Data verification method, device, equipment and storage medium

Abstract

The present invention discloses a data verification method, device, equipment and storage medium. The present invention searches for a corresponding logical relationship chain in a preset business logic network according to the data to be verified, and the preset business logic network is constructed based on the logical relationship between historical business data, and then obtains the relationship chain to be verified corresponding to the data to be verified, and compares the relationship chain to be verified with the logical relationship chain to obtain a comparison result, and then selects target verification data from the data to be verified according to the comparison result, and then obtains standard data corresponding to the target verification data, and verifies the target verification data according to the standard data. The present invention can accurately find the logical relationship chain corresponding to the data to be verified, and accurately select the target verification data according to the comparison result between the relationship chain to be verified and the logical relationship chain, and then verify the target verification data according to the standard data, so that a large number of data to be verified can be verified through the preset business logic network.

Description

Technical Field

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

[0002] In data development work, long-term data verification work is usually accompanied by long-term testing and verification work before and after each data project goes online. This is an indispensable part of data projects. With the continuous development of Internet applications, the amount of data faced in the data verification process has become a huge challenge in the verification work. When the amount of data reaches tens of thousands, the operating efficiency of traditional verification tools will be greatly reduced. When faced with a database of tens of millions of data, it is even more powerless and can only rely on manual verification, which greatly consumes labor costs. Therefore, how to accurately verify large quantities of data has become a problem that needs to be solved urgently.

[0003] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of the present invention is to provide a data verification method, device, equipment and storage medium, aiming to solve the technical problem of how to accurately verify large quantities of data.

[0005] To achieve the above object, the present invention provides a data verification method, which comprises:

[0006] Searching for a corresponding logical relationship chain in a preset business logic network according to the data to be checked, wherein the preset business logic network is constructed based on the logical relationship between historical business data;

[0007] Acquire the to-be-checked relationship chain corresponding to the to-be-checked data, and compare the to-be-checked relationship chain with the logical relationship chain to obtain a comparison result;

[0008] Selecting target verification data from the data to be verified according to the comparison result;

[0009] Acquire standard data corresponding to the target verification data, and verify the target verification data according to the standard data.

[0010] Optionally, before the step of searching for a corresponding logical relationship chain in a preset business logic network according to the data to be checked, and constructing the preset business logic network based on the logical relationship between historical business data, the step further includes:

[0011] Acquire the logical relationship between historical business data, and determine the logical relationship chain according to the logical relationship;

[0012] Selecting the data to be checked from the massive data according to the logical relationship chain;

[0013] The data to be checked are checked in batches with preset standard data to obtain data checking results, and the process returns to the step of selecting the data to be checked from the massive data according to the logical relationship chain;

[0014] After completing the preset number of data checks, the preset business logic network is determined according to the obtained data check results.

[0015] Optionally, the step of acquiring the logical relationship between the historical business data and determining the logical relationship chain according to the logical relationship specifically includes:

[0016] Split historical business data and store the split data in a distributed non-relational database;

[0017] Obtaining business relationship information and business significance information corresponding to the split data;

[0018] The historical data is associated and matched according to the business relationship information and the business significance information to obtain a logical relationship, and a logical relationship chain is determined according to the logical relationship.

[0019] Optionally, the step of splitting the historical business data and storing the split data in a distributed non-relational database specifically includes:

[0020] Get the data type corresponding to the historical business data;

[0021] Classifying the historical business data according to the data type to obtain different types of data sets;

[0022] Acquire the data volume of each data set, and split each data set according to the data volume to obtain the split data sets;

[0023] The split data set is stored in a distributed non-relational database.

[0024] Optionally, the step of selecting the data to be checked from the massive data according to the logical relationship chain specifically includes:

[0025] Obtain the initial logical relationship chain between the massive amounts of data collected;

[0026] Comparing the logical relationship chain with the initial logical relationship chain to obtain a relationship comparison result;

[0027] The data to be checked is selected from the massive data according to the relationship comparison result.

[0028] Optionally, after completing the preset number of data checks, the step of determining the preset service logic network according to the obtained data check results specifically includes:

[0029] After completing the preset number of data checks, an initial business logic network is generated according to the obtained data check results;

[0030] Acquire the unconventional report and unstructured data input by the business personnel, and add the unconventional report and the unstructured data to the initial business logic network to obtain the association point;

[0031] The initial business logic network is integrated according to the association points to obtain a preset business logic network.

[0032] Optionally, after completing the preset number of data checks, the step of generating an initial business logic network according to the obtained data check results specifically includes:

[0033] After completing the preset number of data checks, obtaining the same batch of data sets to be checked in different order data check processes;

[0034] Obtain all data verification results corresponding to all the data to be verified in the data set to be verified;

[0035] Determine the number of results in different preset areas according to all data verification results, wherein the preset areas are areas divided based on the data verification results;

[0036] Obtain target data verification results corresponding to the number of results that meet the preset quantity conditions, and obtain the data to be verified corresponding to the target data verification results;

[0037] The logical relationship chain is updated according to the data to be checked to obtain an updated logical relationship chain;

[0038] An initial business logic network is generated according to the updated logic relationship chain.

[0039] In addition, to achieve the above object, the present invention also provides a data checking device, the data checking device comprising:

[0040] A chain search module, used to search for a corresponding logical relationship chain in a preset business logic network according to the data to be checked, wherein the preset business logic network is constructed based on the logical relationship between historical business data;

[0041] A relationship comparison module, used for obtaining the to-be-checked relationship chain corresponding to the to-be-checked data, and comparing the to-be-checked relationship chain with the logical relationship chain to obtain a comparison result;

[0042] A data selection module, used for selecting target verification data from the data to be verified according to the comparison result;

[0043] The data verification module is used to obtain standard data corresponding to the target verification data and verify the target verification data according to the standard data.

[0044] In addition, to achieve the above-mentioned purpose, the present invention also proposes a data verification device, which includes: a memory, a processor, and a data verification program stored in the memory and executable on the processor, and the data verification program is configured to implement the data verification method described above.

[0045] In addition, to achieve the above-mentioned purpose, the present invention further proposes a storage medium, on which a data verification program is stored, and when the data verification program is executed by a processor, the data verification method as described above is implemented.

[0046] The present invention searches for the corresponding logical relationship chain in the preset business logic network according to the data to be checked, and the preset business logic network is constructed based on the logical relationship between historical business data, and then obtains the relationship chain to be checked corresponding to the data to be checked, and compares the relationship chain to be checked with the logical relationship chain to obtain the comparison result, and then selects the target verification data from the data to be checked according to the comparison result, and then obtains the standard data corresponding to the target verification data, and verifies the target verification data according to the standard data. The present invention searches for the logical relationship chain corresponding to the data to be checked in the preset business logic network, and the preset business logic network is constructed based on the logical relationship between historical business data, and can accurately find the logical relationship chain corresponding to the data to be checked, and then selects the target verification data from the data to be checked according to the comparison result between the relationship chain to be checked and the logical relationship chain, and can accurately select the target verification data, and then verify the target verification data according to the standard data, so that a large number of data to be checked can be verified through the preset business logic network. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a structural schematic diagram of a data checking device of a hardware operating environment involved in an embodiment of the present invention;

[0048] Figure 2 A schematic diagram of a flow chart of a first embodiment of a data checking method of the present invention;

[0049] Figure 3 A schematic diagram of a flow chart of a second embodiment of a data checking method of the present invention;

[0050] Figure 4 A schematic diagram of a flow chart of a third embodiment of a data checking method of the present invention;

[0051] Figure 5 It is a structural block diagram of the first embodiment of the data checking device of the present invention.

[0052] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0053] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0054] Reference Figure 1 , Figure 1 The present invention is a schematic diagram of the structure of a data checking device in a hardware operating environment according to an embodiment of the present invention.

[0055] like Figure 1 As shown, the data verification device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM), or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0056] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the data checking device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0057] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module and a data checking program.

[0058] exist Figure 1In the data verification device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the data verification device of the present invention can be set in the data verification device, and the data verification device calls the data verification program stored in the memory 1005 through the processor 1001, and executes the data verification method provided by the embodiment of the present invention.

[0059] The present invention provides a data verification method, referring to Figure 2 , Figure 2 Schematic diagram of the flow of the first embodiment of the data checking method of the present invention.

[0060] In this embodiment, the data verification method includes the following steps:

[0061] Step S10: searching for a corresponding logical relationship chain in a preset business logic network according to the data to be checked, wherein the preset business logic network is constructed based on the logical relationship between historical business data;

[0062] It should be noted that the execution subject of this embodiment can be the above-mentioned data verification device with network communication and program running functions, or it can be other devices that can achieve the same or similar functions. This embodiment does not impose specific restrictions on this.

[0063] It is understandable that the preset business logic network refers to a pre-built business logic network, which is specifically built based on the logical relationship between historical business data. Historical business data refers to data within a preset time period, and the logical relationship refers to the relationship between each data in the historical business data, for example: historical business data is added by 1 in sequence, historical business data is subtracted by 1 in sequence, etc. The specific logical relationship needs to be obtained based on the actual historical business data.

[0064] It should be understood that the preset business logic relationship network is composed of multiple logic relationship chains, and the logic relationship chains include data and logical relationships between data.

[0065] Step S20: obtaining the to-be-checked relationship chain corresponding to the to-be-checked data, and comparing the to-be-checked relationship chain with the logical relationship chain to obtain a comparison result;

[0066] It is understandable that there is also a chain of relationships to be verified between the data to be verified. For example, if the data to be verified is 1, 3, 3, 4, 5..., then the chain of relationships to be verified is the first data to the second data plus 2, the second data to the third data plus 0, the third data to the fourth data plus 1, and the fourth data to the fifth data plus 1.

[0067] In a specific implementation, assuming that the logical relationship chain is the first data to the second data plus 1, the second data to the third data plus 1, etc., then the comparison result is that the logical relationship between the first data to the second data and the second data to the third data is different.

[0068] Step S30: selecting target verification data from the data to be verified according to the comparison result;

[0069] It should be noted that the target verification data refers to the data that needs to be verified among the data to be verified.

[0070] In a specific implementation, target verification data can be selected from the data to be verified based on the comparison result. For example, if the comparison result shows that the logical relationship between the first data to the second data and the logical relationship between the second data to the third data is different, it means that the target verification data is the second data, i.e., 3.

[0071] Step S40: Acquire standard data corresponding to the target verification data, and verify the target verification data according to the standard data.

[0072] It is understandable that the standard data can be obtained from the logical relationship chain, or can be pre-set data. By comparing the standard data with the target verification data, the verification result can be obtained and feedback can be provided.

[0073] This embodiment searches for the corresponding logical relationship chain in the preset business logic network according to the data to be checked, and the preset business logic network is constructed based on the logical relationship between historical business data, and then obtains the relationship chain to be checked corresponding to the data to be checked, and compares the relationship chain to be checked with the logical relationship chain to obtain the comparison result, and then selects the target verification data from the data to be checked according to the comparison result, and then obtains the standard data corresponding to the target verification data, and verifies the target verification data according to the standard data. This embodiment searches for the logical relationship chain corresponding to the data to be checked in the preset business logic network, and the preset business logic network is constructed based on the logical relationship between historical business data, so that the logical relationship chain corresponding to the data to be checked can be accurately found, and then the target verification data can be selected from the data to be checked according to the comparison result between the relationship chain to be checked and the logical relationship chain, and the target verification data can be accurately selected, and then the target verification data can be verified according to the standard data, so that a large number of data to be checked can be verified through the preset business logic network.

[0074] refer to Figure 3 , Figure 3 FIG. 4 is a flow chart of a second embodiment of a data checking method according to the present invention.

[0075] Based on the first embodiment above, in this embodiment, before step S10, the following steps are further included:

[0076] Step S00: obtaining the logical relationship between historical business data, and determining the logical relationship chain according to the logical relationship;

[0077] Furthermore, in order to accurately determine the logical relationship chain, in this embodiment, the step S00 includes: splitting the historical business data and storing the split data in a distributed non-relational database; obtaining the business relationship information and business significance information corresponding to the split data; correlating and matching the historical business data according to the business relationship information and the business significance information to obtain the logical relationship, and determining the logical relationship chain according to the logical relationship.

[0078] It should be noted that a distributed non-relational database refers to a lightweight, open source, SQL-incompatible relational database, a non-relational, distributed, and non-ACID (the four basic elements of database transaction processing) database design pattern. Common non-relational databases include Redis, Amazon DynamoDB, Memcached, Microsoft Azure Cosmos DB, and Hazelcast. This embodiment does not specifically limit the type of distributed non-relational databases.

[0079] It is understandable that business relationship information refers to the relationship between the split data, such as the relationship between age and gender. Business meaning information refers to the meaning of the split data, such as age, gender, etc.

[0080] In the specific implementation, after obtaining the business relationship information and business significance information corresponding to each type of data after the split, the historical business data can be associated and matched according to the business relationship information and business significance information to obtain the logical relationship, and then the logical relationship chain can be determined based on the logical relationship.

[0081] Furthermore, in order to accurately split the historical business data, in this embodiment, the steps of splitting the historical business data and storing the split data in a distributed non-relational database specifically include: obtaining the data type corresponding to the historical business data; classifying the historical business data according to the data type to obtain different types of data sets; obtaining the data volume of each data set, and splitting each data set according to the data volume to obtain split data sets; and storing the split data sets in a distributed non-relational database.

[0082] It should be noted that the data types may include: auto insurance data type, life insurance data type, etc., and this embodiment does not impose any specific restrictions on this.

[0083] It is understandable that after the data type corresponding to the historical business data is obtained, the historical business data can be classified according to the data type to obtain different types of data sets, which contain all historical business data of each type.

[0084] In a specific implementation, after obtaining different types of data sets, the amount of data in each data set can be obtained, and then each data set can be split according to the data amount. The larger the data amount, the more data sets there are after the split. The correspondence between the specific data amount and the number of data sets after the split can be set according to the actual situation, and this embodiment does not impose specific restrictions on this.

[0085] This embodiment classifies historical business data according to data type and then splits each data set according to data volume, so that historical business data can be accurately split and stored in a distributed non-relational database.

[0086] Step S01: selecting data to be checked from the massive data according to the logical relationship chain;

[0087] Furthermore, in order to accurately select the data to be checked, in this embodiment, the step S01 includes: obtaining the initial logical relationship chain between the collected massive data; comparing the logical relationship chain with the initial logical relationship chain to obtain a relationship comparison result; and selecting the data to be checked from the massive data based on the relationship comparison result.

[0088] It should be noted that the massive data refers to a large amount of data collected randomly, and the initial logical relationship chain refers to a chain formed based on the logical relationship between the massive data. The relationship comparison result refers to the difference between the logical relationship chain and the initial logical relationship chain. The data to be verified refers to the data that needs to be verified in the massive data.

[0089] In the specific implementation, the logical relationship chain between the historical business data can be compared with the logical relationship chain between the mass data to obtain the relationship comparison result, and then the data to be checked can be selected from the mass data according to the relationship comparison result. For example: the mass data is 1, 2, 3, 4, 5..., then the initial logical relationship chain between the mass data is each data plus 1, assuming that the logical relationship chain is each data multiplied by 2, then the third data, the fourth data, and the fifth data are all data to be checked.

[0090] Step S02: Check the data to be checked against the preset standard data in batches to obtain data checking results, and return to the step of selecting the data to be checked from the massive data according to the logical relationship chain;

[0091] It should be noted that the preset standard data is pre-set standard data used to check with the data to be checked, and the standard data may be data thresholds corresponding to different business relationship information.

[0092] It is understandable that when the amount of data to be checked is large, the data can be checked in batches to improve data checking efficiency.

[0093] In a specific implementation, after completing a data check, it is necessary to return to the step of selecting the data to be checked from the massive data according to the logical relationship chain. The collected massive data can change continuously, and the corresponding data to be checked also changes continuously, so multiple data checks can be completed.

[0094] Step S03: After completing the preset number of data checks, a preset business logic network is determined according to the obtained data check results.

[0095] It should be noted that the preset number of times refers to the number of pre-set data verification times, for example: 10 times, 20 times, etc., and this embodiment does not impose any specific limitation on this.

[0096] It should be understood that the data verification results obtained refer to the data verification results obtained in each data verification process.

[0097] This embodiment obtains the logical relationship between historical business data, determines the logical relationship chain according to the logical relationship, then selects the data to be checked from the massive data according to the logical relationship chain, and then checks the data to be checked with the preset standard data in batches to obtain the data verification result, and returns to the step of selecting the data to be checked from the massive data according to the logical relationship chain. After completing the preset number of data checks, the preset business logic network is determined according to the obtained data verification results. This embodiment selects the data to be checked from the massive data according to the logical relationship chain, can accurately obtain the data to be checked, and then checks the data to be checked with the preset standard data in batches, can improve the efficiency of data verification, and performs the preset number of data checks, determines the preset business logic network according to the obtained data verification results, and can determine the preset business logic network according to the data verification results obtained after performing multiple data checks, so that the business logic network can be accurately obtained.

[0098] refer to Figure 4 , Figure 4 Schematic diagram of the flow chart of the third embodiment of the data checking method of the present invention.

[0099] Based on the above embodiments, in this embodiment, step S03 includes:

[0100] Step S031: after completing a preset number of data checks, generating an initial business logic network according to the obtained data check results;

[0101] Furthermore, in order to accurately generate the initial business logic network, in this embodiment, the step S031 includes: after completing a preset number of data verifications, obtaining a set of data to be verified in the same batch in a data verification process of different orders; obtaining all data verification results corresponding to all data to be verified in the set of data to be verified; determining the number of results in different preset areas based on all data verification results, and the preset areas are areas divided based on data verification results; obtaining target data verification results corresponding to the number of results that meet a preset quantity condition, and obtaining the data to be verified corresponding to the target data verification results; updating the logical relationship chain according to the data to be verified to obtain an updated logical relationship chain; and generating the initial business logic network according to the updated logical relationship chain.

[0102] It should be noted that, since the amount of data to be checked may be too large, it is necessary to check in batches. The set of data to be checked in the same batch during the data checking process of different orders refers to the set of data to be checked in the same batch during the data checking process of different orders. The preset area is an area divided based on the data checking result, for example: [1,5], [6,10], etc., and this embodiment does not make specific restrictions on this.

[0103] It is understandable that each data to be checked corresponds to a data check result, so all data check results corresponding to all data to be checked in the set of data to be checked can be obtained. For each data check result, it can be determined which preset area the data check result is in. For example, when the data check result is 5, it can be determined that the preset area is [1,5]. For each preset area, there are multiple data check results corresponding to the data check results, and the number of data check results is the number of results in this embodiment.

[0104] It should be understood that the preset quantity condition is a preset quantity threshold of data verification results, for example, greater than 20, which can be set according to actual conditions, and this embodiment does not impose specific restrictions on this.

[0105] In a specific implementation, a preset area that meets a preset quantity condition can be obtained, and based on the preset area, all data verification results in the preset area, that is, the target data verification results, can be obtained, and the data to be verified corresponding to the target data verification results can be obtained. The logical relationship chain can be updated based on the data to be verified. The specific updating method can be to take the average value of all the data to be verified in the preset area, or other updating methods. This embodiment does not impose any specific restrictions on this.

[0106] This embodiment obtains the target data verification results corresponding to the number of results that meet the preset quantity conditions, obtains the data to be verified corresponding to the target data verification results, and then updates the logical relationship chain according to the data to be verified. When the number of results in a certain preset area is large, the logical relationship chain can be updated in time.

[0107] Step S032: Acquire the unconventional report and unstructured data input by the business personnel, and add the unconventional report and the unstructured data to the initial business logic network to obtain association points;

[0108] It should be noted that unconventional reports refer to unconventional statistical reports obtained by business personnel after sorting and integrating business relationship information and business significance information, and unstructured data refers to data with irregular or incomplete data structure. Association points can refer to association points generated in data verification work based on business relationships in unconventional reports and unstructured data.

[0109] Step S033: Integrate the initial business logic network according to the association points to obtain a preset business logic network.

[0110] Further, in this embodiment, the step S033 includes: obtaining the first data location information of the association point in the initial business logic network and the second data location information of the association point in the new business logic network; analyzing the initial business logic network and the association point in the same dimension according to the first data location information and the second data location information to obtain the first data set and the second data set corresponding to each identical data location information; determining a new logical relationship chain according to the first data set and the second data set, and determining a preset business logic network according to the new logical relationship chain.

[0111] It should be noted that the new business logic network refers to an independent business logic network generated when a new verification logic that cannot be associated with the initial business logic network appears, that is, a new business logic network.

[0112] It is understandable that the first data location information refers to the location information of the association point in the initial logic network, for example: the third data in the third logical relationship chain, and the second data location information refers to the location information in the new business logic network.

[0113] It should be understood that after obtaining the first data location information and the second data location information, the initial business logic network and the association points can be analyzed in the same dimension, that is, the initial business logic network and the new business logic network can be superimposed and analyzed based on the association points, and the first data set and the second data set corresponding to each identical location information can be obtained. For example: the fourth data in the second logical relationship chain in the initial business logic network and the fourth data in the second logical relationship chain in the new business logic network can be obtained.

[0114] In a specific implementation, the first data and the second data at the same position may be averaged to determine a new logical relationship chain, thereby determining a preset business logic network.

[0115] After completing the preset number of data checks, this embodiment generates an initial business logic network based on the obtained data check results, then obtains the unconventional reports and unstructured data input by the business personnel, and adds the unconventional reports and unstructured data to the initial business logic network to obtain the association points, and then integrates the initial business logic network according to the association points to obtain the preset business logic network. This embodiment integrates the initial business logic network according to the association points to obtain the preset business logic network, and can update the initial business logic network in time to obtain a more accurate preset business logic network, so that a large amount of data to be checked can be checked through the preset business logic network.

[0116] In addition, an embodiment of the present invention further provides a storage medium, on which a data verification program is stored. When the data verification program is executed by a processor, the data verification method as described above is implemented.

[0117] Reference Figure 5 , Figure 5 It is a structural block diagram of the first embodiment of the data checking device of the present invention.

[0118] like Figure 5 As shown, the data checking device proposed in the embodiment of the present invention includes:

[0119] A chain search module 10, for searching a corresponding logical relationship chain in a preset business logic network according to the data to be checked, wherein the preset business logic network is constructed based on the logical relationship between historical business data;

[0120] The relationship comparison module 20 is used to obtain the to-be-checked relationship chain corresponding to the to-be-checked data, and compare the to-be-checked relationship chain with the logical relationship chain to obtain a comparison result;

[0121] A data selection module 30, configured to select target verification data from the data to be verified according to the comparison result;

[0122] The data checking module 40 is used to obtain standard data corresponding to the target checking data and check the target checking data according to the standard data.

[0123] This embodiment searches for the corresponding logical relationship chain in the preset business logic network according to the data to be checked, and the preset business logic network is constructed based on the logical relationship between historical business data, and then obtains the relationship chain to be checked corresponding to the data to be checked, and compares the relationship chain to be checked with the logical relationship chain to obtain the comparison result, and then selects the target verification data from the data to be checked according to the comparison result, and then obtains the standard data corresponding to the target verification data, and verifies the target verification data according to the standard data. This embodiment searches for the logical relationship chain corresponding to the data to be checked in the preset business logic network, and the preset business logic network is constructed based on the logical relationship between historical business data, so that the logical relationship chain corresponding to the data to be checked can be accurately found, and then the target verification data can be selected from the data to be checked according to the comparison result between the relationship chain to be checked and the logical relationship chain, and the target verification data can be accurately selected, and then the target verification data can be verified according to the standard data, so that a large number of data to be checked can be verified through the preset business logic network.

[0124] Based on the above-mentioned first embodiment of the data checking device of the present invention, a second embodiment of the data checking device of the present invention is proposed.

[0125] In this embodiment, the data verification device also includes a logic network construction module 00, which is used to obtain the logical relationship between historical business data and determine the logic relationship chain based on the logic relationship; select the data to be verified from the massive data according to the logic relationship chain; verify the data to be verified with the preset standard data in batches to obtain data verification results, and return to the step of selecting the data to be verified from the massive data according to the logic relationship chain; after completing the preset number of data verifications, determine the preset business logic network according to the obtained data verification results.

[0126] Furthermore, the logic network construction module 00 is also used to split the historical business data and store the split data in a distributed non-relational database; obtain the business relationship information and business significance information corresponding to the split data; associate and match the historical data according to the business relationship information and the business significance information, obtain the logical relationship, and determine the logical relationship chain according to the logical relationship.

[0127] Furthermore, the logic network construction module 00 is also used to obtain the data type corresponding to the historical business data; classify the historical business data according to the data type to obtain different types of data sets; obtain the data volume of each data set, and split the each data set according to the data volume to obtain the split data sets; store the split data sets in a distributed non-relational database.

[0128] Furthermore, the logic network construction module 00 is also used to obtain an initial logic relationship chain between the collected massive data; compare the logic relationship chain with the initial logic relationship chain to obtain a relationship comparison result; and select the data to be checked from the massive data according to the relationship comparison result.

[0129] Furthermore, the logic network construction module 00 is also used to generate an initial business logic network according to the obtained data verification results after completing a preset number of data verifications; obtain unconventional reports and unstructured data input by business personnel, and add the unconventional reports and the unstructured data to the initial business logic network to obtain association points; integrate the initial business logic network according to the association points to obtain a preset business logic network.

[0130] Furthermore, the logic network construction module 00 is also used to obtain a set of data to be checked in the same batch in a data verification process of different orders after completing a preset number of data verifications; obtain all data verification results corresponding to all data to be checked in the set of data to be checked; determine the number of results in different preset areas based on all data verification results, and the preset areas are areas divided based on data verification results; obtain target data verification results corresponding to the number of results that meet a preset quantity condition, and obtain the data to be checked corresponding to the target data verification results; update the logical relationship chain according to the data to be checked to obtain an updated logical relationship chain; and generate an initial business logic network according to the updated logical relationship chain.

[0131] Other embodiments or specific implementations of the data checking device of the present invention can refer to the above-mentioned method embodiments and will not be described in detail here.

[0132] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0133] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0134] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory / random access memory, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0135] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A data verification method, characterized in that: The data verification method comprises: Searching for a corresponding logical relationship chain in a preset business logic network according to the data to be checked, wherein the preset business logic network is constructed based on the logical relationship between historical business data; Acquire the to-be-verified relationship chain corresponding to the to-be-verified data, and compare the to-be-verified relationship chain with the logical relationship chain to obtain a comparison result; Selecting target verification data from the data to be verified according to the comparison result; Acquire standard data corresponding to the target verification data, and verify the target verification data according to the standard data; Before the step of searching for a corresponding logical relationship chain in a preset business logic network according to the data to be checked, wherein the preset business logic network is constructed based on the logical relationship between the historical business data, the step further includes: Acquire the logical relationship between historical business data, and determine the logical relationship chain according to the logical relationship; Selecting the data to be checked from the massive data according to the logical relationship chain; The data to be checked are checked in batches with preset standard data to obtain data checking results, and the process returns to the step of selecting the data to be checked from the massive data according to the logical relationship chain; After completing the preset number of data checks, the preset business logic network is determined according to the obtained data check results.

2. The data checking method according to claim 1, characterized in that: The step of obtaining the logical relationship between the historical business data and determining the logical relationship chain according to the logical relationship specifically includes: Split historical business data and store the split data in a distributed non-relational database; Obtaining business relationship information and business significance information corresponding to the split data; The historical business data is associated and matched according to the business relationship information and the business significance information to obtain a logical relationship, and a logical relationship chain is determined according to the logical relationship.

3. The data checking method according to claim 2, characterized in that: The step of splitting the historical business data and storing the split data in the distributed non-relational database specifically includes: Get the data type corresponding to the historical business data; Classifying the historical business data according to the data type to obtain different types of data sets; Acquire the data volume of each data set, and split each data set according to the data volume to obtain the split data sets; The split data set is stored in a distributed non-relational database.

4. The data checking method according to claim 1, characterized in that: The step of selecting the data to be checked from the massive data according to the logical relationship chain specifically includes: Obtain the initial logical relationship chain between the massive amounts of data collected; Comparing the logical relationship chain with the initial logical relationship chain to obtain a relationship comparison result; The data to be checked is selected from the massive data according to the relationship comparison result.

5. The data checking method according to claim 1, characterized in that: After completing the preset number of data checks, the step of determining the preset service logic network according to the obtained data check results specifically includes: After completing the preset number of data checks, an initial business logic network is generated according to the obtained data check results; Acquire the unconventional report and unstructured data input by the business personnel, and add the unconventional report and the unstructured data to the initial business logic network to obtain the association point; The initial business logic network is integrated according to the association points to obtain a preset business logic network.

6. The data checking method according to claim 5, characterized in that: After completing the preset number of data checks, the step of generating an initial business logic network according to the obtained data check results specifically includes: After completing the preset number of data checks, obtaining the same batch of data sets to be checked in different order data check processes; Obtain all data verification results corresponding to all the data to be verified in the data set to be verified; Determine the number of results in different preset areas according to all data verification results, wherein the preset areas are areas divided based on the data verification results; Obtain target data verification results corresponding to the number of results that meet the preset quantity conditions, and obtain the data to be verified corresponding to the target data verification results; The logical relationship chain is updated according to the data to be checked to obtain an updated logical relationship chain; An initial business logic network is generated according to the updated logic relationship chain.

7. A data checking device, characterized in that: The data checking device comprises: A chain search module, used to search for a corresponding logical relationship chain in a preset business logic network according to the data to be checked, wherein the preset business logic network is constructed based on the logical relationship between historical business data; A relationship comparison module, used for obtaining the to-be-checked relationship chain corresponding to the to-be-checked data, and comparing the to-be-checked relationship chain with the logical relationship chain to obtain a comparison result; A data selection module, used for selecting target verification data from the data to be verified according to the comparison result; A data checking module, used for acquiring standard data corresponding to the target checking data, and checking the target checking data according to the standard data; The data verification device also includes a logic network construction module, which is used to obtain the logical relationship between historical business data and determine the logic relationship chain based on the logic relationship; select the data to be verified from the massive data according to the logic relationship chain; verify the data to be verified with the preset standard data in batches to obtain the data verification results, and return to the step of selecting the data to be verified from the massive data according to the logic relationship chain; after completing the preset number of data verifications, determine the preset business logic network according to the obtained data verification results.

8. A data checking device, characterized in that: The data checking device comprises: a memory, a processor, and a data checking program stored in the memory and executable on the processor, wherein the data checking program is configured to implement the data checking method according to any one of claims 1 to 6.

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

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