A data governance analysis method and system

Abstract

The application provides a data governance analysis method and system, and relates to the technical field of data analysis, and comprises the following steps: monitoring and processing and classifying various data generated in the business operation process in real time to obtain a first processed data set; acquiring the data type corresponding to each first processed data sub-set, screening the corresponding data quality evaluation standard from an evaluation database, constructing a comprehensive quality evaluation system, and thus performing data evaluation; determining the data quality problem of each first processed data based on the data evaluation result and performing inspection and tracking, so as to obtain the first analysis result of each first processed data; and comprehensively processing each first analysis result in the first processed data set, so as to perform corresponding data visualization on the data comprehensive result. Through the classified processing of the data of each data source, the classified analysis is performed, the personalized data visualization is realized, the analysis of the data is more accurate and in-depth, and thus the value judgment can be more effectively performed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data analysis, and particularly relates to a data governance analysis method and system. BACKGROUND

[0002] At present, with the rapid development of information technology, data has become an important asset of enterprises.

[0003] However, there are problems such as low data quality, poor data security, and insufficient data value mining in the data governance process. Traditional data governance methods often focus on data storage and management, and ignore in-depth analysis and value mining of data.

[0004] Therefore, the present application provides a data governance analysis method and system. SUMMARY

[0005] The present application provides a data governance analysis method and system to solve the problems of low data quality and inaccurate data value judgment in the prior art.

[0006] The present application provides a data governance analysis method, comprising:

[0007] Step 1: Real-time monitoring of various types of data generated in the business operation process, and processing and classifying the various types of data obtained by monitoring to obtain a first processing data set;

[0008] Step 2: Obtaining the data type corresponding to each first processing data sub-set in the first processing data set, thereby screening the corresponding data quality evaluation standard from the evaluation database, constructing a comprehensive quality evaluation system, and performing data evaluation on the first processing data in the first processing data set;

[0009] Step 3: Determining the data quality problem of each first processing data in the first processing data set based on the data evaluation result, and performing inspection and tracking, thereby obtaining a first analysis result of each first processing data;

[0010] Step 4: Integrating each first analysis result in the first processing data set, thereby performing corresponding data visualization on the data integration result

[0011] According to the present application, real-time monitoring of various types of data generated in the business operation process is performed, and the various types of data obtained by monitoring are processed and classified to obtain a first processing data set, comprising:

[0012] Step 11: Real-time monitoring of each data source involved in the business operation process, and performing real-time data collection to obtain initial collection data;

[0013] Step 12: data cleaning and data standardization processing are performed on the initial acquisition data to obtain initial processing data;

[0014] Step 13: data classification is performed on the initial processing data based on data properties and uses, and the classified data sub-sets are arranged to obtain a first processing data set.

[0015] According to the application, the data type corresponding to each first processing data sub-set in the first processing data set is obtained, so as to screen the corresponding data quality evaluation standard from the evaluation database, construct a comprehensive quality evaluation system, and evaluate the first processing data in the first processing data set, including:

[0016] Step 21: the classification type corresponding to each first processing data sub-set in the first processing data set and the data type of each first processing data in the current first processing data sub-set are obtained, so as to comprehensively determine the first data type of the first processing data;

[0017] Step 22: the first data type is used to screen the corresponding data quality evaluation standard from the evaluation database to obtain the first quality evaluation standard of the current first processing data;

[0018] Step 23: based on each first quality evaluation standard of the same first processing data sub-set, a first quality evaluation standard set is obtained;

[0019] Step 24: each first quality evaluation standard in the first quality evaluation standard set is classified according to the evaluation type to obtain a second quality evaluation standard set;

[0020] Step 25: it is judged whether each second quality evaluation standard in the second quality evaluation standard set conflicts;

[0021] If there is a second quality evaluation standard conflict, the current second quality evaluation standard set is divided into two evaluation standard sub-sets, so as to respectively perform quality evaluation standard judgment;

[0022] If there is no second quality evaluation standard conflict, the second quality evaluation standard with the highest evaluation standard in each second quality evaluation standard sub-set in the second quality evaluation standard set is extracted as a first reference quality evaluation standard;

[0023] Step 26: each first reference quality evaluation standard in the second quality evaluation standard set is integrated to obtain a first quality evaluation system of the current second quality evaluation standard set, so as to obtain an initial comprehensive quality evaluation system of the current first processing data set;

[0024] Step 27: based on the comprehensive quality evaluation system, each first processing data in the first processing data set is evaluated to obtain a data evaluation result.

[0025] The second quality evaluation standard set is divided into two evaluation standard subsets, and quality evaluation standard judgment is performed respectively, comprising:

[0026] Step 251: obtaining two second quality evaluation standards in which there is a conflict between second quality evaluation standards in the second quality evaluation standard set, to obtain a third quality evaluation standard and a fourth quality evaluation standard;

[0027] Step 252: judging whether the remaining second quality evaluation standards in the second quality evaluation standard set conflict with the third quality evaluation standard;

[0028] If not, the remaining second quality evaluation standards in the second quality evaluation standard set are combined with the third quality evaluation standard to obtain a third quality evaluation standard set;

[0029] Extracting the third quality evaluation standard with the highest evaluation standard in each third quality evaluation standard subset in the third quality evaluation standard set as a first reference quality evaluation standard;

[0030] At the same time, the fourth quality evaluation standard is taken as a first reference instruction evaluation standard.

[0031] According to the application, each first processing data in the first processing data set is evaluated based on the comprehensive quality evaluation system to obtain a data evaluation result, comprising:

[0032] The current first processing data is evaluated to obtain a first data evaluation result S of the current first processing data;

[0033] ; wherein S is the first data evaluation result of the current first processing data, is a historical data evaluation result of the i th historical processing data of the same data type as the current first processing data of the intelligent terminal, is an influence factor of the historical data evaluation result of the i th historical processing data of the same data type as the current first processing data of the intelligent terminal on the current first data evaluation result, is an influence weight of the historical data evaluation result on the first data evaluation result, is the key degree of the corresponding data type of the current first processing data, is a data integrity index of the current first processing data, is an influence weight of the key degree of the data type on the first data evaluation result, is an influence weight of the data integrity index on the first data evaluation result, wherein n is the number of historical processing data of the intelligent terminal, is a natural logarithm, .

[0034] According to the data evaluation result, the data quality problem of each first processing data in the first processing data set is determined, and inspection tracking is performed, so as to obtain the first analysis result of each first processing data, comprising:

[0035] Step 31: Based on the data evaluation result, the data quality problem of each first processing data in the first processing data set is determined, and the first data quality set is obtained;

[0036] Step 32: Each data quality problem in the first data quality set is classified according to different quality problem types, so as to obtain the first classification quality set;

[0037] Step 33: The quality problem type of each first classification quality sub-set in the first classification quality set is obtained, and the corresponding initial quality solution is screened from the quality-solution database;

[0038] Step 34: Based on the data value of the first processing data in each classification quality sub-set, the corresponding initial quality solution is optimized, and the first quality solution of each first processing data is obtained;

[0039] Step 35: Based on the first quality solution, the corresponding first processing data is processed, so as to obtain the second processing data;

[0040] Step 36: Based on the comprehensive quality evaluation system, the second processing data is evaluated, so as to obtain the second evaluation data, and the first analysis result of the first processing data is obtained based on the data processing evaluation process from the first processing data to the second evaluation data.

[0041] According to the data evaluation result, the data evaluation result is obtained by integrating each first analysis result in the first processing data set, and the corresponding data visualization of the data integration result is performed, comprising:

[0042] Step 41: Each first analysis result in the first processing data set is integrated to obtain a comprehensive data quality report;

[0043] Step 42: The data characteristics of the first processing data corresponding to the first analysis result and the visualization demand of the intelligent terminal are obtained to determine the visualization tool for data visualization of the first processing data;

[0044] Step 43: Based on the visualization tool, the content of the comprehensive data quality report is subjected to corresponding data visualization, so as to obtain the first visualization result, and the data visualization is realized.

[0045] The present application provides a data governance analysis system, comprising:

[0046] The data processing module is used for monitoring various data generated in the business operation process in real time, and processing and classifying various data obtained through monitoring to obtain a first processing data set;

[0047] The data evaluation module is used for obtaining a data type corresponding to each first processing data sub-set in the first processing data set, thereby screening a corresponding data quality evaluation standard from the evaluation database, constructing a comprehensive quality evaluation system, and performing data evaluation on the first processing data in the first processing data set.

[0048] The data analysis module is used for determining a data quality problem of each first processing data in the first processing data set based on the data evaluation result, and performing inspection and tracking, thereby obtaining a first analysis result of each first processing data.

[0049] The data visualization module is used for comprehensively processing each first analysis result in the first processing data set, thereby performing corresponding data visualization on the data comprehensive result.

[0050] Compared with the prior art, the data governance analysis method and system provided by the application can classify and process data of each data source, perform classification analysis, realize personalized data visualization, make the data analysis more accurate and in-depth, and thus can more effectively perform value judgment. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the application or prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of these drawings.

[0052] Figure 1 is a flow chart of a data governance analysis method provided by an embodiment of the application;

[0053] Figure 2 is a structural diagram of a data governance analysis system provided by an embodiment of the application. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical scheme and advantages of the application more clear, the technical scheme in the application will be clearly and completely described below in combination with the drawings in the application. Obviously, the described embodiments are some embodiments of the application, not all embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the application.

[0055] Embodiment 1:

[0056] The embodiment of the present application provides a data governance analysis method, as shown in the figure, comprising: Figure 1

[0057] Step 1: Real-time monitoring of various data generated in the business operation process, and processing and classifying the various data obtained by monitoring to obtain a first processing data set;

[0058] Step 2: Obtain the data type corresponding to each first processing data sub-set in the first processing data set, thereby filtering the corresponding data quality evaluation standard from the evaluation database, constructing a comprehensive quality evaluation system, and performing data evaluation on the first processing data in the first processing data set;

[0059] Step 3: Determine the data quality problem of each first processing data in the first processing data set based on the data evaluation result, and perform inspection and tracking, thereby obtaining a first analysis result of each first processing data;

[0060] Step 4: Integrate each first analysis result in the first processing data set, thereby performing corresponding data visualization on the data integration result.

[0061] In this embodiment, real-time monitoring refers to continuous and uninterrupted monitoring and recording of various data generated in the business operation process, which usually involves using specific software tools or systems to capture data for subsequent analysis and processing.

[0062] In this embodiment, the first processing data set refers to a data set that has been preliminarily processed (such as cleaning, sorting, etc.), which is extracted from the original data obtained from real-time monitoring and has been pre-processed in some form for subsequent analysis and evaluation.

[0063] In this embodiment, data type refers to the nature and classification of data, such as numbers, text, dates, etc.

[0064] In this embodiment, the evaluation database is a database that stores various data quality evaluation standards. These standards are used to measure data accuracy, completeness, consistency, and other quality indicators.

[0065] In this embodiment, the comprehensive quality evaluation system is a system constructed based on the data quality evaluation standards in the evaluation database, used to comprehensively and integratively evaluate the data in the first processing data set.

[0066] In this embodiment, data evaluation refers to the evaluation process of the data in the first processing data set according to the comprehensive quality evaluation system.

[0067] ​In this embodiment, the data quality problem refers to the data quality problem found in the data evaluation process, such as data error, missing, inconsistency, etc.

[0068] In this embodiment, the inspection tracking refers to further checking and analyzing the data quality problem to determine the cause of the problem and possible solutions.

[0069] In this embodiment, the first analysis result refers to the analysis result obtained after data quality evaluation, determination of data quality problems and inspection tracking for each first processed data.

[0070] In this embodiment, data visualization refers to the process of displaying data in the form of graphics, images, animations, etc.

[0071] In this embodiment, for example, in a certain retail enterprise, the data governance analysis method proposed by the present application is applied to collect and analyze customer purchase records, preferences, behaviors and other data. Through data analysis, it is found that the sales volume of a certain type of product shows a significant growth trend in a certain season. Based on this discovery, the enterprise adjusts the marketing strategy, increases the promotion of this type of product, and stocks up in advance before the season, ultimately achieving a substantial increase in sales.

[0072] The beneficial effects of the above technical solutions are: by classifying and processing the data of each data source, the classification analysis is carried out, the personalized data visualization is realized, the analysis of the data is more accurate and in-depth, and the value judgment can be more effectively carried out.

[0073] Embodiment 2:

[0074] Based on the basis of embodiment 1, real-time monitoring of various data generated in the business operation process is carried out, and the various data obtained by monitoring is processed and classified to obtain a first processed data set, including:

[0075] Step 11: Real-time monitoring of each data source involved in the business operation process is carried out, and real-time data collection is carried out to obtain initial collected data;

[0076] Step 12: Data cleaning and data standardization processing are carried out on the initial collected data to obtain initial processed data;

[0077] Step 13: Based on the data properties and uses, the initial processed data is classified, and the classified data sub-set is arranged to obtain the first processed data set.

[0078] In this embodiment, the data source includes a database, a log file, sensor data, etc.

[0079] In this embodiment, the initial collected data refers to the collected data obtained by real-time monitoring of each data source involved in the business operation process and performing data collection.

[0080] In this embodiment, data cleaning refers to a process of identifying and correcting (or deleting) errors, duplicates, incomplete or abnormal data in the data set.

[0081] In this embodiment, data standardization processing is a process of scaling data to fall into a small specific interval (usually 0 to 1 or -1 to 1). The purpose of standardization processing is to eliminate the influence of the dimension of different types of data (variables) and make them have the same scale, so as to facilitate comparison and weighting. For example, the method of data standardization processing is generally Min-Max standardization or Z-score standardization.

[0082] In this embodiment, data classification refers to classifying the initial processing data according to the nature, purpose and other factors of the data, such as classifying the initial processing data into user behavior data, transaction data, system log data, etc.

[0083] In this embodiment, the first processing data set refers to classifying the initial processing data according to the nature and purpose of the data, and arranging the classified data sub-set to obtain the processing data set.

[0084] The beneficial effects of the above technical solutions are: by performing data cleaning and data standardization processing on the data of each data source, and performing data classification on the processed data, the classification analysis can be more accurate, and the analysis of the data is more accurate and in-depth.

[0085] Embodiment 3:

[0086] Based on the basis of embodiment 2, the data type corresponding to each first processing data sub-set in the first processing data set is obtained, so as to filter the corresponding data quality evaluation standard from the evaluation database, construct a comprehensive quality evaluation system, and perform data evaluation on the first processing data in the first processing data set, including:

[0087] Step 21: obtaining the classification type corresponding to each first processing data sub-set in the first processing data set and the data type of each first processing data in the current first processing data sub-set, so as to comprehensively determine the first data type of the first processing data;

[0088] Step 22: filtering the corresponding data quality evaluation standard from the evaluation database based on the first data type, to obtain the first quality evaluation standard of the current first processing data;

[0089] Step 23: obtaining the first quality evaluation standard set based on each first quality evaluation standard of the same first processing data sub-set;

[0090] Step 24: classify each first quality evaluation criterion in the first quality evaluation criterion set according to the evaluation type to obtain a second quality evaluation criterion set;

[0091] Step 25: determine whether each second quality evaluation criterion in the second quality evaluation criterion set conflicts;

[0092] If there is a conflict between the second quality evaluation criteria, the current second quality evaluation criterion set is divided into two evaluation criterion subsets, and the quality evaluation criteria are determined respectively;

[0093] If there is no conflict between the second quality evaluation criteria, the second quality evaluation criterion with the highest evaluation criterion in each second quality evaluation criterion subset in the second quality evaluation criterion set is extracted as a first reference quality evaluation criterion;

[0094] Step 26: integrate each first reference quality evaluation criterion in the second quality evaluation criterion set to obtain a first quality evaluation system of the current second quality evaluation criterion set, thereby obtaining an initial comprehensive quality evaluation system of the current first processing data set;

[0095] Step 27: based on the comprehensive quality evaluation system, evaluate each first processing data in the first processing data set to obtain a data evaluation result.

[0096] In this embodiment, the data type refers to the nature and classification of the data, such as numbers, text, dates, etc.

[0097] In this embodiment, the evaluation database is a database that stores various data quality evaluation criteria. These criteria are used to measure the accuracy, completeness, consistency, and other quality indicators of the data.

[0098] In this embodiment, the first quality evaluation criterion is a quality evaluation criterion corresponding to the first data type selected from the evaluation database.

[0099] In this embodiment, the first quality evaluation criterion set refers to a set of multiple first quality evaluation criteria selected based on different aspects or dimensions for the same first processing data subset.

[0100] In this embodiment, the evaluation type refers to the classification method of the quality evaluation criteria, such as accuracy, completeness, consistency, etc.

[0101] In this embodiment, the second evaluation quality criterion set is obtained by classifying the criteria in the first quality evaluation criterion set according to the evaluation type.

[0102] In this embodiment, the evaluation criterion subset refers to two subsets obtained by dividing the current second quality evaluation criterion set to solve the conflict between the second quality evaluation criteria.

[0103] In this embodiment, the quality evaluation criterion judgment refers to evaluating and comparing the criteria in the evaluation criterion sub-set to determine which criterion is more appropriate or more accurate.

[0104] In this embodiment, the first reference quality evaluation criterion refers to the second quality evaluation criterion with the highest evaluation criterion under the same evaluation type.

[0105] In this embodiment, the first quality evaluation system refers to the evaluation system obtained by synthesizing the first reference quality evaluation criteria, which is used for overall quality evaluation of the first processed data set.

[0106] In this embodiment, the initial comprehensive quality evaluation system refers to the initial quality evaluation system obtained based on the first quality evaluation system for the current first processed data set.

[0107] In this embodiment, the comprehensive quality evaluation system is a system constructed based on the data quality evaluation criteria in the evaluation database, which is used for comprehensive evaluation of the data in the first processed data set.

[0108] In this embodiment, the data evaluation refers to the evaluation process of the data in the first processed data set according to the comprehensive quality evaluation system.

[0109] The beneficial effects of the above technical solutions are: different quality evaluation criteria are used to classify and evaluate different processed data, so as to more accurately judge the data quality problems of the first processed data, thereby realizing more accurate data analysis of the first processed data, which can make the data analysis more accurate and in-depth, thereby more effectively performing value judgment.

[0110] Embodiment 4:

[0111] Based on the basis of embodiment 3, the current second quality evaluation criterion set is divided into two evaluation criterion sub-sets, so as to respectively perform quality evaluation criterion judgment, including:

[0112] Step 251: obtaining two second quality evaluation criteria with second quality evaluation criterion conflict in the second quality evaluation criterion set, to obtain third quality evaluation criterion and fourth quality evaluation criterion;

[0113] Step 252: judging whether the remaining second quality evaluation criteria in the second quality evaluation criterion set conflict with the third quality evaluation criterion;

[0114] If not, the remaining second quality evaluation criteria in the second quality evaluation criterion set are synthesized with the third quality evaluation criterion to obtain a third quality evaluation criterion set;

[0115] extract the third quality evaluation standard with the highest evaluation standard in each third quality evaluation standard subset in the third quality evaluation standard set as the first benchmark quality evaluation standard;

[0116] Meanwhile, the fourth quality evaluation standard is taken as the first benchmark instruction evaluation standard.

[0117] In this embodiment, the third quality evaluation standard and the fourth quality evaluation standard refer to two second quality evaluation standards with second quality evaluation standard conflicts in the second quality evaluation standard set.

[0118] The beneficial effects of the above technical solutions are: different quality evaluation standards are used to classify and evaluate different processing data, so as to more accurately judge the data quality problems of the first processing data, thereby realizing more accurate data analysis of the first processing data.

[0119] Embodiment 5:

[0120] Based on the basis of embodiment 3, the first processing data set in the comprehensive quality evaluation system is evaluated to obtain a data evaluation result, including:

[0121] The current first processing data is evaluated to obtain the first data evaluation result S of the current first processing data;

[0122] ; wherein S is the first data evaluation result of the current first processing data, is the historical data evaluation result of the i-th historical processing data of the intelligent terminal and the current first processing data with the same data type, is the influence factor of the historical data evaluation result of the i-th historical processing data of the intelligent terminal and the current first processing data with the same data type on the current first data evaluation result, is the influence weight of the historical data evaluation result on the first data evaluation result, is the key degree of the corresponding data type of the current first processing data, is the data integrity index of the current first processing data, is the influence weight of the key degree of the data type on the first data evaluation result, is the influence weight of the data integrity index on the first data evaluation result, wherein n is the number of historical processing data of the intelligent terminal, is the natural logarithm, .

[0123] The beneficial effects of the above technical solutions are: by determining the data evaluation result of the first processed data, the data quality problem of the first processed data is more accurately judged, thereby realizing more accurate data analysis of the first processed data, and the analysis of the data is more accurate and in-depth.

[0124] Embodiment 6:

[0125] Based on the basis of Embodiment 3, the data quality problem of each first processed data in the first processed data set is determined based on the data evaluation result, and is tracked for verification, thereby obtaining the first analysis result of each first processed data, including:

[0126] Step 31: determining the data quality problem of each first processed data in the first processed data set based on the data evaluation result, and obtaining the first data quality set;

[0127] Step 32: classifying each data quality problem in the first data quality set according to different quality problem types, thereby obtaining the first classified quality set;

[0128] Step 33: obtaining the quality problem type of each first classified quality sub-set in the first classified quality set, and screening the corresponding initial quality solution from the quality-solution database;

[0129] Step 34: optimizing the corresponding initial quality solution based on the data value of the first processed data in each classified quality sub-set, thereby obtaining the first quality solution of each first processed data;

[0130] Step 35: performing data processing on the corresponding first processed data based on the first quality solution, thereby obtaining the second processed data;

[0131] Step 36: performing data evaluation on the second processed data based on the comprehensive quality evaluation system, thereby obtaining the second evaluation data, and obtaining the first analysis result of the first processed data based on the data processing evaluation process from the first processed data to the second evaluation data.

[0132] In this embodiment, the data quality problem refers to the data quality problem found in the data evaluation process, such as data error, missing, inconsistency, etc.

[0133] In this embodiment, the first data quality set refers to a set composed of the data quality problem of each first processed data determined according to the data evaluation result.

[0134] In this embodiment, the quality problem type includes: integrity problem, security problem, redundancy problem, accuracy problem, consistency problem, etc.

[0135] In this embodiment, the first classification quality set refers to classification of the first data quality set according to different quality problem types.

[0136] In this embodiment, the initial quality solution refers to screening of a quality solution corresponding to each sub-set in the first classification quality set from the quality-solution database.

[0137] In this embodiment, the first quality solution refers to a solution obtained by optimizing the initial quality solution based on the data value of each first processing data in the classification quality sub-set.

[0138] In this embodiment, the second processing data refers to processing data obtained by processing the first processing data according to the first quality solution.

[0139] In this embodiment, the second evaluation data refers to evaluation data obtained by evaluating the second processing data according to the comprehensive quality evaluation system.

[0140] In this embodiment, the first analysis result refers to an analysis result obtained by performing data quality evaluation, determining data quality problems, and performing inspection and tracking on each first processing data.

[0141] The beneficial effects of the above technical solutions are: by analyzing the data quality problems, the analysis result of each first processing data is obtained, the classification analysis is performed, the individualized data visualization is realized, the analysis of the data is more accurate and in-depth, and the value judgment can be more effectively performed.

[0142] Embodiment 7:

[0143] Based on the basis of embodiment 6, each first analysis result in the first processing data set is integrated, and the corresponding data visualization of the data integration result is performed, including:

[0144] Step 41: integrating each first analysis result in the first processing data set to obtain a comprehensive data quality report;

[0145] Step 42: obtaining the data characteristics of the first processing data corresponding to the first analysis result and the visualization demand of the intelligent terminal to determine the visualization tool for data visualization of the first processing data;

[0146] Step 43: performing corresponding data visualization on the content of the comprehensive data quality report based on the visualization tool to obtain a first visualization result, and realizing data visualization.

[0147] In this embodiment, the comprehensive data quality report refers to re-arranging and integrating each first analysis result corresponding to the first processing data set, thereby obtaining a comprehensive data quality judgment report of the data.

[0148] In this embodiment, the visualization tool includes Tableau, Power BI, etc.

[0149] In this embodiment, the corresponding visualization refers to visualizing the appropriate visualization chart designed based on the visualization tool on the comprehensive data quality report to intuitively display the data quality, wherein the visualization chart includes a column chart, a line chart, a pie chart, a scatter chart, etc., wherein different visualization charts focus on different visualization angles and visualization requirements.

[0150] The beneficial effects of the above technical solution are: by comprehensively analyzing the data characteristics of the first processed data and the visualization requirements of the intelligent terminal, the data visualization tool of each data is determined, the personalized data visualization is performed, the analysis of the data is more accurate and in-depth, and thus the value judgment can be more effectively performed.

[0151] Embodiment 8:

[0152] The embodiment of the application provides a data governance analysis system, as shown in Figure 2 , comprising:

[0153] The data processing module is used for monitoring various types of data generated in the business operation process in real time, and processing and classifying various types of data obtained through monitoring to obtain a first processed data set;

[0154] The data evaluation module is used for obtaining the data type corresponding to each first processed data sub-set in the first processed data set, thereby screening the corresponding data quality evaluation standard from the evaluation database, constructing a comprehensive quality evaluation system, and performing data evaluation on the first processed data in the first processed data set;

[0155] The data analysis module is used for determining the data quality problem of each first processed data in the first processed data set based on the data evaluation result, and performing inspection and tracking, thereby obtaining a first analysis result of each first processed data;

[0156] The data visualization module is used for comprehensively processing each first analysis result in the first processed data set, thereby performing corresponding data visualization on the data comprehensive result.

[0157] The beneficial effects of the above technical solution are: by classifying and processing the data of each data source, the classification analysis is performed, the personalized data visualization is realized, the analysis of the data is more accurate and in-depth, and thus the value judgment can be more effectively performed.

[0158] The above examples are only used to illustrate the technical solutions of the present application, and are not intended to limit the present application; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that the technical solutions recorded in the foregoing examples can be modified, or some technical features can be replaced by equivalent features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A data governance analytics method, characterized by, Comprising: Step 1: Real-time monitoring of various data generated in the process of business operation, and processing and classifying various data obtained by monitoring to obtain a first processed data set; Step 2: Obtain the data type corresponding to each first processed data sub-set in the first processed data set, thereby filtering the corresponding data quality evaluation standard from the evaluation database, constructing a comprehensive quality evaluation system, and evaluating the first processed data in the first processed data set; Comprising: Step 21: Obtain the classification type corresponding to each first processed data sub-set in the first processed data set and the data type of each first processed data in the current first processed data sub-set, thereby comprehensively determining the first data type of the first processed data; Step 22: Based on the first data type, filter the corresponding data quality evaluation standard from the evaluation database to obtain the first quality evaluation standard of the current first processed data; Step 23: Based on each first quality evaluation standard of the same first processed data sub-set, obtain a first quality evaluation standard set; Step 24: Classify each first quality evaluation standard in the first quality evaluation standard set according to the evaluation type to obtain a second quality evaluation standard set; Step 25: Determine whether each second quality evaluation standard in the second quality evaluation standard set conflicts; If there is a conflict between the second quality evaluation standards, the current second quality evaluation standard set is divided into two evaluation standard sub-sets, and the quality evaluation standards are judged respectively; If there is no conflict between the second quality evaluation standards, extract the second quality evaluation standard with the highest evaluation standard in each second quality evaluation standard sub-set in the second quality evaluation standard set as the first reference quality evaluation standard; Step 26: Integrate each first reference quality evaluation standard in the second quality evaluation standard set to obtain the first quality evaluation system of the current second quality evaluation standard set, thereby obtaining the initial comprehensive quality evaluation system of the current first processed data set; Step 27: Based on the comprehensive quality evaluation system, evaluate each first processed data in the first processed data set to obtain a data evaluation result; Step 3: Determine the data quality problem of each first processed data in the first processed data set based on the data evaluation result, and perform inspection and tracking to obtain a first analysis result of each first processed data; Step 4: Integrate each first analysis result in the first processed data set to perform corresponding data visualization on the data integration result.

2. The data governance analysis method of claim 1, wherein, Real-time monitoring of various data generated in the process of business operation, and processing and classifying various data obtained by monitoring to obtain a first processed data set, comprising: Step 11: Real-time monitoring of various data sources involved in the process of business operation, and real-time data collection to obtain initial collection data; Step 12: Data cleaning and data standardization processing of the initial collection data to obtain initial processed data; Step 13: Data classification of the initial processed data based on data properties and purposes, and arrangement of the classified data sub-set to obtain a first processed data set.

3. The data governance analysis method of claim 1, wherein, The current second quality evaluation standard set is divided into two evaluation standard subsets, so as to respectively perform quality evaluation standard judgment, including: Step 251: obtaining two second quality evaluation standards with second quality evaluation standard conflict in the second quality evaluation standard set, obtaining third quality evaluation standard and fourth quality evaluation standard; Step 252: judging whether the remaining second quality evaluation standards in the second quality evaluation standard set conflict with the third quality evaluation standard; If not, the remaining second quality evaluation standards in the second quality evaluation standard set are combined with the third quality evaluation standard to obtain a third quality evaluation standard set; Extract the third quality evaluation standard with the highest evaluation standard in each third quality evaluation standard subset in the third quality evaluation standard set as the first reference quality evaluation standard; At the same time, the fourth quality evaluation standard is taken as the first reference instruction evaluation standard.

4. The data governance analysis method of claim 1, wherein, Based on the data evaluation result, the data quality problem of each first processing data in the first processing data set is determined, and the test tracking is performed, so as to obtain the first analysis result of each first processing data, including: Step 31: based on the data evaluation result, the data quality problem of each first processing data in the first processing data set is determined, and the first data quality set is obtained; Step 32: each data quality problem in the first data quality set is classified according to different quality problem types, so as to obtain a first classification quality set; Step 33: obtaining the quality problem type of each first classification quality subset in the first classification quality set, and screening the corresponding initial quality solution from the quality-scheme database; Step 34: based on the data value of the first processing data in each classification quality subset, the scheme optimization is performed on the corresponding initial quality solution, and the first quality solution of each first processing data is obtained; Step 35: based on the first quality solution, the corresponding first processing data is processed, so as to obtain second processing data; Step 36: based on the comprehensive quality evaluation system, the second processing data is evaluated, so as to obtain second evaluation data, and the first analysis result of the first processing data is obtained based on the data processing evaluation process from the first processing data to the second evaluation data.

5. The data governance analysis method of claim 4, wherein, The first analysis result of each first processing data is integrated, so as to perform corresponding data visualization on the data synthesis result, including: Step 41: integrating each first analysis result in the first processing data set to obtain a comprehensive data quality report; Step 42: obtaining the data characteristics of the first processing data corresponding to the first analysis result and the visualization demand of the intelligent terminal to determine the visualization tool for data visualization of the first processing data; Step 43: based on the visualization tool, the content of the comprehensive data quality report is subjected to corresponding data visualization, so as to obtain a first visualization result, realizing data visualization.

6. A data governance analytics system, characterized by, Including: Data processing module: used for monitoring various data generated in the business operation process in real time, and processing and classifying various data obtained by monitoring to obtain a first processing data set; The data evaluation module is configured to obtain a data type corresponding to each first processing data sub-set in the first processing data set, filter a corresponding data quality evaluation standard from the evaluation database, construct a comprehensive quality evaluation system, and perform data evaluation on the first processing data in the first processing data set. The data evaluation module is configured to obtain a data type corresponding to each first processing data sub-set in the first processing data set, filter a corresponding data quality evaluation standard from the evaluation database, construct a comprehensive quality evaluation system, and perform data evaluation on the first processing data in the first processing data set. The data evaluation module is configured to obtain a data type corresponding to each first processing data sub-set in the first processing data set, filter a corresponding data quality evaluation standard from the evaluation database, construct a comprehensive quality evaluation system, and perform data evaluation on the first processing data in the first processing data set. The data evaluation module is configured to obtain a data type corresponding to each first processing data sub-set in the first processing data set, filter a corresponding data quality evaluation standard from the evaluation database, construct a comprehensive quality evaluation system, and perform data evaluation on the first processing data in the first processing data set. The data evaluation module is configured to obtain a data type corresponding to each first processing data sub-set in the first processing data set, filter a corresponding data quality evaluation standard from the evaluation database, construct a comprehensive quality evaluation system, and perform data evaluation on the first processing data in the first processing data set. The data evaluation module is configured to obtain a data type corresponding to each first processing data sub-set in the first processing data set, filter a corresponding data quality evaluation standard from the evaluation database, construct a comprehensive quality evaluation system, and perform data evaluation on the first processing data in the first processing data set. The data evaluation module is configured to obtain a data type corresponding to each first processing data sub-set in the first processing data set, filter a corresponding data quality evaluation standard from the evaluation database, construct a comprehensive quality evaluation system, and perform data evaluation on the first processing data in the first processing data set. The data evaluation module is configured to obtain a data type corresponding to each first processing data sub-set in the first processing data set, filter a corresponding data quality evaluation standard from the evaluation database, construct a comprehensive quality evaluation system, and perform data evaluation on the first processing data in the first processing data set. The data analysis module is configured to determine data quality problems of each first processing data in the first processing data set based on the data evaluation result, perform inspection and tracking, and obtain a first analysis result of each first processing data. The data visualization module is configured to comprehensively analyze each first analysis result in the first processing data set, and perform corresponding data visualization on the data comprehensive result. ​ ​ ​

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