data and data processing, i.e., a method of implementing the collation data in the above-described method embodiments, by executing nonvolatile software programs, instructions, and units stored in the storage device.
The specific technical details for implementing the computer program when the terminal device 20 executes the computer program are discussed in detail in the foregoing method steps, and therefore are not described in detail herein.
The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program comprising program instructions which, when executed by a processor, cause the processor to perform the method of accounting for inventory of goods.
The computer readable storage medium may be an internal storage unit of the system according to any of the foregoing embodiments, for example, a hard disk or a memory of the system. The computer readable storage medium may also be an external storage device of the system, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. provided on the system. Further, the computer readable storage medium may also include both an internal storage unit and an external storage device of the system. The computer-readable storage medium is used for storing the computer program and other programs and data required by the system. The computer readable storage medium may also be used to temporarily store data that has been output or is to be output.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electric, mechanical or other form of connection.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method of collating data, said method comprising the steps of:
predefining a checking rule, wherein the checking rule comprises a checking priority;
drawing two target data, and defining one target data as a first target data and the other target data as a second target data;
and checking the second target data according to the checking priority by taking the first target data as a reference.
2. Method for collating data according to claim 1, wherein said collating priorities includes in particular a first priority, a second priority, a third priority and a fourth priority;
wherein the first priority is expressed as equality of a value of the first target data and a value of the second target data;
the second priority is expressed as the sum of the numerical values of the plurality of pieces of the first target data being equal to the numerical value of the second target data;
the third priority is expressed as a sum of a value of the first target data and a value of a plurality of pieces of the second target data;
the fourth priority is expressed as a sum of values of a plurality of pieces of the first target data being smaller than a value of one piece of the second target data.
3. The method for collating data according to claim 1, wherein the step of pulling two pieces of target data and defining one piece of target data as the first target data and the other piece of target data as the second target data specifically includes:
filtering the target data according to a preset condition to obtain a corresponding filtering result;
pulling target data from the filtering result;
and defining one part of target data as first target data and defining the other part of target data as second target data according to preset definition rules.
4. A method for collating data according to claim 1, 2 or 3, wherein said step of collating said second target data based on said first target data and in accordance with said collation priority further includes:
and receiving a query instruction input by a user to query the successfully checked data in the second target data.
5. A method for collating data according to claim 1, 2 or 3, wherein said step of collating said second target data based on said first target data and in accordance with said collation priority further includes:
and recording the matching relation and the data difference value of the two successfully checked target data.
6. A method for collating data according to claim 1, 2 or 3, wherein said step of collating said second target data based on said first target data and in accordance with said collation priority further includes:
when the data in the target data is successfully checked, marking the successfully checked data;
when the data in the target data fails to be checked, prompt information of the checking failure is displayed for the data which fails to be checked, and the prompt information contains the reason of the checking failure.
7. A method of collating data as claimed in claim 1 or claim 2 or claim 3 wherein the collation rules further includes one or more of a spread, collation pattern or data item.
8. An apparatus for collating data, said apparatus comprising:
a definition module for defining a collation rule including a collation priority;
the pull module is used for pulling two pieces of target data, and defining one piece of target data as first target data and the other piece of target data as second target data;
and the checking module is used for checking the second target data by taking the first target data as a reference according to the checking priority.
9. A terminal device comprising a processor, a memory, and a computer program stored on the memory and operable on the processor, wherein the processor, when executing the computer program, implements the method for collating data according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that it stores a computer program comprising program instructions which, when executed by a processor, cause the processor to carry out a method of collating data according to any one of claims 1 to 7.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060013448A1 (en) * | 2004-07-02 | 2006-01-19 | Sharp Kabushiki Kaisha | Biometric data collating apparatus, biometric data collating method and biometric data collating program product |
| CN105989059A (en) * | 2015-02-09 | 2016-10-05 | 阿里巴巴集团控股有限公司 | Data record checking method and device |
| CN109493201A (en) * | 2018-09-18 | 2019-03-19 | 深圳壹账通智能科技有限公司 | Account checking method, device, computer equipment and storage medium |
| CN110689419A (en) * | 2019-10-08 | 2020-01-14 | 四川云智造科技有限公司 | Method, device and equipment for checking multi-party data |
| CN111353841A (en) * | 2018-12-21 | 2020-06-30 | 阿里巴巴集团控股有限公司 | Document data processing method, device and system |
-
2020
- 2020-09-30 CN CN202011064378.XA patent/CN112215692A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060013448A1 (en) * | 2004-07-02 | 2006-01-19 | Sharp Kabushiki Kaisha | Biometric data collating apparatus, biometric data collating method and biometric data collating program product |
| CN105989059A (en) * | 2015-02-09 | 2016-10-05 | 阿里巴巴集团控股有限公司 | Data record checking method and device |
| CN109493201A (en) * | 2018-09-18 | 2019-03-19 | 深圳壹账通智能科技有限公司 | Account checking method, device, computer equipment and storage medium |
| CN111353841A (en) * | 2018-12-21 | 2020-06-30 | 阿里巴巴集团控股有限公司 | Document data processing method, device and system |
| CN110689419A (en) * | 2019-10-08 | 2020-01-14 | 四川云智造科技有限公司 | Method, device and equipment for checking multi-party data |
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