Data checking method and device based on data registration platform

Abstract

The invention provides a data auditing method and device based on a data registration platform, and relates to the technical field of intelligent auditing of the data registration platform, and the method comprises the steps: obtaining data filled by a user based on the data registration platform, and carrying out the preprocessing of the data, performing compliance detection and data quality detection on the preprocessed data, performing integration analysis on a compliance detection result and a data quality detection result to obtain a data analysis result, and obtaining a data auditing report based on the data analysis result, the data auditing report comprises a result of whether the data passes the auditing or not. According to the method, data quality auditing and data compliance auditing functions can be automatically realized, and the efficiency, accuracy and reliability of data registration auditing are improved.

Description

Technical Field

[0001] The present application relates to the technical field of intelligent auditing of data registration platforms, and in particular to a data auditing method and device based on a data registration platform. Background Art

[0002] In the field of data circulation and transaction, data registration and audit are of vital importance. The most important thing about data registration and audit is the quality audit and compliance audit of data. However, there are significant defects in the data registration and audit in the existing technology, including: the existing data quality audit mainly relies on manual work, which is inefficient in the face of the growing amount of data. It is difficult for manual work to comprehensively and accurately check the integrity, accuracy and consistency of data, and it is easy to ignore the complex logical association errors between data, resulting in data with quality problems entering the circulation link, reducing the value of data use and affecting the reliability of decision-making. Data compliance audit faces huge challenges. The regulations and policies of different countries, regions and industries are significantly different and continuously updated. It is difficult for manual audits to grasp these changes in real time and accurately, and compliance loopholes are prone to occur, so that non-compliant data is mixed into the transaction process, bringing serious legal risks and reputation losses to related companies and institutions. The existing data audit auxiliary tools or system functions are limited, either focusing on a single type of data error screening, or only targeting the compliance requirements of specific industries, lacking comprehensive and intelligent audit capabilities, and unable to meet the needs of data circulation transactions for audit efficiency, comprehensiveness and accuracy, restricting the healthy development of the data circulation and transaction market. Summary of the invention

[0003] In response to the above problems, this application provides a data review method based on a data registration platform, including the following contents:

[0004] In a first aspect, the present application provides a data review method based on a data registration platform, the method comprising:

[0005] Obtain the data filled in by the user based on the data registration platform;

[0006] Preprocessing the data to obtain preprocessed data;

[0007] The preprocessed data is subjected to compliance testing and data quality testing respectively; when the compliance testing is performed, the preprocessed data is tested in combination with a preset database, and when the data quality testing is performed, the preprocessed data is tested in combination with preset rules;

[0008] Integrate and analyze the compliance test results and data quality test results to obtain data analysis results;

[0009] A data audit report is obtained based on the data analysis result, and the data audit report includes a result of whether the data has passed the audit.

[0010] Optionally, the obtaining of data filled in by the user based on the data registration platform includes:

[0011] Obtain the basic data information, basic rights information, certification materials, sample data and data registration commitment letter filled in by the user on the data registration platform.

[0012] Optionally, performing compliance processing on the preprocessed data includes:

[0013] Automatically compare the data filled in by the user based on the data registration platform with a preset data compliance knowledge base and a preset registration data knowledge base to identify compliance issues;

[0014] Based on the comparison result with the preset registration data knowledge base, the data with a repetition rate greater than the preset repetition rate threshold are listed.

[0015] Optionally, the process of performing data quality detection on the preprocessed data includes:

[0016] Comparing the sample data in the preprocessed data with the rules in the preset standard rule base and the preset industry knowledge base to obtain a comparison result, wherein the comparison result at least includes the quantitative results of the data integrity, accuracy, consistency and timeliness indicators;

[0017] The comparing of the sample data in the preprocessed data with the rules in the preset standard rule base and the preset industry knowledge base includes checking whether the data format and type are correct, and whether the data is within a preset range.

[0018] Optionally, the compliance test results and the data quality test results are integrated and analyzed to obtain data analysis results including:

[0019] Analyze the compliance test results and the data quality test results through a preset algorithm, quantitatively evaluate the compliance risk and data quality risk, and obtain the risk probability;

[0020] Based on the risk probability, risk impact, business needs and cost-benefit analysis, the risk priority is determined and intelligent audit opinions are generated.

[0021] Optionally, the method further includes:

[0022] For the quantifiable data included in the report, visual means are used to demonstrate the quality and compliance status of the data.

[0023] In a second aspect, the present application provides a data review device based on a data registration platform, the device comprising:

[0024] A data acquisition unit, used to acquire data filled in by the user based on the data registration platform;

[0025] A data preprocessing unit, used for preprocessing the data to obtain preprocessed data;

[0026] A data processing unit, used to perform compliance detection and data quality detection on the preprocessed data respectively; when performing compliance detection, the preprocessed data is detected in combination with a preset database, and when performing data quality detection, the preprocessed data is detected in combination with preset rules;

[0027] A data analysis unit, used to integrate and analyze compliance test results and data quality test results to obtain data analysis results;

[0028] A report generating unit is used to obtain a data audit report based on the data analysis result, wherein the data audit report includes a result of whether the data has passed the audit.

[0029] Optionally, the data acquisition unit acquires data filled in by the user based on the data registration platform, including:

[0030] Obtain the basic data information, basic rights information, certification materials, sample data and data registration commitment letter filled in by the user on the data registration platform.

[0031] Optionally, the data preprocessing unit performs compliance processing on the preprocessed data, including:

[0032] Automatically compare the data filled in by the user based on the data registration platform with a preset data compliance knowledge base and a preset registration data knowledge base to identify compliance issues;

[0033] Based on the comparison result with the preset registration data knowledge base, the data with a repetition rate greater than the preset repetition rate threshold are listed.

[0034] Optionally, the process of the data processing unit performing data quality detection on the preprocessed data includes:

[0035] Comparing the sample data in the preprocessed data with the rules in the preset standard rule base and the preset industry knowledge base to obtain a comparison result, wherein the comparison result at least includes the quantitative results of the data integrity, accuracy, consistency and timeliness indicators;

[0036] The comparing of the sample data in the preprocessed data with the rules in the preset standard rule base and the preset industry knowledge base includes checking whether the data format and type are correct, and whether the data is within a preset range.

[0037] Optionally, the data analysis unit integrates and analyzes the compliance test results and the data quality test results to obtain the data analysis results including:

[0038] Analyze the compliance test results and the data quality test results through a preset algorithm, quantitatively evaluate the compliance risk and data quality risk, and obtain the risk probability;

[0039] Based on the risk probability, risk impact, business needs and cost-benefit analysis, the risk priority is determined and intelligent audit opinions are generated.

[0040] Optionally, the device further comprises:

[0041] The visualization processing unit is used to display the quality and compliance status of the quantifiable data included in the report by using visualization means.

[0042] In a third aspect, the present application provides a device comprising a memory and a processor, wherein the memory is used to store instructions or codes, and the processor is used to execute the instructions or codes so that the device executes the data review method based on the data registration platform introduced in any implementation method of the first aspect.

[0043] In a fourth aspect, the present application provides a computer-readable storage medium storing a code. When the code is executed, the device executing the code implements the data review method based on the data registration platform introduced in any implementation method of the first aspect.

[0044] The present application provides a data audit method based on a data registration platform. When executing the method, first obtain the data filled in by the user based on the data registration platform, then pre-process the data to obtain the pre-processed data, perform compliance detection and data quality detection on the pre-processed data respectively, perform compliance detection on the pre-processed data in combination with a preset database, perform data quality detection on the pre-processed data in combination with preset rules, integrate and analyze the compliance detection results and data quality detection results, obtain data analysis results, and obtain a data audit report based on the data analysis results, and the data audit report includes the result of whether the data has passed the audit. Through this comprehensive data pre-processing and audit process, the efficiency and accuracy of the entire data processing system can be significantly improved. This method ensures that the data has been thoroughly cleaned and verified before entering the analysis stage, thereby reducing the possibility of errors and deviations. The combined use of compliance detection and data quality detection not only improves the legitimacy and accuracy of the data, but also enhances the availability and trust of the data. Ultimately, the results of the integrated analysis provide decision makers with a clear and accurate data view, making data-based decisions more reliable and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in this embodiment or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 A flowchart of a data review method based on a data registration platform provided in an embodiment of the present application;

[0047] Figure 2 A flowchart of another data review method based on a data registration platform provided in an embodiment of the present application;

[0048] Figure 3 A structural schematic diagram of a data review device based on a data registration platform provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0050] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0051] Figure 1 A flowchart of a data audit method based on a data registration platform provided in an embodiment of the present application. Figure 1 As shown, the data review method based on the data registration platform provided in the embodiment of the present application may include:

[0052] S101. Obtain data filled in by the user based on the data registration platform.

[0053] The registrant shall supplement the application information in accordance with the registration application form provided by the platform, including basic data information (data name, application scenario, industry, region, data structure, data acquisition method, update frequency, etc.), basic rights information (data ownership type, ownership period, ownership restrictions, ownership pledge status), upload ownership certification materials (the materials need to describe in detail the data acquisition method, proof of source, etc.), upload sample data, upload data registration commitment letter and other materials, and submit them to the platform after completion.

[0054] S102: Preprocess the data to obtain preprocessed data.

[0055] Clean, format, and validate the collected data. Data cleaning includes identifying and removing duplicate data, correcting obvious errors such as format errors or logical errors, and handling missing values ​​by filling or deleting them. Data formatting includes unifying the format of dates, times, etc., converting data types, ensuring consistency, and encoding categorical data. Data validation includes ensuring that the data is logically consistent, such as checking whether the dependencies between data are reasonable.

[0056] S103: Perform compliance detection and data quality detection on the preprocessed data.

[0057] When conducting compliance testing, the data filled in by the user based on the data registration platform is automatically compared with the preset data compliance knowledge base and the preset registration data knowledge base. Specifically, advanced algorithms and automation tools, such as artificial intelligence (AI) or big data analysis, are used to pre-process the data based on the content of the application form submitted by the registrant and automatically compare them with the preset data compliance knowledge base and the preset registration data knowledge base to quickly identify potential compliance issues, ensure that the data complies with relevant laws, regulations and industry standards, and generate corresponding risk values ​​based on whether the data violates laws and regulations. The risk value reflects the probability of the risk of personal privacy involving the data and the risk of confidentiality involving the data.

[0058] AI technology can be used to automatically review compliance reports, identify compliance risks, and other tasks. Through machine learning algorithms, the system can learn and identify compliance risk patterns, thereby improving the accuracy and efficiency of compliance management; big data analysis technology can process large amounts of data and mine valuable information hidden in the data. In compliance automation, big data analysis can be used to discover early warning signals of compliance risks and take measures in advance. Based on the comparison results with the preset registration data knowledge base, data with a repetition rate greater than the preset repetition rate threshold is listed to avoid duplicate registration of data. By listing data with a repetition rate greater than the preset repetition rate threshold for auditors to refer to, efficient and accurate compliance assurance is provided for the data registration platform.

[0059] When performing data quality detection, the sample data in the preprocessed data is compared with the rules in the preset standard rule base and the preset industry knowledge base to obtain a comparison result. The comparison result includes at least the quantitative results of the data integrity, accuracy, consistency and timeliness indicators. In addition, the indicators also include the standardization and accessibility of the data. The comparison of the sample data in the preprocessed data with the rules in the preset standard rule base and the preset industry knowledge base includes checking whether the data format and type are correct, and whether the data is within the preset range. Specifically, after data preprocessing, the preprocessed data is deeply analyzed to check whether the data format and type are correct, and whether the data is within a reasonable range. The quality of the data is judged by the quality score. For example, the full score is 100, and one of the data scores 45 points, indicating that the quality of this data is not high. If the score is 90 points, it means that the quality is relatively excellent. Generally, 85-90 points are set as a relatively excellent quality score. Finally, the analysis results are given, which directly reflect the scores corresponding to the key indicators of data quality, ensuring that the data set meets the predetermined quality standards. The analysis results clearly point out the advantages of the data and areas that need improvement, ensuring that the data meets business needs and compliance requirements. In this way, by comparing and analyzing the sample data with the relevant rules in the standard rule base and industry knowledge base, the system can automatically evaluate the quantitative results of key quality indicators such as data integrity, accuracy, consistency, and timeliness.

[0060] S104. Integrate and analyze the compliance test results and the data quality test results to obtain data analysis results.

[0061] The compliance test results and the data quality test results are analyzed by a preset algorithm, and the compliance risks and data quality risks are quantitatively assessed to obtain the risk probability; based on the risk probability, the degree of risk impact, business needs and cost-benefit analysis, the risk priority is determined and an intelligent audit opinion is generated. Specifically, the algorithm is used to deeply analyze and quantitatively assess compliance risks and data quality risks, such as non-compliance with regulations, cross-border transmission, unclear authorization, and data accuracy, completeness and consistency issues, taking into account the probability of risk occurrence and the degree of impact, combining business needs and cost-effectiveness to determine priorities, predict potential risk trends, and form intelligent audit opinions to provide auditors with comprehensive risk management and decision-making support. The above-mentioned algorithms, such as machine learning algorithms, natural language processing (NLP) technology, and other algorithms that can achieve the above functions are all applicable to this application, and the specific types of algorithms are not limited here.

[0062] S105. Obtain a data audit report based on the data analysis result, wherein the data audit report includes a result of whether the data has passed the audit.

[0063] On the basis of intelligent comprehensive analysis, the analysis results are further integrated to form the final intelligent audit report. Then, based on the compliance and quality test results of the data and in accordance with the established audit rules, clear audit suggestions for data registration are given, including pass or fail decisions. The report will also cover the assessment of data result priorities and the quantitative analysis of key data risks, so as to ensure that auditors can quickly grasp the core points of data audit.

[0064] In addition, for quantifiable data, the report will use visual means such as charts to intuitively display the quality and compliance status of the data, thereby providing clear audit recommendations and decision-making basis for data registration.

[0065] The above embodiment introduces the data audit method based on the data registration platform in this application. Figure 2 , a specific application scenario is used to further introduce the data review method based on the data registration platform in this application. Figure 2 Another data review method based on a data registration platform is provided in the embodiment of the present application. In this embodiment, a data named "mechanical equipment fault monitoring data" is registered on the registration platform as an example. The specific implementation process is as follows:

[0066] S201: Data acquisition.

[0067] The registrant fills out a registration application form for mechanical equipment fault monitoring data on the platform. The data in the application form includes basic data information, basic rights information and supporting materials. The basic data information includes data name, application scenario, data acquisition method, industry, region, data structure and update frequency; the basic rights information includes property type, property term, property restrictions, property pledge status and other information; the supporting materials include property certification materials, sample data and data registration commitment letter.

[0068] S202: Data preprocessing.

[0069] Clean the data submitted by the registrant, remove invalid or erroneous data entries, correct format errors, and handle missing values, such as filling or deleting missing monitoring data. Format the data to ensure that all date and time data formats are consistent, the numerical data type is correct, and encode the categorical data.

[0070] S203. Data compliance testing.

[0071] The processed data is compared with the data in the preset data compliance detection library, which includes a data compliance knowledge base and a registration data knowledge base. By automatically comparing the application form content with the built-in data compliance knowledge base, it is checked whether the data complies with the laws, regulations and industry standards related to mechanical equipment fault monitoring. By comparing with the registration data knowledge base, it is detected whether there is duplicate registered fault monitoring data to avoid data duplication.

[0072] S204: Data quality detection.

[0073] Compare and analyze the sample data with the relevant rules in the standard rule base and industry knowledge base to evaluate the quantitative results of key quality indicators such as data completeness, accuracy, consistency, timeliness, etc. Check whether the data format and type are correct, and whether the data is within a reasonable range, such as whether the value of the monitoring data is within the normal operating parameters.

[0074] S205. Intelligent comprehensive analysis.

[0075] Integrate the results of compliance testing and quality testing, use algorithms to deeply analyze and quantitatively evaluate compliance risks and data quality risks, and analyze possible consequences, including misleading business decisions, causing potential economic losses, triggering legal disputes, and damaging the reputation of the registration platform.

[0076] S206: Generate report.

[0077] Based on the results of intelligent comprehensive analysis, the system automatically generates an intelligent audit report, which includes audit recommendations, data result priorities, and quantitative analysis of key data risks. The report may include visual charts to intuitively display the quality and compliance status of the data.

[0078] The method in the above-mentioned embodiment of the present application can quickly identify potential compliance issues by utilizing advanced algorithms and automation tools, ensure that the data complies with relevant laws, regulations and industry standards, and effectively reduce the risks of the registration platform itself; by comparing and analyzing the submitted data with the registration data knowledge base through intelligent algorithms, it can effectively identify and reduce duplicate data registrations, optimize the efficiency of data management, and accurately screen out duplicate data by comparing with the registration data knowledge base; through the automated review process, the user waiting time is significantly shortened, the user experience is improved, and users can obtain review results faster; through comparison and analysis with the standard rule base and industry knowledge base, the system can automatically evaluate the integrity, accuracy and consistency of the data to ensure that the data quality meets business needs; the intelligent audit report provided not only includes audit recommendations, but also covers the quantitative analysis of data result priorities and key data risks, providing decision makers with comprehensive and in-depth decision support.

[0079] The above are some specific implementations of a data audit method based on a data registration platform provided in the embodiment of the present application. Based on this, the present application also provides a corresponding device. The device provided in the embodiment of the present application will be introduced from the perspective of functional modularization.

[0080] Figure 3 A schematic diagram of the structure of a data audit device based on a data registration platform provided in an embodiment of the present application. Figure 3 As shown, the data audit device 300 based on the data registration platform provided in the embodiment of the present application includes:

[0081] The data acquisition unit 310 is used to acquire the data filled in by the user based on the data registration platform;

[0082] A data preprocessing unit 320, configured to preprocess the data to obtain preprocessed data;

[0083] The data processing unit 330 is used to perform compliance detection and data quality detection on the preprocessed data respectively; when performing the compliance detection, the preprocessed data is detected in combination with a preset database, and when performing the data quality detection, the preprocessed data is detected in combination with preset rules;

[0084] The data analysis unit 340 is used to integrate and analyze the compliance test results and the data quality test results to obtain data analysis results;

[0085] The report generating unit 350 is used to obtain a data audit report based on the data analysis result, wherein the data audit report includes a result of whether the data has passed the audit.

[0086] In one implementation of the embodiment of the present application, the data acquisition unit acquires the data filled in by the user based on the data registration platform, including:

[0087] Obtain the basic data information, basic rights information, certification materials, sample data and data registration commitment letter filled in by the user on the data registration platform.

[0088] In an implementation of the embodiment of the present application, the data preprocessing unit performs compliance processing on the preprocessed data, including:

[0089] Automatically compare the data filled in by the user based on the data registration platform with a preset data compliance knowledge base and a preset registration data knowledge base to identify compliance issues;

[0090] Based on the comparison result with the preset registration data knowledge base, the data with a repetition rate greater than the preset repetition rate threshold are listed.

[0091] In one implementation of the embodiment of the present application, the process of the data processing unit performing data quality detection on the pre-processed data includes:

[0092] Comparing the sample data in the preprocessed data with the rules in the preset standard rule base and the preset industry knowledge base to obtain a comparison result, wherein the comparison result at least includes the quantitative results of the data integrity, accuracy, consistency and timeliness indicators;

[0093] The comparing of the sample data in the preprocessed data with the rules in the preset standard rule base and the preset industry knowledge base includes checking whether the data format and type are correct, and whether the data is within a preset range.

[0094] In one implementation of the embodiment of the present application, the data analysis unit integrates and analyzes the compliance test results and the data quality test results to obtain the data analysis results, including:

[0095] Analyze the compliance test results and the data quality test results through a preset algorithm, quantitatively evaluate the compliance risk and data quality risk, and obtain the risk probability;

[0096] Based on the risk probability, risk impact, business needs and cost-benefit analysis, the risk priority is determined and intelligent audit opinions are generated.

[0097] In one implementation of the embodiment of the present application, the device further includes:

[0098] The visualization processing unit is used to display the quality and compliance status of the quantifiable data included in the report by using visualization means.

[0099] The embodiments of the present application also provide corresponding devices and computer storage media for implementing the solutions provided by the embodiments of the present application.

[0100] The device includes a memory and a processor, the memory is used to store instructions or codes, and the processor is used to execute the instructions or codes so that the device executes the method described in any embodiment of the present application.

[0101] The computer storage medium stores codes, and when the codes are executed, a device executing the codes implements the method described in any embodiment of the present application.

[0102] Through the description of the above implementation methods, it can be known that those skilled in the art can clearly understand that all or part of the steps in the above-mentioned embodiment method can be implemented by means of software plus a general hardware platform. Based on such an understanding, the technical solution of the present application can be embodied in the form of a software product, which can be stored in a storage medium, such as a read-only memory (ROM) / RAM, a magnetic disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network communication device such as a router) to execute the methods described in each embodiment of the present application or some parts of the embodiments.

[0103] It is understandable that in the specific implementation of the present application, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved, when the above embodiments of the present application are applied to specific products or technologies, need to obtain user permission or consent, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0104] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device 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 device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0105] It should also be noted that the various embodiments in this specification are described in a progressive manner, and the same and similar parts between the various embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and apparatus embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments. The device and apparatus embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components indicated as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0106] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A data audit method based on a data registration platform, characterized in that: The method comprises: Obtain the data filled in by the user based on the data registration platform; Preprocessing the data to obtain preprocessed data; The preprocessed data is subjected to compliance testing and data quality testing respectively; when the compliance testing is performed, the preprocessed data is tested in combination with a preset database, and when the data quality testing is performed, the preprocessed data is tested in combination with preset rules; Integrate and analyze the compliance test results and data quality test results to obtain data analysis results; A data audit report is obtained based on the data analysis result, and the data audit report includes a result of whether the data has passed the audit.

2. The method according to claim 1, characterized in that The acquisition of data filled in by the user based on the data registration platform includes: Obtain the basic data information, basic rights information, certification materials, sample data and data registration commitment letter filled in by the user on the data registration platform.

3. The method according to claim 1, characterized in that: The compliance processing of the pre-processed data includes: Automatically compare the data filled in by the user based on the data registration platform with a preset data compliance knowledge base and a preset registration data knowledge base to identify compliance issues; Based on the comparison result with the preset registration data knowledge base, the data with a repetition rate greater than the preset repetition rate threshold are listed.

4. The method according to claim 1, characterized in that The process of performing data quality detection on the preprocessed data includes: Comparing the sample data in the preprocessed data with the rules in the preset standard rule base and the preset industry knowledge base to obtain a comparison result, wherein the comparison result at least includes the quantitative results of the data integrity, accuracy, consistency and timeliness indicators; The comparing of the sample data in the preprocessed data with the rules in the preset standard rule base and the preset industry knowledge base includes checking whether the data format and type are correct, and whether the data is within a preset range.

5. The method according to claim 1, characterized in that The compliance test results and data quality test results are integrated and analyzed to obtain data analysis results including: Analyze the compliance test results and the data quality test results through a preset algorithm, quantitatively evaluate the compliance risk and data quality risk, and obtain the risk probability; Based on the risk probability, risk impact, business needs and cost-benefit analysis, the risk priority is determined and intelligent audit opinions are generated.

6. The method according to claim 1, characterized in that The method further comprises: For the quantifiable data included in the report, visual means are used to demonstrate the quality and compliance status of the data.

7. A data audit device based on a data registration platform, characterized in that: The device comprises: A data acquisition unit, used to acquire data filled in by the user based on the data registration platform; A data preprocessing unit, used for preprocessing the data to obtain preprocessed data; A data processing unit, used to perform compliance detection and data quality detection on the preprocessed data respectively; when performing compliance detection, the preprocessed data is detected in combination with a preset database, and when performing data quality detection, the preprocessed data is detected in combination with preset rules; A data analysis unit, used to integrate and analyze compliance test results and data quality test results to obtain data analysis results; A report generating unit is used to obtain a data audit report based on the data analysis result, wherein the data audit report includes a result of whether the data has passed the audit.

8. The device according to claim 7, characterized in that The device also includes: The visualization processing unit is used to display the quality and compliance status of the quantifiable data included in the report by using visualization means.

9. A computing device, characterized in that The computing device includes: a memory and a processor; The memory is used to store computer programs; The processor is configured to implement the method according to any one of claims 1 to 6 when executing the computer program.

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

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