CN111813829A - Data resolution method, device, electronic equipment and storage medium - Google Patents
Data resolution method, device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of artificial intelligence, can be applied to the field of intelligent government affairs of intelligent cities, and provides a data resolution method, a device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring data to be settled through a system interface and a preset data warehouse; performing settlement on the data to be settled according to a preset first settlement formula to obtain settlement data; checking the settlement data to obtain a checking result, wherein the checking mode comprises checking according to a preset checking formula and/or a preset access rule and/or table connection operation; if the check result is passed, summarizing the settlement data to obtain summarized data; and sending the summarized data to a preset terminal. Furthermore, the present invention also relates to block chain techniques, which summarized data may be stored in block chains. By using the method and the device, the accuracy of the settlement data can be ensured, and the data settlement efficiency can be improved.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a data resolution method, a data resolution device, electronic equipment and a storage medium.
Background
At present, each item of data (such as financial money transfer) needs to be settled by a government department every year according to a newly issued settlement rule (formula), and in practice, it is found that due to huge data volume, a large number of people are needed to perform data checking peer-to-peer work, so that settlement efficiency is not high.
Therefore, how to improve the data resolution efficiency is a technical problem which needs to be solved urgently.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a data resolution method, an apparatus, an electronic device, and a storage medium, which can improve data resolution efficiency.
A first aspect of the present invention provides a data resolution method, the method comprising:
acquiring data to be settled through a system interface and a preset data warehouse;
performing settlement on the data to be settled according to a preset first settlement formula to obtain settlement data;
checking the settlement data to obtain a checking result, wherein the checking mode comprises checking according to a preset checking formula and/or a preset access rule and/or table connection operation;
if the check result is passed, summarizing the settlement data to obtain summarized data;
and sending the summarized data to a preset terminal.
In a possible implementation manner, the checking the decision data, and obtaining a check result includes:
according to the first settlement formula, performing settlement again on the data to be settled to obtain first check data;
judging whether the settlement data is consistent with the first check data or not;
if the settlement data is consistent with the first check data, determining that the check result is passed; or
And if the decision making data is inconsistent with the first check data, determining that the check result is not passed.
As an optional implementation manner, there are multiple types of the resolution data, and the checking the resolution data to obtain the checking result includes:
acquiring a preset numerical threshold range corresponding to settlement data by adopting a preset access rule aiming at each type of settlement data;
judging whether the settlement data is in the preset value threshold range or not;
if the settlement data is within the preset value threshold range, determining that the checking result is passed; or
And if the decision-making data is not in the preset value threshold range, determining that the check result is not passed.
In a possible implementation manner, the checking the decision data, and obtaining a check result includes:
acquiring target data from a data interface or a data table specified by the access rule according to the access rule;
determining second check data corresponding to the target data according to a second decision formula corresponding to the target data in the check formulas;
determining data to be checked corresponding to the target data from the settlement data;
performing table linkage on the target data, the second check data and the data to be checked to obtain a target data table;
inquiring whether a target row exists in the target data table or not, wherein second check data corresponding to the target row are inconsistent with data to be checked corresponding to the target row;
if the target data table does not have a target row, determining that the verification result is passed; and if the target row exists in the target data table, determining that the verification result is failed.
In one possible implementation, the data resolution method further includes:
if the verification result is that the verification result does not pass, generating alarm information;
and sending the alarm information to a terminal of a manager.
In one possible implementation, the data to be resolved includes first data to be resolved and second data to be resolved, and the data resolution method further includes:
acquiring data to be settled which is not input into a system;
preprocessing the data to be settled which are not input into the system to obtain preprocessed data;
storing the preprocessed data in the data repository;
the acquiring the data to be settled through the system interface and the preset data warehouse comprises:
acquiring the first data to be settled through the system interface;
and querying and acquiring the second data to be settled from the preprocessed data through the data warehouse.
In one possible implementation, the data resolution method further includes:
when a data analysis instruction is received, determining the source of the data to be resolved;
generating a first table according to the data to be settled;
in the first table, using a plurality of preset color blocks to mark data to be resolved from different sources to obtain a second table, wherein the data to be resolved from one source corresponds to one color block;
and outputting the second table.
A second aspect of the present invention provides a data resolution apparatus including:
the acquisition module is used for acquiring data to be resolved through a system interface and a preset data warehouse;
the settlement module is used for performing settlement on the data to be settled according to a preset first settlement formula to obtain settlement data;
the checking module is used for checking the settlement data to obtain a checking result, wherein the checking mode comprises checking according to a preset checking formula and/or a preset access rule and/or table connection operation;
the summarizing module is used for summarizing the decision data to obtain summarized data if the checking result is that the check result passes;
and the sending module is used for sending the summarized data to a preset terminal.
A third aspect of the present invention provides an electronic device comprising a processor and a memory, wherein the processor is configured to implement the data voting method when executing a computer program stored in the memory.
A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the data resolution method.
By the technical scheme, the settlement data to be settled can be settled according to the preset first settlement formula through the artificial intelligence technology, the settlement data passing the verification is collected and reported (the collected data is sent to the preset equipment terminal), the accuracy of the settlement data is ensured, and the data settlement efficiency is improved.
Drawings
Fig. 1 is a flow chart of a preferred embodiment of a data resolution method disclosed in the present invention.
Fig. 2 is a functional block diagram of a preferred embodiment of a data resolution apparatus according to the present disclosure.
Fig. 3 is a schematic structural diagram of an electronic device for implementing a data resolution method according to a preferred embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
The data resolution method provided by the embodiment of the invention is applied to the electronic equipment, and can also be applied to a hardware environment formed by the electronic equipment and a server connected with the electronic equipment through a network, and the server and the electronic equipment are jointly executed. Networks include, but are not limited to: a wide area network, a metropolitan area network, or a local area network.
A server may refer to a computer system that provides services to other devices (e.g., electronic devices) in a network. A personal computer may also be called a server if it can externally provide a File Transfer Protocol (FTP) service. In a narrow sense, a server refers to a high-performance computer, which can provide services to the outside through a network, and compared with a common personal computer, the server has higher requirements on stability, security, performance and the like, and therefore, hardware such as a CPU, a chipset, a memory, a disk system, a network and the like is different from that of the common personal computer.
The electronic device is a device capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction, and the hardware thereof includes, but is not limited to, a microprocessor, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like. The electronic device may also include a network device and/or a user device. The network device includes, but is not limited to, a single network device, a server group consisting of a plurality of network devices, or a Cloud Computing (Cloud Computing) based Cloud consisting of a large number of hosts or network devices, wherein the Cloud Computing is one of distributed Computing, and is a super virtual computer consisting of a group of loosely coupled computers. The user device includes, but is not limited to, any electronic product that can interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device, for example, a personal computer, a tablet computer, a smart phone, a Personal Digital Assistant (PDA), or the like.
Referring to fig. 1, fig. 1 is a flow chart of a preferred embodiment of a data resolution method according to the present invention. The order of the steps in the flowchart may be changed, and some steps may be omitted. The execution subject of the data resolution method can be an electronic device.
And S11, acquiring the data to be resolved through a system interface and a preset data warehouse.
Wherein the data warehouse stores pre-operation data
Wherein, the data to be settled can be social insurance payment data, government fund income data and the like.
The pre-operation data can be the summation result, the averaging result and the like of some common data, the operation results are stored in the data warehouse and can be obtained at any time, repeated operation on a large amount of data is not needed each time, and the system efficiency is improved.
The sources of the data to be settled comprise a data warehouse, third party entry and a data providing interface of a docking system.
In the embodiment of the invention, the required data to be settled can be inquired and obtained from the data warehouse, the data to be settled can be obtained through the data providing interface of the docking system, and the data to be settled can also be input by a third party.
As an optional implementation, the data to be resolved includes first data to be resolved and second data to be resolved, and the method further includes:
acquiring data to be settled which is not input into a system;
preprocessing the data to be settled which are not input into the system to obtain preprocessed data;
storing the preprocessed data in the data repository;
the acquiring the data to be settled through the system interface and the preset data warehouse comprises:
acquiring the first data to be settled through the system interface;
and querying and acquiring the second data to be settled from the preprocessed data through the data warehouse.
Wherein the preprocessing includes, but is not limited to, data format conversion, data pre-operation, and data screening. The data format conversion refers to converting the format of the data of the specified type into a preset standard format, such as converting the number of digits after a decimal point, such as data of a date type (2020.06.28 or No. 6/28/2020-06-28 in 2020); the data pre-operation can be the statistics of income data in a preset practice segment, such as the annual statistics of payroll data; the data screening may be to screen data to filter out obviously abnormal data, such as social security payment data of negative numbers.
The data warehouse is used for storing and managing data, and may be a database.
Optionally, the target data in each system may be imported into the data warehouse for management, and the data may be classified and stored in a refined manner, such as social security payment data, government fund income data, and the like, and a certain type of data may be quickly read in subsequent settlement operations, so as to improve the settlement efficiency, and meanwhile, some common operations may be performed in advance, such as accumulation and averaging of a certain type of data in a week, a month, a quarter, and a year (i.e., obtaining the preprocessed data), and the results of these operations may be stored in the data warehouse, so as to obtain the results of these operations at any time during the settlement process, save some calculation steps, and further improve the settlement efficiency.
And S12, performing settlement on the data to be settled according to a preset first settlement formula to obtain settlement data.
The final settlement may be a process of arranging data such as each annual income and expenditure according to a certain rule, such as asset load data and total income data, by a unit, a department, and a country.
Wherein the settlement data may be total income data, total expenditure data, equity data, etc.
And S13, checking the settlement data to obtain a checking result, wherein the checking mode comprises checking according to a preset checking formula and/or a preset access rule and/or table connection operation.
In the embodiment of the invention, the settlement data can be verified in various ways to determine the correctness of the settlement data.
Specifically, the verifying the settlement data to obtain a verification result includes:
according to the first settlement formula, performing settlement again on the data to be settled to obtain first check data;
judging whether the settlement data is consistent with the first check data or not;
if the settlement data is consistent with the first check data, determining that the check result is passed; or
And if the decision making data is inconsistent with the first check data, determining that the check result is not passed.
In this optional embodiment, the data to be resolved may be resolved again to obtain check data, and it is determined whether the resolved data is consistent with the check data, if the resolved data is consistent with the check data, it is determined that the check result is passed, and if the resolved data is not consistent with the check data, it is determined that the check result is not passed.
Specifically, the settlement data may be of various types, and the checking the settlement data to obtain a checking result includes:
acquiring a preset numerical threshold range corresponding to settlement data by adopting a preset access rule aiming at each type of settlement data;
judging whether the settlement data is in the preset value threshold range or not;
if the settlement data is within the preset value threshold range, determining that the checking result is passed; or
And if the decision-making data is not in the preset value threshold range, determining that the check result is not passed.
In this optional embodiment, a preset numerical threshold range may be set in advance for each type of resolution data, and the resolution data within this preset numerical threshold range may be considered as normal, and it is determined that the check result is a pass; decision data outside this preset threshold range of values may be considered abnormal and the check result determined to fail. Optionally, for the resolution data with obviously abnormal values (the resolution data is not within the preset value threshold range), an abnormal prompt word (for example, the resolution data is obviously larger) which is preset, the resolution data and the report of the data to be resolved can be combined into abnormal prompt information and the abnormal prompt information is output to prompt a worker to perform data detection in time.
Specifically, the verifying the settlement data to obtain a verification result includes:
acquiring target data from a data interface or a data table specified by the access rule according to the access rule;
determining second check data corresponding to the target data according to a second decision formula corresponding to the target data in the check formulas;
determining data to be checked corresponding to the target data from the settlement data;
performing table linkage on the target data, the second check data and the data to be checked to obtain a target data table;
inquiring whether a target row exists in the target data table or not, wherein second check data corresponding to the target row are inconsistent with data to be checked corresponding to the target row;
if the target data table does not have a target row, determining that the verification result is passed; and if the target row exists in the target data table, determining that the verification result is failed.
In this alternative embodiment, it is assumed that the access rule takes class a data and class B data, the second resolution formula corresponding to the target data in the check formula is assumed to be a + B ═ C, class C data is the check data, that is, A, B, C class data belongs to the same table, resolution data corresponding to a and B is assumed to be D, and D belongs to another table (including the to-be-resolved data E, F corresponding to each resolution data). The A, B, C, D type can be combined into one table by table join (such as an inner join command of a database). That is, a matching E, B matches F to obtain a target data table, where each row of data in the target data table includes a type a data (equal to the type E data in the row, and does not display the type E data), a type B data (equal to the type F data in the row, and does not display the type F data), a type D data (the check data), and a resolution data (the data to be checked), and if the check data in the row is inconsistent with the data to be checked, it is determined that the target row of the row, that is, the resolution data, is likely to have an error, and error troubleshooting is required.
S14, if the check result is that the result passes, summarizing the decision data to obtain summarized data;
in the embodiment of the present invention, if the check result is passed, it may be determined that the resolution data does not have a problem, the resolution data may be summarized, or the resolution data from different units may be summarized into the summarized data.
As an optional implementation, the method further comprises:
if the verification result is that the verification result does not pass, generating alarm information;
and sending the alarm information to a terminal of a manager.
In this optional embodiment, if the check result is failed, it is determined that the resolution data is abnormal, and an alarm message may be generated, where the alarm message may carry a reason why the check result is failed, such as an abnormal data to be resolved corresponding to the resolution data, an abnormal resolution formula, and the like. And sending the alarm information to a terminal of a manager to prompt the manager to carry out error checking.
And S15, sending the summarized data to a preset terminal.
In the embodiment of the invention, the summarized data can be reported to a superior institution, a superior unit or a superior government by sending the summarized data to a preset terminal.
As an optional implementation, the method further comprises:
when a data analysis instruction is received, determining the source of the data to be resolved;
generating a first table according to the data to be settled;
in the first table, using a plurality of preset color blocks to mark data to be resolved from different sources to obtain a second table, wherein the data to be resolved from one source corresponds to one color block;
and outputting the second table.
In this optional embodiment, when a data analysis instruction is received, the data to be resolved from different sources may be marked by using different color blocks, so that the data in the generated table is clear and convenient for analysis.
It is emphasized that, to further ensure the privacy and security of the summarized data, the summarized data may also be stored in a node of a block chain.
In the method flow described in fig. 1, the data to be resolved can be resolved according to a preset first resolving formula through an artificial intelligence technique, and then verified, the resolved data that passes verification is summarized and reported (the summarized data is sent to a preset device terminal), so that the accuracy of the resolved data is ensured, and the data resolving efficiency is also improved. The invention can be applied to the field of intelligent government affairs of intelligent cities, and helps government affairs staff to automatically carry out final settlement of various annual reports and the like.
Fig. 2 is a functional block diagram of a preferred embodiment of a data resolution apparatus according to the present disclosure.
Referring to fig. 2, the data accounting apparatus 20 may be operated in an electronic device. The data resolution means 20 may comprise a plurality of functional modules consisting of program code segments. Program code for various program segments in the data resolution means 20 may be stored in a memory and executed by at least one processor to perform some or all of the steps of the data resolution method described in fig. 1.
In this embodiment, the data resolution device 20 may be divided into a plurality of functional modules according to the functions performed by the data resolution device. The functional module may include: the system comprises an acquisition module 201, a settlement module 202, a check module 203, a summary module 204 and a sending module 205. The module referred to herein is a series of computer program segments capable of being executed by at least one processor and capable of performing a fixed function and is stored in memory.
The obtaining module 201 is configured to obtain data to be resolved through a system interface and a preset data warehouse.
Wherein the data warehouse stores pre-operation data
Wherein, the data to be settled can be social insurance payment data, government fund income data and the like.
The pre-operation data can be the summation result, the averaging result and the like of some common data, the operation results are stored in the data warehouse and can be obtained at any time, repeated operation on a large amount of data is not needed each time, and the system efficiency is improved.
The sources of the data to be settled comprise a data warehouse, third party entry and a data providing interface of a docking system.
In the embodiment of the invention, the required data to be settled can be inquired and obtained from the data warehouse, the data to be settled can be obtained through the data providing interface of the docking system, and the data to be settled can also be input by a third party.
A final settlement module 202, configured to perform final settlement on the data to be final settled according to a preset first final settlement formula, so as to obtain final settlement data.
The final settlement may be a process of arranging data such as each annual income and expenditure according to a certain rule, such as asset load data and total income data, by a unit, a department, and a country.
Wherein the settlement data may be total income data, total expenditure data, equity data, etc.
The checking module 203 is configured to check the final data to obtain a checking result, where the checking mode includes checking according to a preset checking formula and/or according to a preset access rule and/or using a table join operation.
In the embodiment of the invention, the settlement data can be verified in various ways to determine the correctness of the settlement data.
A summarizing module 204, configured to summarize the final data to obtain summarized data if the verification result is that the final data passes through the checking module.
In the embodiment of the present invention, if the check result is passed, it may be determined that the resolution data does not have a problem, the resolution data may be summarized, or the resolution data from different units may be summarized into the summarized data.
A sending module 205, configured to send the summarized data to a preset terminal.
In the embodiment of the invention, the summarized data can be reported to a superior institution, a superior unit or a superior government by sending the summarized data to a preset terminal.
As an optional implementation manner, the checking module 203 checks the settlement data, and the manner of obtaining the checking result specifically includes:
according to the first settlement formula, performing settlement again on the data to be settled to obtain first check data;
judging whether the settlement data is consistent with the first check data or not;
if the settlement data is consistent with the first check data, determining that the check result is passed; or
And if the decision making data is inconsistent with the first check data, determining that the check result is not passed.
In this optional embodiment, the data to be resolved may be resolved again to obtain check data, and it is determined whether the resolved data is consistent with the check data, if the resolved data is consistent with the check data, it is determined that the check result is passed, and if the resolved data is not consistent with the check data, it is determined that the check result is not passed.
Specifically, the settlement data may be of various types, and the checking module 203 checks the settlement data to obtain a checking result specifically includes:
acquiring a preset numerical threshold range corresponding to settlement data by adopting a preset access rule aiming at each type of settlement data;
judging whether the settlement data is in the preset value threshold range or not;
if the settlement data is within the preset value threshold range, determining that the checking result is passed; or
And if the decision-making data is not in the preset value threshold range, determining that the check result is not passed.
In this optional embodiment, a preset numerical threshold range may be set in advance for each type of resolution data, and the resolution data within this preset numerical threshold range may be considered as normal, and it is determined that the check result is a pass; decision data outside this preset threshold range of values may be considered abnormal and the check result determined to fail. Optionally, for the resolution data with obviously abnormal values (the resolution data is not within the preset value threshold range), an abnormal prompt word (for example, the resolution data is obviously larger) which is preset, the resolution data and the report of the data to be resolved can be combined into abnormal prompt information and the abnormal prompt information is output to prompt a worker to perform data detection in time.
Specifically, the checking module 203 checks the final settlement data, and the manner of obtaining the checking result specifically includes:
acquiring target data from a data interface or a data table specified by the access rule according to the access rule;
determining second check data corresponding to the target data according to a second decision formula corresponding to the target data in the check formulas;
determining data to be checked corresponding to the target data from the settlement data;
performing table linkage on the target data, the second check data and the data to be checked to obtain a target data table;
inquiring whether a target row exists in the target data table or not, wherein second check data corresponding to the target row are inconsistent with data to be checked corresponding to the target row;
if the target data table does not have a target row, determining that the verification result is passed; and if the target row exists in the target data table, determining that the verification result is failed.
In this alternative embodiment, it is assumed that the access rule takes class a data and class B data, the second resolution formula corresponding to the target data in the check formula is assumed to be a + B ═ C, class C data is the check data, that is, A, B, C class data belongs to the same table, resolution data corresponding to a and B is assumed to be D, and D belongs to another table (including the to-be-resolved data E, F corresponding to each resolution data). The A, B, C, D type can be combined into one table by table join (such as an inner join command of a database). That is, a matching E, B matches F to obtain a target data table, where each row of data in the target data table includes a type a data (equal to the type E data in the row, and does not display the type E data), a type B data (equal to the type F data in the row, and does not display the type F data), a type D data (the check data), and a resolution data (the data to be checked), and if the check data in the row is inconsistent with the data to be checked, it is determined that the target row of the row, that is, the resolution data, is likely to have an error, and error troubleshooting is required.
As an optional implementation, the data resolution device 20 further includes:
the first generation module is used for generating alarm information if the verification result is that the verification result does not pass;
the sending module 205 is further configured to send the alarm information to a terminal of a manager.
In this optional embodiment, if the check result is failed, it is determined that the resolution data is abnormal, and an alarm message may be generated, where the alarm message may carry a reason why the check result is failed, such as an abnormal data to be resolved corresponding to the resolution data, an abnormal resolution formula, and the like. And sending the alarm information to a terminal of a manager to prompt the manager to carry out error checking.
As an optional implementation manner, the data to be resolved includes first data to be resolved and second data to be resolved, and the obtaining module 201 is further configured to obtain data to be resolved that is not entered into a system;
the data resolution means 20 further comprises:
the preprocessing module is used for preprocessing the data to be settled which are not input into the system to obtain preprocessed data;
and the storage module is used for storing the preprocessing data into the data warehouse.
The obtaining module 201 obtains the data to be resolved through a system interface and a preset data warehouse specifically by the following steps:
acquiring the first data to be settled through the system interface;
and querying and acquiring the second data to be settled from the preprocessed data through the data warehouse.
Wherein the preprocessing includes, but is not limited to, data format conversion, data pre-operation, and data screening. The data format conversion refers to converting the format of the data of the specified type into a preset standard format, such as converting the number of digits after a decimal point, such as data of a date type (2020.06.28 or No. 6/28/2020-06-28 in 2020); the data pre-operation can be the statistics of income data in a preset practice segment, such as the annual statistics of payroll data; the data screening may be to screen data to filter out obviously abnormal data, such as social security payment data of negative numbers.
The data warehouse is used for storing and managing data, and may be a database.
Optionally, the target data in each system may be imported into the data warehouse for management, and the data may be classified and stored in a refined manner, such as social security payment data, government fund income data, and the like, and a certain type of data may be quickly read in subsequent settlement operations, so as to improve the settlement efficiency, and meanwhile, some common operations may be performed in advance, such as accumulation and averaging of a certain type of data in a week, a month, a quarter, and a year (i.e., obtaining the preprocessed data), and the results of these operations may be stored in the data warehouse, so as to obtain the results of these operations at any time during the settlement process, save some calculation steps, and further improve the settlement efficiency.
As an optional implementation, the data resolution device 20 further includes:
the second determining module is used for determining the source of the data to be resolved when a data analysis instruction is received;
a third generating module, configured to generate a first table according to the data to be resolved;
the marking module is used for marking the data to be resolved from different sources by using a plurality of preset color blocks in the first table to obtain a second table, wherein the data to be resolved from one source corresponds to one color block;
and the second output module is used for outputting the second table.
In this optional embodiment, when a data analysis instruction is received, the data to be resolved from different sources may be marked by using different color blocks, so that the data in the generated table is clear and convenient for analysis.
In the data resolution device 20 described in fig. 2, the data to be resolved can be resolved according to the preset first resolution formula through an artificial intelligence technique, and is verified, then the resolved data that passes verification is summarized and reported (the summarized data is sent to the preset device terminal), so that the accuracy of the resolved data is ensured, and the data resolution efficiency is also improved.
The invention can be applied to the field of intelligent government affairs of intelligent cities, and helps government affairs staff to automatically carry out final settlement of various annual reports and the like.
It is emphasized that, to further ensure the privacy and security of the summarized data, the summarized data may also be stored in a node of a block chain.
As shown in fig. 3, fig. 3 is a schematic structural diagram of an electronic device for implementing a data resolution method according to a preferred embodiment of the present invention. The electronic device 3 comprises a memory 31, at least one processor 32, a computer program 33 stored in the memory 31 and executable on the at least one processor 32, and at least one communication bus 34.
Those skilled in the art will appreciate that the schematic diagram shown in fig. 3 is merely an example of the electronic device 3, and does not constitute a limitation of the electronic device 3, and may include more or less components than those shown, or combine some components, or different components, for example, the electronic device 3 may further include an input/output device, a network access device, and the like.
The electronic device 3 may also include, but is not limited to, any electronic product that can interact with a user through a keyboard, a mouse, a remote controller, a touch panel, or a voice control device, for example, a Personal computer, a tablet computer, a smart phone, a Personal Digital Assistant (PDA), a game machine, an Internet Protocol Television (IPTV), an intelligent wearable device, and the like. The Network where the electronic device 3 is located includes, but is not limited to, the internet, a wide area Network, a metropolitan area Network, a local area Network, a Virtual Private Network (VPN), and the like.
The at least one Processor 32 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a transistor logic device, a discrete hardware component, etc. The processor 32 may be a microprocessor or the processor 32 may be any conventional processor or the like, and the processor 32 is a control center of the electronic device 3 and connects various parts of the whole electronic device 3 by various interfaces and lines.
The memory 31 may be used to store the computer program 33 and/or the module/unit, and the processor 32 may implement various functions of the electronic device 3 by running or executing the computer program and/or the module/unit stored in the memory 31 and calling data stored in the memory 31. The memory 31 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to the use of the electronic device 3, and the like. In addition, the memory 31 may include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Memory Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, and the like.
With reference to fig. 1, the memory 31 of the electronic device 3 stores a plurality of instructions to implement a data resolution method, and the processor 32 can execute the plurality of instructions to implement:
acquiring data to be settled through a system interface and a preset data warehouse;
performing settlement on the data to be settled according to a preset first settlement formula to obtain settlement data;
checking the settlement data to obtain a checking result, wherein the checking mode comprises checking according to a preset checking formula and/or a preset access rule and/or table connection operation;
if the check result is passed, summarizing the settlement data to obtain summarized data;
and sending the summarized data to a preset terminal.
Specifically, the processor 32 may refer to the description of the relevant steps in the embodiment corresponding to fig. 1 for a specific implementation method of the instruction, which is not described herein again.
In the electronic device 3 described in fig. 3, the data to be resolved can be resolved according to a preset first resolving formula through an artificial intelligence technique, and then verified, the resolved data that passes verification is summarized and reported (the summarized data is sent to a preset device terminal), so that the accuracy of the resolved data is ensured, and the data resolving efficiency is also improved.
The integrated modules/units of the electronic device 3 may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as separate products. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program code may be in source code form, object code form, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
Further, the computer usable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the blockchain node, and the like.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
In the embodiments provided in the present invention, it should be understood that the disclosed system, 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 modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules 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 modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules 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, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A data resolution method, characterized in that said data resolution method comprises:
acquiring data to be settled through a system interface and a preset data warehouse;
performing settlement on the data to be settled according to a preset first settlement formula to obtain settlement data;
checking the settlement data to obtain a checking result, wherein the checking mode comprises checking according to a preset checking formula and/or a preset access rule and/or table connection operation;
if the check result is passed, summarizing the settlement data to obtain summarized data;
and sending the summarized data to a preset terminal.
2. A data resolution method according to claim 1, wherein said checking said resolution data and obtaining a checking result comprises:
according to the first settlement formula, performing settlement again on the data to be settled to obtain first check data;
judging whether the settlement data is consistent with the first check data or not;
if the settlement data is consistent with the first check data, determining that the check result is passed; or
And if the decision making data is inconsistent with the first check data, determining that the check result is not passed.
3. A data resolution method according to claim 1, wherein said resolution data is of a plurality of types, and said checking said resolution data to obtain a check result comprises:
acquiring a preset numerical threshold range corresponding to settlement data by adopting a preset access rule aiming at each type of settlement data;
judging whether the settlement data is in the preset value threshold range or not;
if the settlement data is within the preset value threshold range, determining that the checking result is passed; or
And if the decision-making data is not in the preset value threshold range, determining that the check result is not passed.
4. A data resolution method according to claim 1, wherein said checking said resolution data and obtaining a checking result comprises:
acquiring target data from a data interface or a data table specified by the access rule according to the access rule;
determining second check data corresponding to the target data according to a second decision formula corresponding to the target data in the check formulas;
determining data to be checked corresponding to the target data from the settlement data;
performing table linkage on the target data, the second check data and the data to be checked to obtain a target data table;
inquiring whether a target row exists in the target data table or not, wherein second check data corresponding to the target row are inconsistent with data to be checked corresponding to the target row;
if the target data table does not have a target row, determining that the verification result is passed; and if the target row exists in the target data table, determining that the verification result is failed.
5. A data resolution method as defined in claim 4, wherein the data resolution method further comprises:
if the verification result is that the verification result does not pass, generating alarm information;
and sending the alarm information to a terminal of a manager.
6. A data resolution method according to any one of claims 1 to 5, characterized in that the data to be resolved comprises first data to be resolved and second data to be resolved, the data resolution method further comprising:
acquiring data to be settled which is not input into a system;
preprocessing the data to be settled which are not input into the system to obtain preprocessed data;
storing the preprocessed data in the data repository;
the acquiring the data to be settled through the system interface and the preset data warehouse comprises:
acquiring the first data to be settled through the system interface;
and querying and acquiring the second data to be settled from the preprocessed data through the data warehouse.
7. A data resolution method according to any one of claims 1 to 5, characterized in that it further comprises:
when a data analysis instruction is received, determining the source of the data to be resolved;
generating a first table according to the data to be settled;
in the first table, using a plurality of preset color blocks to mark data to be resolved from different sources to obtain a second table, wherein the data to be resolved from one source corresponds to one color block;
and outputting the second table.
8. A data resolution apparatus, characterized in that said data resolution apparatus comprises:
the acquisition module is used for acquiring data to be resolved through a system interface and a preset data warehouse;
the settlement module is used for performing settlement on the data to be settled according to a preset first settlement formula to obtain settlement data;
the checking module is used for checking the settlement data to obtain a checking result, wherein the checking mode comprises checking according to a preset checking formula and/or a preset access rule and/or table connection operation;
the summarizing module is used for summarizing the decision data to obtain summarized data if the checking result is that the check result passes;
and the sending module is used for sending the summarized data to a preset terminal.
9. An electronic device, comprising a processor and a memory, wherein the processor is configured to execute a computer program stored in the memory to implement the data voting method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that it stores at least one instruction which, when executed by a processor, implements a data voting method according to any one of claims 1 to 7.
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