CN115242349B - Enterprise-level data verification method, enterprise-level data verification device, computer equipment and storage medium - Google Patents
Enterprise-level data verification method, enterprise-level data verification device, computer equipment and storage medium Download PDFInfo
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- CN115242349B CN115242349B CN202210707584.0A CN202210707584A CN115242349B CN 115242349 B CN115242349 B CN 115242349B CN 202210707584 A CN202210707584 A CN 202210707584A CN 115242349 B CN115242349 B CN 115242349B
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- 238000000034 method Methods 0.000 title claims abstract description 30
- 238000013524 data verification Methods 0.000 title claims abstract description 22
- 230000007547 defect Effects 0.000 claims abstract description 90
- 230000002159 abnormal effect Effects 0.000 claims abstract description 46
- 238000012795 verification Methods 0.000 claims abstract description 45
- 238000004590 computer program Methods 0.000 claims description 11
- 230000005540 biological transmission Effects 0.000 abstract description 7
- 238000007726 management method Methods 0.000 description 1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
- H04L1/0041—Arrangements at the transmitter end
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
- H04L1/0056—Systems characterized by the type of code used
- H04L1/0061—Error detection codes
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Abstract
According to the enterprise data verification method, the device, the computer equipment and the storage medium, the verification identifier, the correction identifier and the defect identifier of the data transmitted by the enterprise data center are obtained, the normal data after verification are continuously transmitted according to the default circulation condition, the abnormal data are transmitted to the source node generating the data after being marked, the abnormal data are corrected according to the defect type by the source data node and then enter the enterprise data center again, the data transmission efficiency is improved, the verification rule can be updated timely in the actual process, and the effectiveness of data verification is guaranteed.
Description
Technical Field
The present invention relates to the field of industrial management, and in particular, to an enterprise-level data verification method, an enterprise-level data verification device, a computer device, and a storage medium.
Background
In calendar operation, a large amount of data is generated between departments within an enterprise, and in order to ensure the correctness and usability of the data, data verification needs to be performed on the business data before the data is used.
At present, each data in a data stream of a certain service is often sequentially circulated to a next node, when a certain data in the data stream is determined to be abnormal data, the abnormal data needs to be corrected, and then the subsequent data can be circulated, so that the transmission efficiency is low.
Disclosure of Invention
In order to solve the problems, the invention provides an enterprise-level data verification method, an enterprise-level data verification device, computer equipment and a storage medium.
The main content of the invention comprises:
the enterprise-level data verification method comprises the following steps:
verifying the data in the data stream transmitted by the enterprise data center according to the corresponding verification rule, and correspondingly marking the data as normal data and abnormal data according to the verification result;
transmitting the data marked as normal according to a default circulation condition;
transmitting the data marked as abnormal according to a feedback correction rule, wherein the feedback correction rule comprises the following steps:
replacing the source data node with the next node in the default circulation condition and transmitting;
determining the defect type of the abnormal data, eliminating the defects in a set mode, and transmitting the defect type to an enterprise data center according to a default circulation condition;
the source data node refers to a node generating certain data.
Preferably, verifying the data in the data stream transmitted from the enterprise data center according to the corresponding verification rule includes:
acquiring verification identifications of various data in a data stream transmitted to an enterprise data center by a plurality of data input ports;
and according to the verification identification, acquiring a corresponding verification rule, and verifying the data to be verified.
Preferably, determining the defect type of the abnormal data, and transmitting the defect to the enterprise data center according to a default circulation condition after eliminating the defect according to a set mode includes:
the source data node determines defect types of the abnormal data, wherein the defect types comprise data defects and rule defects;
and according to the defect type, the source data node eliminates the defect in a set mode, and identifies the abnormal data as corrected, so that the abnormal data enters the enterprise data center through the corresponding data input port.
Preferably, the source data node removing the defect in a set manner according to the defect type includes:
when the defect type is a data defect, the source data node corrects the abnormal data, marks the correction mark of the abnormal data as corrected, and changes the defect mark of the abnormal data into normal data so that the abnormal data enters an enterprise data center through a corresponding data input port;
when the defect type is a regular defect, the source data node corrects the abnormal data, marks the correction identification of the abnormal data as corrected, and enables the abnormal data to enter the enterprise data center through the corresponding data input port.
Preferably, the verification of the data in the data stream transmitted from the enterprise data center according to the corresponding verification rule further comprises:
acquiring a correction identifier of data to be verified;
when the correction mark of the data to be verified is uncorrected, acquiring a corresponding verification rule, and verifying the data to be verified;
and when the correction mark of the data to be verified is corrected, acquiring the defect mark of the verification data, and verifying the data to be verified according to the corresponding defect mark.
Preferably, when the correction identifier of the data to be verified is corrected, a defect identifier of the verification data is obtained, and the data to be verified is verified according to the corresponding defect identifier, including:
when the defect mark is normal data, acquiring a corresponding check rule, and checking the data to be checked;
when the defect mark is a rule defect, correcting the defect mark into normal data, acquiring a corresponding check rule, and checking the data to be checked.
Preferably, when the defect identifier is a rule defect, correcting the defect identifier to be normal data, acquiring a corresponding check rule, and checking the data to be checked, wherein the method comprises correcting the defect identifier to be normal data after the corresponding check rule is modified and correcting the defect identifier to be normal data after the corresponding check rule is not modified.
The invention also provides an enterprise-level data verification device, which comprises:
the data generation modules are used for generating data to be verified;
the data generating modules transmit data to be verified to the enterprise data center through corresponding data input ports;
and the rule checking module is used for checking the data to be checked in the data stream transmitted by the enterprise data center according to the checking method.
The invention also provides a computer device, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the verification method when executing the computer program.
Furthermore, the invention proposes a computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the verification method described above.
The enterprise data verification method, the enterprise data verification device, the computer equipment and the storage medium have the advantages that normal data after verification are continuously transmitted according to default circulation conditions, abnormal data are transmitted to a source node generating the data after being marked, the abnormal data are corrected according to defect types by the source data node and then enter an enterprise data center again, the data transmission efficiency is improved, verification rules can be updated in time in an actual process, and the effectiveness of data verification is guaranteed.
Drawings
FIG. 1 is a flow chart of the verification of the present invention.
Detailed Description
The technical scheme protected by the invention is specifically described below with reference to the accompanying drawings.
The invention provides an enterprise-level data verification device, which comprises:
the data generation modules are used for generating data to be verified;
the data generating modules transmit data to be verified to the enterprise data center through corresponding data input ports;
and the rule checking module is used for checking the data to be checked in the data stream transmitted by the enterprise data center according to the checking method.
Please refer to fig. 1. The invention provides an enterprise data verification method, which is used for carrying out circulation transmission after verifying a data flow of an enterprise data center, wherein abnormal data found in the verification process is corrected by a source data node, normal data is continuously transmitted to a next node, the corrected source data node enters the enterprise data center indiscriminately again and waits for further verification, and the abnormal data can be continuously transmitted to the next node after verification.
The enterprise data center establishes a data transmission channel with each service department through a plurality of data input nodes, namely each service department serves as a source data generation node, service data generated by the service departments are transmitted to the enterprise data center in an indiscriminate mode, the enterprise data center transmits corresponding service data according to a set circulation condition according to a service circulation request, data transmitted by the enterprise data center are checked through a rule check module, and different data are processed in a targeted mode according to a check result. The data transmitted by the enterprise data center is called to-be-checked data, and the to-be-checked data has check identification information, including but not limited to information such as report name, report type, report number, check rule number and the like, and is used for indicating the generation address of the to-be-checked data, the membership of the to-be-checked data and the corresponding check rule. The data to be checked also has a correction identifier and a defect identifier, wherein the correction identifier is used for indicating whether the data is corrected, and the defect identifier is used for indicating whether the data is normal data and the defect type of abnormal data. Defect identifiers of data entering the enterprise data center for the first time are all defaults to normal data, and defect identifiers of corrected data can be normal data or regular defect data.
Specifically, the enterprise-level data verification method of the invention comprises the following steps:
firstly, each source data node, namely each service department transmits the corresponding data stream to an enterprise data center through a corresponding data input interface, the data in each data stream is transmitted to the next node according to a default circulation condition, and the corresponding verification of the data is required before the data is transmitted to the next node.
The rule checking module acquires the check mark of each data, checks the data according to the corresponding check rule, and marks the corresponding data as normal data and abnormal data according to the check result. Specifically, the rule checking module may first obtain a correction identifier corresponding to the data to be checked, and determine whether the corrected data is data that enters the enterprise data center again; if the corrected data to be checked is corrected, the defect identification of the data is required to be obtained, and at the moment, two conditions exist, and the treatment modes of different conditions are different.
When the defect mark is normal data, the source data node corrects the data according to the verification rule, and the data can be verified according to the verification rule without difference.
When the defect is identified as a rule defect, that is, the source data node considers that the data itself has no defect, the rule checking module needs to determine whether to correct the corresponding checking rule. After the rule checking module obtains the defect identification, checking a corresponding checking rule, if the corresponding checking rule is selected to be corrected, modifying the defect identification of the data into normal data by the rule checking module, and then continuing checking according to the corresponding checking rule; if the rule checking module refuses to modify the corresponding checking rule, the rule checking module still modifies the defect identifier of the data into normal data so that the normal data and other data participate in checking together.
The rule checking module is used for indifferently treating all data, acquiring a corresponding checking rule according to the checking identification of the data to be checked, checking the corresponding data, and marking the data as normal data and abnormal data according to the checking result, wherein in one embodiment, the rule checking module can mark the defect identification of the data, and the checking rule is in a standard data form. Transmitting the data marked as normal according to a default circulation condition, namely transmitting unimpeded circulation to the next node according to a preset circulation condition; and transmitting the data marked as abnormal according to a feedback correction rule, namely, correcting the default circulation condition of the data to circulate to the source data node, namely, correcting the abnormal data by the source data node for generating the data for the data which is found to be abnormal, so that the circulation of normal data is not influenced, and the efficiency of data transmission is ensured.
The source data node receives the fed back abnormal data, determines the defect type of the abnormal data, eliminates the defects according to a set mode and then transmits the defect type to the enterprise data center according to a default circulation condition; if the source data node considers that the data has defects, the data is corrected according to the corresponding requirements, and the defect identification of the data is corrected to be normal data after the correction; if the source data node considers that the data itself does not have any defect, or considers that the data itself accords with the fact that the data itself does not need to be changed, the defect identification of the data is marked as a rule defect, the rule checking module determines whether the rule needs to be corrected, and corresponding processing of the rule checking module is as described above and is not repeated here.
According to the verification method provided by the invention, the abnormal data after verification is directly fed back to the source data node for correction, and the defect identification is given only by the rule verification module, so that no correction processing is performed, normal circulation of normal data is not blocked, and the data transmission efficiency is improved. Meanwhile, the source data node is used for correcting the abnormal data in view of the fact that the source data node, namely the data generating node, is the best known in data attribute, so that the data correction efficiency is improved to a certain extent, and the data correction accuracy is guaranteed.
In addition, the invention also provides computer equipment, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the verification method when executing the computer program.
The invention also proposes a computer readable storage medium on which a computer program is stored which, when executed by a processor, performs the steps of the verification method described above.
The foregoing description is only illustrative of the present invention and is not intended to limit the scope of the invention, and all equivalent structures or equivalent processes or direct or indirect application in other related technical fields are included in the scope of the present invention.
Claims (9)
1. The enterprise-level data verification method is characterized by comprising the following steps of:
verifying the data in the data stream transmitted by the enterprise data center according to the corresponding verification rule, and correspondingly marking the data as normal data and abnormal data according to the verification result;
transmitting the data marked as normal according to a default circulation condition;
transmitting the data marked as abnormal according to a feedback correction rule, wherein the feedback correction rule comprises the following steps:
replacing the source data node with the next node in the default circulation condition and transmitting;
determining the defect type of the abnormal data, eliminating the defects in a set mode, and transmitting the defect type to an enterprise data center according to a default circulation condition;
the source data node refers to a node generating certain data;
verifying the data in the data stream transmitted by the enterprise data center according to the corresponding verification rule, and further comprising:
acquiring a correction identifier of data to be verified;
when the correction mark of the data to be verified is uncorrected, acquiring a corresponding verification rule, and verifying the data to be verified;
and when the correction mark of the data to be verified is corrected, acquiring the defect mark of the verification data, and verifying the data to be verified according to the corresponding defect mark.
2. The method for verifying an enterprise data stream as claimed in claim 1, wherein verifying the data in the data stream transmitted from the enterprise data center according to the corresponding verification rule comprises:
acquiring verification identifications of various data in a data stream transmitted to an enterprise data center by a plurality of data input ports;
and according to the verification identification, acquiring a corresponding verification rule, and verifying the data to be verified.
3. The method of claim 2, wherein determining the defect type of the abnormal data, and transmitting to the enterprise data center according to a default circulation condition after eliminating the defect according to a set manner comprises:
the source data node determines defect types of the abnormal data, wherein the defect types comprise data defects and rule defects;
and according to the defect type, the source data node eliminates the defect in a set mode, and identifies the abnormal data as corrected, so that the abnormal data enters the enterprise data center through the corresponding data input port.
4. The enterprise-level data verification method of claim 3, wherein the source data node eliminating the defect in a set manner based on the defect type comprises:
when the defect type is a data defect, the source data node corrects the abnormal data, marks the correction mark of the abnormal data as corrected, and changes the defect mark of the abnormal data into normal data so that the abnormal data enters an enterprise data center through a corresponding data input port;
when the defect type is a regular defect, the source data node corrects the abnormal data, marks the correction identification of the abnormal data as corrected, and enables the abnormal data to enter the enterprise data center through the corresponding data input port.
5. The method for verifying the enterprise data as set forth in claim 4, wherein when the correction identifier of the data to be verified is corrected, the defect identifier of the verification data is obtained, and the data to be verified is verified according to the corresponding defect identifier, comprising:
when the defect mark is normal data, acquiring a corresponding check rule, and checking the data to be checked;
when the defect mark is a rule defect, correcting the defect mark into normal data, acquiring a corresponding check rule, and checking the data to be checked.
6. The method according to claim 5, wherein when the defect is identified as a rule defect, correcting the defect identification to normal data, obtaining a corresponding verification rule, and verifying the data to be verified, including correcting the defect identification to normal data after the corresponding verification rule is modified and correcting the defect identification to normal data after the corresponding verification rule is not modified.
7. Enterprise-level data verification device, which is characterized by comprising:
the data generation modules are used for generating data to be verified;
the data generating modules transmit data to be verified to the enterprise data center through corresponding data input ports;
the rule checking module checks the data to be checked in the data stream transmitted by the enterprise data center according to the checking method as set forth in any one of claims 1 to 6.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the verification method of any one of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program when executed by a processor implements the steps of the verification method according to any one of claims 1 to 6.
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Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101324856A (en) * | 2008-08-07 | 2008-12-17 | 金蝶软件（中国）有限公司 | Method and system for upgrading data |
| CN101604336A (en) * | 2009-07-22 | 2009-12-16 | 河北省烟草公司承德市公司 | A kind of method and system that carries out data detection, correction from the source |
| CN102930373A (en) * | 2012-09-29 | 2013-02-13 | 河北省食品质量监督检验研究院 | Safety risk monitoring and early warning method for dairy products |
| CN103152198A (en) * | 2013-03-01 | 2013-06-12 | 北京百度网讯科技有限公司 | Micro-server-based automatic asset management method and device |
| US9244958B1 (en) * | 2013-06-13 | 2016-01-26 | Amazon Technologies, Inc. | Detecting and reconciling system resource metadata anomolies in a distributed storage system |
| CN106254045A (en) * | 2016-08-09 | 2016-12-21 | 中国银行股份有限公司 | A kind of data verification method and device |
| CN106600293A (en) * | 2016-12-09 | 2017-04-26 | 广州中国科学院软件应用技术研究所 | Automatic electronic food tracing data report terminal system |
| CN107220892A (en) * | 2017-05-27 | 2017-09-29 | 国家计算机网络与信息安全管理中心 | One kind melts data intelligence pretreating tool and method applied to magnanimity P2P net monetary allowances |
| CN109543942A (en) * | 2018-10-16 | 2019-03-29 | 平安普惠企业管理有限公司 | Data verification method, device, computer equipment and storage medium |
| CN110427361A (en) * | 2019-08-01 | 2019-11-08 | 万达信息股份有限公司 | A kind of method of quality control and system for medical data |
| CN110502531A (en) * | 2019-07-05 | 2019-11-26 | 招联消费金融有限公司 | Report data method of calibration, device, computer equipment and storage medium |
| WO2020232885A1 (en) * | 2019-05-22 | 2020-11-26 | 平安科技（深圳）有限公司 | Data inlink transaction processing method and device, computer device and storage medium |
| CN112231362A (en) * | 2020-10-29 | 2021-01-15 | 广东电网有限责任公司广州供电局 | Visual monitoring application system based on power grid main data service log |
| CN112817935A (en) * | 2021-01-22 | 2021-05-18 | 平安普惠企业管理有限公司 | Data processing method, device and equipment based on field type and storage medium |
| CN113312900A (en) * | 2021-06-17 | 2021-08-27 | 北京沃东天骏信息技术有限公司 | Data verification method and device |
| CN114549151A (en) * | 2021-12-16 | 2022-05-27 | 航天信息股份有限公司 | Enterprise financial auditing method and system |
-
2022
- 2022-06-21 CN CN202210707584.0A patent/CN115242349B/en active Active
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101324856A (en) * | 2008-08-07 | 2008-12-17 | 金蝶软件（中国）有限公司 | Method and system for upgrading data |
| CN101604336A (en) * | 2009-07-22 | 2009-12-16 | 河北省烟草公司承德市公司 | A kind of method and system that carries out data detection, correction from the source |
| CN102930373A (en) * | 2012-09-29 | 2013-02-13 | 河北省食品质量监督检验研究院 | Safety risk monitoring and early warning method for dairy products |
| CN103152198A (en) * | 2013-03-01 | 2013-06-12 | 北京百度网讯科技有限公司 | Micro-server-based automatic asset management method and device |
| US9244958B1 (en) * | 2013-06-13 | 2016-01-26 | Amazon Technologies, Inc. | Detecting and reconciling system resource metadata anomolies in a distributed storage system |
| CN106254045A (en) * | 2016-08-09 | 2016-12-21 | 中国银行股份有限公司 | A kind of data verification method and device |
| CN106600293A (en) * | 2016-12-09 | 2017-04-26 | 广州中国科学院软件应用技术研究所 | Automatic electronic food tracing data report terminal system |
| CN107220892A (en) * | 2017-05-27 | 2017-09-29 | 国家计算机网络与信息安全管理中心 | One kind melts data intelligence pretreating tool and method applied to magnanimity P2P net monetary allowances |
| CN109543942A (en) * | 2018-10-16 | 2019-03-29 | 平安普惠企业管理有限公司 | Data verification method, device, computer equipment and storage medium |
| WO2020232885A1 (en) * | 2019-05-22 | 2020-11-26 | 平安科技（深圳）有限公司 | Data inlink transaction processing method and device, computer device and storage medium |
| CN110502531A (en) * | 2019-07-05 | 2019-11-26 | 招联消费金融有限公司 | Report data method of calibration, device, computer equipment and storage medium |
| CN110427361A (en) * | 2019-08-01 | 2019-11-08 | 万达信息股份有限公司 | A kind of method of quality control and system for medical data |
| CN112231362A (en) * | 2020-10-29 | 2021-01-15 | 广东电网有限责任公司广州供电局 | Visual monitoring application system based on power grid main data service log |
| CN112817935A (en) * | 2021-01-22 | 2021-05-18 | 平安普惠企业管理有限公司 | Data processing method, device and equipment based on field type and storage medium |
| CN113312900A (en) * | 2021-06-17 | 2021-08-27 | 北京沃东天骏信息技术有限公司 | Data verification method and device |
| CN114549151A (en) * | 2021-12-16 | 2022-05-27 | 航天信息股份有限公司 | Enterprise financial auditing method and system |
Non-Patent Citations (2)
| Title |
|---|
| Xingyue Chen ; Tao Shang ; Ilryong Kim ; Jianwei Liu.A Remote Data Integrity Checking Scheme for Big Data Storage.《 2017 IEEE Second International Conference on Data Science in Cyberspace (DSC)》.2017,全文. * |
| 曾庆妍 ; 王浩 ; .监管报送数据质量平台的设计与实现.信息技术与信息化.2020,(第01期),全文. * |
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