Maturity evaluation method, device and system, computer equipment and storage medium

Abstract

The invention relates to a maturity evaluation method, device and system, computer equipment and a storage medium. The method comprises the steps of performing data governance processing on each piece of to-be-governed data according to at least one to-be-evaluated data governance strategy to obtain a plurality of pieces of first governed data; and according to a contrast data governance strategy corresponding to each to-be-evaluated data governance strategy, performing data governance processing on each to-be-governed data to obtain a plurality of second post-governance data, and according to each first post-governance data and each second post-governance data, performing maturity evaluation on each to-be-evaluated data governance strategy, and determining a maturity assessment result of each to-be-assessed data governance strategy. By adopting the method, the contrast data governance strategy corresponding to each to-be-assessed data governance strategy can be taken as the reference strategy to perform maturity assessment on each to-be-assessed data governance strategy, so that the accuracy of the finally obtained maturity assessment result of each to-be-assessed data governance strategy is higher.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a maturity assessment method, device, system, computer equipment and storage medium. Background Art

[0002] With the development of big data technology, more and more business data is generated in various fields. In the stages of data application and data management, business data often needs to be governed. Therefore, it is particularly important to evaluate the maturity of data governance strategies.

[0003] In the related art, a qualitative analysis is performed on the maturity of the data governance strategy to be evaluated to determine the maturity evaluation result of the data governance strategy.

[0004] However, in the process of maturity assessment of data governance strategies in related technologies, there is a problem of inaccurate assessment results. Summary of the invention

[0005] Based on this, it is necessary to provide a maturity assessment method, device, system, computer equipment and storage medium to address the above technical problems, which can improve the accuracy of assessment results in the process of maturity assessment of data governance strategies.

[0006] In a first aspect, an embodiment of the present application provides a maturity assessment method, the method comprising:

[0007] Performing data governance processing on each data to be governed according to at least one data governance strategy to be evaluated to obtain a plurality of first governed data; and performing data governance processing on each data to be governed according to a reference data governance strategy corresponding to each data governance strategy to be evaluated to obtain a plurality of second governed data; the reference data governance strategy is a pre-constructed data governance strategy that is similar or complementary to the corresponding data governance strategy to be evaluated;

[0008] Based on each first-governed data and each second-governed data, a maturity assessment is performed on each data governance strategy to be assessed, and a maturity assessment result of each data governance strategy to be assessed is determined.

[0009] In one embodiment, a maturity assessment is performed on each data governance strategy to be assessed based on each first governed data and each second governed data, and a maturity assessment result of each data governance strategy to be assessed is determined, including:

[0010] Determine, according to the actual data type of each to-be-governed data, a processing strategy corresponding to the error rate between each first-governed data and each second-governed data;

[0011] According to each processing strategy, determining the error rate between each first treated data and each second treated data;

[0012] According to the error rate between each first governed data and each second governed data, the maturity evaluation result of each data governance strategy to be evaluated is determined.

[0013] In one embodiment, determining the maturity evaluation result of each data governance strategy to be evaluated according to the error rate between each first governed data and each second governed data includes:

[0014] For any first governed data, if the error rate between the first governed data and the corresponding second governed data is greater than a preset threshold, it is determined that the maturity assessment result of the data governance policy to be assessed corresponding to the first governed data is unreliable;

[0015] If the error rate between the first governed data and the corresponding second governed data is less than or equal to a preset threshold, it is determined that the maturity assessment result of the data governance strategy to be assessed is reliable.

[0016] In one embodiment, the process of constructing each data governance policy to be evaluated includes:

[0017] Build mapping relationships based on governance requirement information, different data governance indicators, and different data governance goals corresponding to different standard data types;

[0018] According to the actual data types of the data to be managed, searching in the mapping relationship for data management targets corresponding to the standard data types that match the actual data types as the first data management targets;

[0019] Each data governance strategy to be evaluated is constructed according to at least one first data governance indicator and each first data governance goal corresponding to each actual data type.

[0020] In one embodiment, the process of constructing each control data governance policy includes:

[0021] Determine at least one second data governance indicator corresponding to each first data governance indicator according to a preset indicator set and mapping relationship;

[0022] Constructing respective comparative data governance strategies according to respective first data governance indicators, respective second data governance indicators and at least one second data governance goal.

[0023] In one embodiment, the second data governance indicator includes the first sub-indicator; and according to the preset indicator set and the mapping relationship, determining at least one second data governance indicator corresponding to each first data governance indicator includes:

[0024] Get multiple reference data governance objectives;

[0025] Searching for data governance indicators corresponding to data governance objectives that match each reference data governance objective in the mapping relationship as multiple candidate data governance indicators;

[0026] At least one candidate data governance indicator in the indicator set is selected from the candidate data governance indicators as each first sub-indicator.

[0027] In one embodiment, a plurality of reference data governance objectives are obtained, including:

[0028] Perform similarity processing on the multiple original data governance objectives and each first data governance objective to determine a similarity value between each original data governance objective and each first data governance objective;

[0029] A plurality of reference data governance objectives whose similarity values ​​are greater than a preset similarity threshold are selected from each original data governance objective.

[0030] In one embodiment, the second data governance indicator includes a second sub-indicator; and determining at least one second data governance indicator corresponding to each first data governance indicator according to a preset indicator set and a mapping relationship includes:

[0031] Acquire multiple third-party data governance objectives;

[0032] Searching for data governance indicators corresponding to data governance objectives that match each third data governance objective in the mapping relationship as multiple candidate data governance indicators;

[0033] At least one candidate data governance indicator in the indicator set is selected from the candidate data governance indicators as each second sub-indicator.

[0034] In one embodiment, obtaining a plurality of third data governance objectives includes:

[0035] Acquire multiple original data governance objectives; and divide the historical data governance issues into multiple problem sets; each original data governance objective covers at least one problem set;

[0036] For any original data governance goal, if there is no overlap between at least one problem set covered by the original data governance goal and at least one problem set covered by each first data governance goal, the original data governance goal is determined as the third data governance goal.

[0037] In a second aspect, an embodiment of the present application provides a maturity assessment device, the device comprising:

[0038] A processing module, configured to perform data governance processing on each data to be governed according to at least one data governance strategy to be evaluated, to obtain a plurality of first governed data; and to perform data governance processing on each data to be governed according to a reference data governance strategy corresponding to each data governance strategy to be evaluated, to obtain a plurality of second governed data; the reference data governance strategy is a pre-constructed data governance strategy that is similar to or complementary to the corresponding data governance strategy to be evaluated;

[0039] The maturity assessment module is used to perform maturity assessment on each data governance strategy to be assessed based on each first governed data and each second governed data, and determine the maturity assessment result of each data governance strategy to be assessed.

[0040] In a third aspect, an embodiment of the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method of any one of the embodiments of the first aspect when executing the computer program.

[0041] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method of any embodiment in the above-mentioned first aspect are implemented.

[0042] In a fifth aspect, an embodiment of the present application further provides a computer program product, the computer program product comprising a computer program, which, when executed by a processor, implements the steps of the method of any embodiment of the first aspect above.

[0043] The maturity assessment method, apparatus, system, computer equipment and storage medium provided in the embodiments of the present application include: performing data governance processing on each data to be governed according to at least one data governance strategy to be evaluated to obtain multiple first governed data; and performing data governance processing on each data to be governed according to a reference data governance strategy corresponding to each data governance strategy to be evaluated to obtain multiple second governed data, and performing maturity assessment on each data governance strategy to be evaluated based on each first governed data and each second governed data, and determining a maturity assessment result of each data governance strategy to be evaluated, wherein the reference data governance strategy is a pre-constructed data governance strategy that is similar or complementary to the corresponding data governance strategy to be evaluated. The above method does not require qualitative analysis of each data governance strategy to be evaluated. The control data governance strategy corresponding to each data governance strategy to be evaluated can be used as a reference strategy to conduct maturity assessment on each data governance strategy to be evaluated, so that the maturity assessment results of each data governance strategy to be evaluated obtained in the end are more accurate. On this basis, accurate reference information can be provided for the subsequent reliable use of the data governance strategy to be evaluated. At the same time, the above method does not require the participation of complex algorithms, thereby reducing the amount of data that needs to be processed in the data governance strategy maturity assessment process, thereby reducing the complexity of the maturity assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] FIG1 is an application environment diagram of a maturity assessment method in one embodiment;

[0045] FIG2 is a schematic diagram of a process flow of a maturity assessment method in one embodiment;

[0046] FIG3 is a schematic flow chart of a maturity assessment method in another embodiment;

[0047] FIG4 is a schematic flow chart of a maturity assessment method in another embodiment;

[0048] FIG5 is a schematic flow chart of a maturity assessment method in another embodiment;

[0049] FIG6 is a schematic flow chart of a maturity assessment method in another embodiment;

[0050] FIG7 is a schematic flow chart of a maturity assessment method in another embodiment;

[0051] FIG8 is a schematic flow chart of a maturity assessment method in another embodiment;

[0052] FIG9 is a schematic flow chart of a maturity assessment method in another embodiment;

[0053] FIG10 is a structural block diagram of a maturity assessment device in one embodiment;

[0054] FIG. 11 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0056] In the field of big data, data governance of business data is often required in the stages of data application and data management. Therefore, it is particularly important to conduct maturity assessment of data governance strategies. In the related art, a qualitative analysis is performed on the maturity of the data governance strategy to be assessed to determine the maturity assessment result of the data governance strategy. However, in the process of performing maturity assessment on the data governance strategy in the related art, there is a problem of inaccurate assessment results. Based on this, an embodiment of the present application provides a maturity assessment method, which can improve the accuracy of the assessment results in the process of performing maturity assessment on the data governance strategy.

[0057] The maturity assessment method provided in the embodiment of the present application can be applied to the maturity assessment system shown in Figure 1, which includes a computer device and a data management device within each enterprise. Optionally, the computer device can be an electronic device with data processing function such as a server, a personal computer, a laptop, a tablet computer, a smart phone, a smart bracelet, etc.; the data management device can be a device with data storage function such as a computer device, a server, a database system, etc.; wherein, this embodiment does not limit the specific form of the computer device and the data management device. In the embodiment of the present application, the data management device can manage the customer relationship, financial, market research, social and other types of data generated in the corresponding enterprise. Optionally, the computer device and the data management device can be connected by communication, and the communication method can be Wi-Fi, mobile network or Bluetooth connection, etc. Among them, Figure 1 takes the computer device as a personal computer, and the data management device is 1 and is a database system as an example to illustrate the maturity assessment system. The following embodiment uses the computer device as the execution subject of the maturity assessment method to introduce the specific process of the maturity assessment method.

[0058] As shown in FIG2 , it is a flow chart of the maturity assessment method provided in the embodiment of the present application, and the method can be implemented by the following steps:

[0059] S100, performing data governance processing on each data to be governed according to at least one data governance strategy to be evaluated, to obtain a plurality of first governed data; and performing data governance processing on each data to be governed according to a reference data governance strategy corresponding to each data governance strategy to be evaluated, to obtain a plurality of second governed data. The reference data governance strategy is a pre-constructed data governance strategy that is similar or complementary to the corresponding data governance strategy to be evaluated.

[0060] Specifically, the computer device can obtain at least one data governance strategy to be evaluated and the control data governance strategy corresponding to each data governance strategy to be evaluated, and call the data collection tool to collect each data to be governed from the data management device to improve the collection efficiency and accuracy of each data to be governed. Optionally, the above-mentioned data to be governed can be various types of data in any field, and the field can be the communication field, the Internet field, the medical field, the computer field, the artificial intelligence field, etc. Among them, the data management device can centrally manage different types of data to be evaluated to facilitate the subsequent centralized and comprehensive collection of data to be governed, and improve the collection efficiency of data to be governed.

[0061] Furthermore, for any data governance strategy to be evaluated, data governance processing can be performed on each data to be governed according to the data governance strategy to be evaluated, and for any comparison data governance strategy, data governance processing can be performed on each data to be governed according to the comparison data governance strategy.

[0062] Among them, each data governance policy to be evaluated may include at least one first data governance indicator, and correspondingly, the control data governance policy corresponding to the data governance policy to be evaluated may include each first data governance indicator in the data governance policy to be evaluated and at least one other data governance indicator. In an embodiment of the present application, each other data governance indicator is similar to each first data governance indicator, or complements each other to form a comprehensive data governance indicator set.

[0063] S200: Perform maturity assessment on each data governance strategy to be assessed based on each first-governed data and each second-governed data, and determine a maturity assessment result of each data governance strategy to be assessed.

[0064] One implementation method may be to pre-train an algorithm model, and then input each first-governed data and each second-governed data into the algorithm model. The algorithm model performs a maturity assessment on each data governance strategy to be assessed and then outputs a maturity assessment result of each data governance strategy to be assessed.

[0065] Another implementation method may be to perform comparison processing, analysis processing, matching processing and / or arithmetic processing on each first governance data and each second governance data to complete the maturity assessment of each data governance strategy to be assessed, and determine the maturity assessment result of each data governance strategy to be assessed according to the processing operation result. Optionally, the arithmetic operation processing may include at least one of addition operation, subtraction operation, multiplication operation, division operation, exponential operation, logarithmic operation, etc.

[0066] The technical solution in the embodiment of the present application performs data governance processing on each data to be governed according to at least one data governance strategy to be evaluated to obtain multiple first governed data; and performs data governance processing on each data to be governed according to the reference data governance strategy corresponding to each data governance strategy to be evaluated to obtain multiple second governed data, and performs maturity assessment on each data governance strategy to be evaluated according to each first governed data and each second governed data, and determines the maturity assessment result of each data governance strategy to be evaluated, wherein the reference data governance strategy is a pre-constructed data governance strategy that is similar to or complementary to the corresponding data governance strategy to be evaluated; the above method does not require qualitative analysis of each data governance strategy to be evaluated, and the reference data governance strategy corresponding to each data governance strategy to be evaluated can be used as a reference strategy to perform maturity assessment on each data governance strategy to be evaluated, so that the maturity assessment result of each data governance strategy to be evaluated finally obtained is more accurate, and on this basis, accurate reference information can be provided for the subsequent reliable use of the data governance strategy to be evaluated; at the same time, the above method does not require the participation of complex algorithms, thereby reducing the amount of data required to be processed in the data governance strategy maturity assessment process, thereby reducing the complexity of the maturity assessment.

[0067] The following is an explanation of the construction process of each data governance strategy to be evaluated. In one embodiment, before executing the steps in S100 above, as shown in FIG3 , the method may further include the following steps:

[0068] S300. Construct a mapping relationship based on the governance requirement information corresponding to different standard data types, different data governance indicators and different data governance goals.

[0069] Among them, different standard data types can be analyzed and matched to obtain governance demand information corresponding to different standard data types. Optionally, the above different standard data types may include structured data, semi-structured data, and unstructured data. Optionally, the above semi-structured data may be JSON, XML, YAML, and other data; the above unstructured data may be text, image, audio, video, and other data.

[0070] It should be noted here that the governance requirement information corresponding to structured data may include ideal values ​​corresponding to data consistency, data integrity and data accuracy; the governance requirement information corresponding to semi-structured data may include ideal values ​​corresponding to data flexibility, data applicability and data scalability; and the governance requirement information corresponding to unstructured data may include ideal values ​​corresponding to data validity and data availability.

[0071] In actual applications, different standard data types correspond to different governance requirement information. Specifically, the computer device can construct the corresponding relationship between governance requirement information corresponding to different standard data types, different data governance indicators and different data governance goals according to the preset mapping method, and generate the mapping relationship between governance requirement information, data governance indicators and data governance goals.

[0072] In addition, the computer device can also pre-train an algorithm model, and then input the governance requirement information corresponding to different standard data types, different data governance indicators and different data governance goals into the algorithm model. The algorithm model outputs the mapping relationship between the governance requirement information corresponding to different standard data types, different data governance indicators and different data governance goals.

[0073] Among them, the data governance goals correspond one-to-one to the corresponding data governance indicators, and the data governance goals can be understood as the target values ​​of the corresponding data governance indicators.

[0074] S400. According to the actual data types of each to-be-managed data, search in the mapping relationship for data governance targets corresponding to standard data types that match each actual data type as multiple first data governance targets.

[0075] Specifically, the computer device can search for data governance targets corresponding to standard data types that match each actual data type in the mapping relationship as multiple first data governance targets based on the actual data type of each to-be-governed data.

[0076] In the embodiment of the present application, the actual data type of the data to be managed can be structured data, semi-structured data or unstructured data. Among them, each data to be managed can be classified, and combined with industry standards and business needs analysis, the characteristics of each data to be managed can be analyzed to obtain the actual data type of each data to be managed.

[0077] S500. Construct each data governance strategy to be evaluated according to at least one first data governance indicator and each first data governance goal corresponding to each actual data type.

[0078] In practical applications, a computer device may pre-train a policy building model, and then input at least one first data governance indicator and each first data governance target corresponding to each actual data type into the policy building model, and the policy building model outputs each data governance policy to be evaluated. Optionally, the policy building model may be implemented by at least one of a convolutional neural network model, a fully connected neural network model, a recurrent neural network model, a long short-term memory neural network model, a residual neural network model, and the like.

[0079] At the same time, the computer device can also call a policy building tool or follow a preset policy building method to build each data governance policy to be evaluated according to at least one first data governance indicator and each first data governance goal corresponding to each actual data type.

[0080] It should be noted here that each of the above-mentioned first data governance indicators is a data governance indicator in a preset indicator set; wherein the above-mentioned indicator set includes multiple data governance indicators. In an embodiment of the present application, the correspondence between the actual data type and the first data governance indicator is described as follows: if the actual data type is structured data, the corresponding first data governance indicator may include data integrity, data consistency and data accuracy; if the actual data type is semi-structured data, the corresponding first data governance indicator may include data flexibility, data applicability and data scalability; if the actual data type is unstructured data, the corresponding first data governance indicator may include data validity and data availability.

[0081] For example, if the first data governance indicators are A, B, and C, respectively, A represents data integrity, B represents data consistency, and C represents data accuracy, then the computer device can arrange and combine A, B, and C to obtain multiple sets of data governance indicator sets, and then construct multiple data governance strategies to be evaluated based on each set of data governance indicator sets and each first data governance goal. Among them, each set of data governance indicator sets can be a combination of A, B, C, AB, AC, BC, or ABC.

[0082] It should be noted here that the first data governance goal corresponding to a single data governance indicator A can be to ensure that all data to be governed are not lost or damaged during the data governance process; the first data governance goal corresponding to a single data governance indicator B can be to ensure that all data to be governed are synchronized and coordinated between multiple systems during the data governance process; the first data governance goal corresponding to a single data governance indicator C can be to ensure that all data to be governed are error-free or anomaly-free during the data governance process; the first data governance goal corresponding to a single data governance indicator AB can be to ensure that all data to be governed are not lost during the data governance process while ensuring that all data to be governed are consistent between multiple systems; the first data governance goal corresponding to a single data governance indicator AC can be to ensure that all data to be governed are not lost during the data governance process and must maintain high accuracy, which is applicable to scenarios that require no data loss and must maintain high accuracy; the first data governance goal corresponding to a single data governance indicator BC can be to ensure that all data to be governed are synchronized and highly accurate between multiple systems during the data governance process, which is applicable to scenarios where data needs to be synchronized in multiple systems and requires high accuracy; the first data governance goal corresponding to a single data governance indicator ABC can be to ensure that all data to be governed are in the best state in all dimensions during the data governance process, which is applicable to business scenarios with extremely high data quality requirements.

[0083] The technical solution in the embodiments of the present application constructs a mapping relationship according to the governance requirement information corresponding to different standard data types, different data governance indicators and different data governance objectives, and according to the actual data type of each data to be governed, searches the mapping relationship for the data governance objectives corresponding to the standard data types that match each actual data type as multiple first data governance objectives, and constructs each data governance strategy to be evaluated according to at least one first data governance indicator and each first data governance objective corresponding to each actual data type; the above method can quickly determine the corresponding data governance objectives through the pre-constructed mapping relationship to construct the data governance strategy, thereby improving the construction speed and efficiency of the data governance strategy; at the same time, the above method can flexibly match multiple data governance features to construct the data governance strategy, thereby improving the flexibility of constructing the data governance strategy, and can construct a variety of different data governance strategies, so that the corresponding data can be efficiently and comprehensively governed based on these data governance strategies in subsequent applications.

[0084] The construction process of each control data governance strategy is described below. In one embodiment, before executing the step in S100 above, as shown in FIG4 , the method may further include the following steps:

[0085] S600. Determine at least one second data governance indicator corresponding to each first data governance indicator according to a preset indicator set and mapping relationship.

[0086] In actual applications, computer equipment can perform search processing, matching processing, screening processing and / or transformation processing according to a preset indicator set and mapping relationship, and determine at least one second data governance indicator corresponding to each first data governance indicator based on the processing operation results.

[0087] S700: Constructing respective comparison data governance strategies according to respective first data governance indicators, respective second data governance indicators and at least one second data governance goal.

[0088] Specifically, for any data governance policy to be evaluated, the computer device can construct a control data governance policy corresponding to the data governance policy to be evaluated based on each first data governance indicator, at least one second data governance indicator and the corresponding second data governance goal in the data governance policy to be evaluated.

[0089] The technical solution in the embodiments of the present application determines at least one second data governance indicator corresponding to each first data governance indicator based on a preset indicator set and a mapping relationship, and constructs each comparison data governance strategy based on each first data governance indicator, each second data governance indicator and at least one second data governance goal; the above method can construct a comparison data governance strategy corresponding to each data governance strategy to be evaluated, so as to serve as a reference strategy for the subsequent maturity evaluation of each data governance strategy to be evaluated, thereby facilitating the accurate evaluation of the maturity of each data governance strategy to be evaluated.

[0090] In one embodiment, the second data governance indicator includes a first sub-indicator; as shown in FIG. 5 , the step of determining at least one second data governance indicator corresponding to each first data governance indicator according to a preset indicator set and a mapping relationship in S600 may be implemented in the following manner:

[0091] S610. Obtain multiple reference data governance objectives.

[0092] Specifically, the computer device can arbitrarily obtain multiple data governance goals as multiple reference data governance goals.

[0093] In one embodiment, as shown in FIG6 , the step of acquiring multiple reference data governance targets in S610 may include:

[0094] S611. Perform similarity processing based on multiple original data governance objectives and each first data governance objective to determine the similarity value between each original data governance objective and each first data governance objective.

[0095] In practical applications, the computer device can calculate the feature vector of each original data governance target and the feature vector of each first data governance target, and use the similarity method to calculate the similarity between the feature vector of each original data governance target and the feature vector of each first data governance target to complete the similarity processing, and obtain the similarity value between each original data governance target and each first data governance target, so as to provide assistance for the subsequent accurate acquisition of multiple reference data governance targets closely related to each original data governance target. Optionally, the above similarity method can be the Euclidean distance method, the Manhattan distance method, etc., but in the embodiment of the present application, the above similarity method can be the cosine similarity method.

[0096] It should be noted here that the feature vector of data governance objectives may include multi-dimensional features related to data governance objectives, such as the nature of data governance objectives, applicable scenarios, and governance effects.

[0097] S612. Filter multiple reference data governance objectives whose similarity values ​​are greater than a preset similarity threshold from each original data governance objective.

[0098] Specifically, the computer device can compare and process the similarity values ​​and similarity thresholds between each original data governance target and each first data governance target, and select multiple reference data governance targets whose similarity values ​​are greater than a preset similarity threshold from each original data governance target based on the comparison processing result, that is, select multiple reference data governance targets with high similarity to each original data governance target. Optionally, the above-mentioned similarity threshold can be determined by the user or based on historical experience, which is not limited in the embodiment of the present application.

[0099] S620. Search the mapping relationships for data governance indicators corresponding to data governance objectives that match the reference data governance objectives, as multiple candidate data governance indicators.

[0100] Furthermore, data governance indicators corresponding to data governance objectives that match each reference data governance objective can be found in the mapping relationship as multiple candidate data governance indicators. It should be noted that some of the multiple candidate data governance indicators may be valid data governance indicators, and some may be invalid data governance indicators.

[0101] S630: Filter at least one candidate data governance indicator in the indicator set from the candidate data governance indicators as each first sub-indicator.

[0102] Specifically, the computer device can select at least one candidate data governance indicator in the indicator set from the candidate data governance indicators, that is, the effective data governance indicator as each first sub-indicator. It should be noted here that the at least one candidate data governance indicator selected is the same as some data governance indicators in the indicator set.

[0103] It should be noted here that the above-mentioned first sub-indicators are similar to the first data governance indicators, so that in the process of constructing the data governance strategy, each first sub-indicator can be combined with the first data governance indicators to effectively supplement or enhance the first data governance indicators, thereby improving the effectiveness, reliability or accuracy of the corresponding data governance strategy constructed, and improving the governance effect of the constructed data governance strategy.

[0104] The technical solution in the embodiment of the present application obtains multiple reference data governance objectives, searches for data governance indicators corresponding to data governance objectives that match each reference data governance objective in a mapping relationship as multiple candidate data governance indicators, and selects at least one candidate data governance indicator in the indicator set from each candidate data governance indicator as each first sub-indicator; the above method can select multiple corresponding valid data governance indicators according to multiple reference data governance objectives to prepare for the subsequent construction of a control data governance strategy, and the processing process is relatively simple and does not require the participation of complex algorithms, thereby speeding up the acquisition of the first sub-indicator and improving the efficiency of acquiring the first sub-indicator.

[0105] In one embodiment, the second data governance indicator includes a second sub-indicator; as shown in FIG. 7 , the step of determining at least one second data governance indicator corresponding to each first data governance indicator according to a preset indicator set and a mapping relationship in S600 may be implemented in the following manner:

[0106] S640. Obtain multiple third data governance targets.

[0107] Specifically, the computer device can arbitrarily obtain multiple data governance objectives as multiple third data governance objectives, wherein the multiple third data governance objectives are different from the multiple reference data governance objectives.

[0108] In one embodiment, as shown in FIG8 , the step of acquiring multiple third data governance targets in S640 may include:

[0109] S641. Obtain multiple original data governance goals; and divide historical data governance issues into multiple problem sets; each original data governance goal covers at least one problem set.

[0110] The above-mentioned historical data governance issues may include multiple data governance issues existing in multiple traditional data governance strategies counted in a historical time period. Specifically, the computer device may classify each data governance issue in the historical data governance issues to obtain multiple different types of problem sets. At the same time, each problem set may cover specific governance requirement information.

[0111] S642. For any original data governance goal, if there is no overlap between at least one problem set covered by the original data governance goal and at least one problem set covered by each first data governance goal, the original data governance goal is determined as the third data governance goal.

[0112] Among them, each of the third data governance objectives can be a data governance objective that is complementary to each of the first data governance objectives. Optionally, a corresponding second sub-indicator can be determined according to each of the third data governance objectives, so that a corresponding comparison data governance strategy can be constructed according to each of the second sub-indicators, so that the constructed comparison data governance strategy can comprehensively cover various potential data governance issues, effectively solve the omissions and deficiencies that may occur in traditional data governance strategies, and make the constructed comparison data governance strategy more systematic and comprehensive.

[0113] In actual applications, for any original data governance goal, the computer device can call a data analysis tool to evaluate the original data governance goal and each first data governance goal to determine whether there is overlap between at least one problem set covered by the original data governance goal and at least one problem set covered by each first data governance goal. If so, it is determined that there is overlap between at least one problem set covered by the original data governance goal and at least one problem set covered by each first data governance goal. Otherwise, it is determined that there is no overlap between at least one problem set covered by the original data governance goal and at least one problem set covered by each first data governance goal. Among them, evaluating the original data governance goal and each first data governance goal refers to the process of comparing or contrasting the original data governance goal and each first data governance goal.

[0114] Further, when it is determined that there is no overlap between at least one problem set covered by the original data governance goal and at least one problem set covered by each first data governance goal, the original data governance goal can be determined as the third data governance goal, so as to effectively fill the gaps of the first data governance goal through the third data governance goal, so that the determined data governance strategy is richer and more comprehensive, thereby avoiding repeated governance of the determined data governance strategy. In the embodiment of the present application, the introduction of complementary data governance goals not only helps to systematically solve data governance problems, but also forms a good synergy between different data governance strategies, so that in actual operation, the data governance strategy constructed based on the third data governance goal can achieve higher governance efficiency and better governance effect.

[0115] S650. Search the mapping relationships for data governance indicators corresponding to data governance objectives that match each third data governance objective as multiple candidate data governance indicators.

[0116] Furthermore, data governance indicators corresponding to data governance objectives that match each third data governance objective may be searched in the mapping relationship as multiple candidate data governance indicators. Since the multiple reference data governance objectives and the multiple third data governance objectives are different, naturally, the multiple candidate data governance indicators here are different from the multiple candidate data governance indicators in S620 above.

[0117] S660: Filter at least one candidate data governance indicator in the indicator set from the candidate data governance indicators as each second sub-indicator.

[0118] It should be noted that the implementation of step S660 is similar to that of step S630, and this embodiment of the present application does not limit this. In addition, the at least one second data governance indicator may be at least one of the first sub-indicator and the second sub-indicator.

[0119] For example, if the first data governance indicators are A, B and C, the first sub-indicators are D, E and F, and the second sub-indicators are G, H and I, the computer device can arrange and combine the first data governance indicators with the first sub-indicators and the second sub-indicators to obtain multiple groups of control data governance indicator sets, and then construct multiple control data governance strategies according to the groups of control data governance indicator sets. Each group of control data governance indicator sets can include an arrangement and combination of A, B, C and at least one of the first sub-indicators and the second sub-indicators (i.e., D, E, F, G, H and I).

[0120] The technical solution in the embodiment of the present application obtains multiple third data governance objectives, searches for data governance indicators corresponding to data governance objectives that match each third data governance objective in the mapping relationship as multiple candidate data governance indicators, and selects at least one candidate data governance indicator in the indicator set from each candidate data governance indicator as each second sub-indicator; the above method can select multiple corresponding valid data governance indicators according to multiple third data governance objectives to prepare for the subsequent construction of a control data governance strategy, and the processing process is relatively simple and does not require the participation of complex algorithms, thereby speeding up the acquisition of the second sub-indicators and improving the efficiency of acquiring the second sub-indicators.

[0121] The following is an explanation of the process of performing maturity evaluation on each data governance strategy to be evaluated based on each first governance data and each second governance data. In one embodiment, as shown in FIG9 , the steps in S200 above can be implemented in the following manner:

[0122] S210: Determine a processing strategy corresponding to the error rate between each first-governed data and each second-governed data according to the actual data type of each to-be-governed data.

[0123] It should be noted here that the above processing strategy can be understood as a specific method or process for calculating the error rate between each first treated data and each second treated data.

[0124] The actual data types of the data to be governed are different, and correspondingly, the processing strategies corresponding to the error rates between the first governed data and the second governed data are different.

[0125] In actual applications, the computer device can search for the actual data type of each to-be-managed data in the association relationship table between different data types and different processing strategies, and then obtain the processing strategy corresponding to the data type matching each actual data type in the association relationship table, and determine the processing strategy corresponding to the error rate between each first managed data and each second managed data. In the embodiment of the present application, the processing strategies corresponding to different actual data types are described as follows:

[0126] a. If the actual data type is structured data, the error rate between the first processed data and the second processed data can be expressed as:

[0127] (1)

[0128] in, 1 indicates the data after the first governance. Represents the data after the second governance.

[0129] b. If the actual data type is semi-structured data, the error rate between the first governed data and the second governed data can be equal to the structural error rate between the first governed data and the second governed data. , Field Error Rate and The result of performing arithmetic operation. Optionally, the arithmetic operation can be implemented by at least one of addition, subtraction, logarithm, exponential, multiplication, etc., but in the embodiment of the present application, the arithmetic operation can be a weighted summation process. The formulas can be expressed as:

[0130] (2)

[0131] (3)

[0132] (4)

[0133] in, Represents the hierarchical structure in the data after the first governance, Represents the hierarchical structure in the second governance data, Indicates the field value in the first processed data. Represents the field value in the second processed data. Indicates the number of missing fields between the first processed data and the second processed data. represents the total number of fields in the first processed data and the second processed data. It can reflect whether there are any field omissions or redundancies in the data to be governed during the data governance process.

[0134] It should be noted here that the first governed data and the second governed data can be parsed to obtain the hierarchical structure and field values ​​in the first governed data, as well as the hierarchical structure and fields in the second governed data. Among them, if there are missing fields, different nesting levels, or changes in key-value pairs between the hierarchical structures in the first governed data and the second governed data, the structural error rate between the first governed data and the second governed data is large, otherwise, the structural error rate is small; at the same time, if there is a large difference between the field values ​​in the first governed data and the second governed data, the field error rate between the first governed data and the second governed data is large, otherwise, the field error rate is small.

[0135] c. (1) If the actual data type is unstructured data and the unstructured data is text data, then the error rate between the first processed data and the second processed data can be equal to the text error rate. and keyword error rate The result of arithmetic processing; among them, the text error rate It can be expressed by the following formula (5) or (6), and the keyword error rate It can be expressed by formula (7):

[0136] (5)

[0137] (6)

[0138] (7)

[0139] in, Indicates the length of the data after the first treatment. Indicates the length of the second processed data. represents the edit distance between the first and second processed data, Represents the vocabulary or character set in the first processed data, Represents the vocabulary or character set in the second processed data, Indicates the total number of keywords that are not extracted or incorrectly extracted from the first processed data and the second processed data, represents the total number of correct keywords extracted from the first processed data and the second processed data. Optionally, the edit distance between the first processed data and the second processed data may be calculated using, but is not limited to, an edit distance method or a Jaccard similarity coefficient.

[0140] (2) If the unstructured data is image data, the error rate between the first processed data and the second processed data can be equal to the image error rate and image feature error rate The result of arithmetic operation; among them, the image error rate This can be achieved using mean square error, image error rate and image feature error rate They can be expressed by formulas (8) and (9) respectively:

[0141] (8)

[0142] (9)

[0143] in, represents the total number of pixels of the first processed data or the second processed data (the total number of pixels of the first processed data is equal to the total number of pixels of the second processed data), Indicates the first governance data The pixel value of pixels, Indicates the second governance data The pixel value of pixels; Indicates the number of unmatched feature points between the first processed data and the second processed data, Represents the total number of feature points in the first processed data and the second processed data. Optionally, a feature extraction algorithm (such as edge detection method, object recognition method, etc.) can be used to extract features from the first processed data and the second processed data to obtain feature points of the first processed data and feature points of the second processed data, and then a feature point matching algorithm (such as SIFT method, ORB method, etc.) can be used to calculate the matching degree of the feature points of the first processed data and the feature points of the second processed data to obtain .

[0144] (3) If the unstructured data is audio data, the error rate between the first processed data and the second processed data can be achieved by comparing the waveform difference between the first processed data and the second processed data using the mean square error method; the error rate between the first processed data and the second processed data can be expressed by formula (10):

[0145] (10)

[0146] in, Indicates the total duration of the first governance data or the second governance data (the total duration of the first governance data is equal to the total duration of the second governance data). represents the audio signal at time j in the first processed data, Represents the audio signal at time j in the second processed data.

[0147] (4) If the unstructured data is video data, the error rate between the first processed data and the second processed data can be achieved by comparing the frame difference between the first processed data and the second processed data using a video frame difference method or a video frame matching method; the error rate between the first processed data and the second processed data can be equal to the video frame error rate and video frame feature error rate The result of arithmetic operation; among them, the video frame error rate It can be achieved by using mean square error, video frame error rate and video frame feature error rate They can be expressed by formulas (11) and (12) respectively as:

[0148] (11)

[0149] (12)

[0150] in, represents the total number of video frames of the first processed data or the second processed data (the total number of video frames of the first processed data is equal to the total number of video frames of the second processed data), Indicates the first governance data The frame data of the video frames, Indicates the second governance data Frame data of video frames; Indicates the number of video frames that do not match between the first processed data and the second processed data, Indicates the total number of video frames in the first processed data and the second processed data.

[0151] S220: Determine the error rate between each first processed data and each second processed data according to each processing strategy.

[0152] Specifically, the computer device may calculate the error rate between the first governed data and the second governed data corresponding to each to-be-governed data according to each processing strategy.

[0153] S230. Determine the maturity evaluation result of each data governance strategy to be evaluated according to the error rate between each first governed data and each second governed data.

[0154] In one embodiment, the computer device can perform at least one of analysis processing, comparison processing, matching processing, etc. on the error rate between each first-governed data and each second-governed data, and obtain the maturity assessment result of each data governance strategy to be assessed based on the processing operation results.

[0155] In another embodiment, the computer device may send the error rate between each first governed data and each second governed data to a third-party device, instructing the third-party device to determine the maturity assessment results of each data governance policy to be evaluated based on each error rate. Correspondingly, the computer device receives the maturity assessment results of each data governance policy to be evaluated sent by the third-party device to obtain the maturity assessment results of each data governance policy to be evaluated.

[0156] In one embodiment, the step of determining the maturity evaluation result of each data governance strategy to be evaluated according to the error rate between each first governed data and each second governed data in S230 may include:

[0157] For any first governed data, if the error rate between the first governed data and the corresponding second governed data is greater than the preset threshold, the maturity assessment result of the data governance strategy to be evaluated corresponding to the first governed data is determined to be unreliable; if the error rate between the first governed data and the corresponding second governed data is less than or equal to the preset threshold, the maturity assessment result of the data governance strategy to be evaluated is determined to be reliable.

[0158] Optionally, the preset threshold may be user-defined or determined based on historical experience, which is not limited in the embodiments of the present application.

[0159] In the embodiment of the present application, for any first governed data, if the error rate between the first governed data and the corresponding second governed data is greater than a preset threshold, it indicates that the difference between the data governance strategy to be evaluated corresponding to the first governed data and the corresponding control data governance strategy is large, and the maturity assessment result of the data governance strategy to be evaluated can be determined to be that the data governance strategy to be evaluated is unreliable. At the same time, if the error rate between the first governed data and the corresponding second governed data is less than or equal to the preset threshold, it indicates that the difference between the data governance strategy to be evaluated corresponding to the first governed data and the corresponding control data governance strategy is small or no difference, and the maturity assessment result of the data governance strategy to be evaluated can be determined to be that the data governance strategy to be evaluated is reliable.

[0160] It should be noted here that if the data governance strategy to be evaluated is unreliable, it means that the data governance strategy to be evaluated is immature and cannot be used as a subsequent reliable or effective data governance strategy; if the data governance strategy to be evaluated is reliable, it means that the data governance strategy to be evaluated is relatively mature and can be used as a subsequent reliable or effective data governance strategy.

[0161] In addition, the maturity assessment result of the above-mentioned data governance strategy to be assessed can represent the maturity level of the data governance strategy to be assessed; specifically, the computer device can determine the maturity assessment level of the corresponding data governance strategy to be assessed according to the corresponding threshold range of the error rate between the first governed data and the corresponding second governed data. Exemplarily, if the error rate between the first governed data and the corresponding second governed data falls within the range of 0%-2%, the maturity assessment level of the corresponding data governance strategy to be assessed is determined to be high; if the error rate between the first governed data and the corresponding second governed data falls within the range of 2%-5%, the maturity assessment level of the corresponding data governance strategy to be assessed is determined to be medium; if the error rate between the first governed data and the corresponding second governed data falls within the range of more than 5%, the maturity assessment level of the corresponding data governance strategy to be assessed is determined to be low.

[0162] The technical solution in the embodiment of the present application determines the processing strategy corresponding to the error rate between each first governed data and each second governed data according to the actual data type of each data to be governed, determines the error rate between each first governed data and each second governed data according to each processing strategy, and determines the maturity assessment result of each data governance strategy to be assessed according to the error rate between each first governed data and each second governed data; the above method can determine the error rate between the first governed data and the second governed data corresponding to different data to be governed according to the actual data type of different data to be governed, so that the determined error rate has higher accuracy, and then the maturity assessment result of each data governance strategy to be assessed can be accurately determined according to the acquired error rates, thereby improving the correctness of the determined maturity assessment result; at the same time, the above method can be applicable to various types of data to be governed, and has no limitations on the usage scenarios of the maturity assessment method, thereby improving the wide applicability of the maturity assessment method.

[0163] In one embodiment, the present application also provides a maturity assessment method, which is applied to a computer device. The method includes the following process:

[0164] (1) Construct a mapping relationship based on the governance requirement information, different data governance indicators, and different data governance goals corresponding to different standard data types;

[0165] (2) according to the actual data types of the data to be governed, searching in the mapping relationship for data governance targets corresponding to the standard data types that match the actual data types as the first data governance targets;

[0166] (3) constructing each data governance strategy to be evaluated based on at least one first data governance indicator and each first data governance goal corresponding to each actual data type;

[0167] (4) Determining at least one second data governance indicator corresponding to each first data governance indicator according to a preset indicator set and mapping relationship; the second data governance indicator includes a first sub-indicator and a second sub-indicator;

[0168] The above step (4) may be implemented in the following manner:

[0169] (41) performing similarity processing on the multiple original data governance objectives and each first data governance objective to determine a similarity value between each original data governance objective and each first data governance objective;

[0170] (42) selecting, from each original data governance objective, a plurality of reference data governance objectives whose similarity values ​​are greater than a preset similarity threshold;

[0171] (43) searching for data governance indicators corresponding to data governance objectives that match each reference data governance objective in the mapping relationship as multiple candidate data governance indicators;

[0172] (44) selecting at least one candidate data governance indicator in the indicator set from each candidate data governance indicator as each first sub-indicator;

[0173] (45) obtaining a plurality of original data governance objectives; and dividing the historical data governance problems into a plurality of problem sets; each original data governance objective covers at least one problem set;

[0174] (46) For any original data governance objective, if there is no overlap between at least one problem set covered by the original data governance objective and at least one problem set covered by each of the first data governance objectives, the original data governance objective is determined as the third data governance objective;

[0175] (47) searching, in the mapping relationship, for data governance indicators corresponding to data governance objectives that match each third data governance objective as multiple candidate data governance indicators;

[0176] (48) selecting at least one candidate data governance indicator in the indicator set from each candidate data governance indicator as each second sub-indicator;

[0177] (5) constructing respective comparative data governance strategies according to respective first data governance indicators, respective second data governance indicators and at least one second data governance objective;

[0178] (6) performing data governance processing on each data to be governed according to at least one data governance strategy to be evaluated, to obtain a plurality of first governed data; and performing data governance processing on each data to be governed according to a reference data governance strategy corresponding to each data governance strategy to be evaluated, to obtain a plurality of second governed data; the reference data governance strategy is a pre-constructed data governance strategy that is similar to or complementary to the corresponding data governance strategy to be evaluated;

[0179] (7) Determining a processing strategy corresponding to the error rate between each first-governed data and each second-governed data according to the actual data type of each data to be governed;

[0180] (8) determining an error rate between each first treated data and each second treated data according to each processing strategy;

[0181] (9) For any first-governed data, if the error rate between the first-governed data and the corresponding second-governed data is greater than a preset threshold, the maturity assessment result of the data governance policy to be assessed corresponding to the first-governed data is determined to be unreliable;

[0182] (10) If the error rate between the first governed data and the corresponding second governed data is less than or equal to a preset threshold, the maturity assessment result of the data governance strategy to be assessed is determined to be reliable.

[0183] The execution process of the above (1) to (10) can be specifically referred to the description of the above embodiment. The implementation principle and technical effect are similar and will not be repeated here.

[0184] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0185] Based on the same inventive concept, the embodiment of the present application also provides a maturity assessment device for implementing the maturity assessment method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more maturity assessment device embodiments provided below can refer to the limitations of the maturity assessment method above, and will not be repeated here.

[0186] In one embodiment, FIG10 is a schematic diagram of the structure of a maturity assessment device in an embodiment of the present application. The maturity assessment device provided in the embodiment of the present application can be applied to a computer device. As shown in FIG10 , the maturity assessment device in the embodiment of the present application can include: a processing module 11 and a maturity assessment module 12, wherein:

[0187] The processing module 11 is used to perform data governance processing on each data to be governed according to at least one data governance strategy to be evaluated, so as to obtain a plurality of first governed data; and to perform data governance processing on each data to be governed according to a reference data governance strategy corresponding to each data governance strategy to be evaluated, so as to obtain a plurality of second governed data; the reference data governance strategy is a pre-constructed data governance strategy that is similar to or complementary to the corresponding data governance strategy to be evaluated;

[0188] The maturity assessment module 12 is used to perform maturity assessment on each data governance strategy to be assessed based on each first governed data and each second governed data, and determine the maturity assessment result of each data governance strategy to be assessed.

[0189] The maturity assessment device provided in the embodiment of the present application can be used to execute the technical solution in the above-mentioned maturity assessment method embodiment of the present application. Its implementation principle and technical effect are similar and will not be repeated here.

[0190] In one embodiment, the maturity assessment module 12 includes: a first determination unit, a second determination unit and a third determination unit, wherein:

[0191] A first determining unit, configured to determine a processing strategy corresponding to an error rate between each first processed data and each second processed data according to an actual data type of each to-be-processed data;

[0192] A second determining unit, for determining an error rate between each first treated data and each second treated data according to each processing strategy;

[0193] The third determining unit is used to determine the maturity evaluation result of each data governance strategy to be evaluated according to the error rate between each first governed data and each second governed data.

[0194] The maturity assessment device provided in the embodiment of the present application can be used to execute the technical solution in the above-mentioned maturity assessment method embodiment of the present application. Its implementation principle and technical effect are similar and will not be repeated here.

[0195] In one embodiment, the third determining unit is specifically configured to:

[0196] For any first governed data, if the error rate between the first governed data and the corresponding second governed data is greater than a preset threshold, it is determined that the maturity assessment result of the data governance policy to be assessed corresponding to the first governed data is unreliable;

[0197] If the error rate between the first governed data and the corresponding second governed data is less than or equal to a preset threshold, it is determined that the maturity assessment result of the data governance strategy to be assessed is reliable.

[0198] The maturity assessment device provided in the embodiment of the present application can be used to execute the technical solution in the above-mentioned maturity assessment method embodiment of the present application. Its implementation principle and technical effect are similar and will not be repeated here.

[0199] In one embodiment, the maturity assessment device further comprises: a mapping relationship building module, a search module and a first strategy building module, wherein:

[0200] A mapping relationship building module is used to build mapping relationships based on the governance requirement information corresponding to different standard data types, different data governance indicators, and different data governance goals;

[0201] A search module, used to search, according to the actual data type of each to-be-managed data, in the mapping relationship for data management targets corresponding to the standard data types that match each actual data type as multiple first data management targets;

[0202] The first strategy building module is used to build each data governance strategy to be evaluated according to at least one first data governance indicator and each first data governance goal corresponding to each actual data type.

[0203] The maturity assessment device provided in the embodiment of the present application can be used to execute the technical solution in the above-mentioned maturity assessment method embodiment of the present application. Its implementation principle and technical effect are similar and will not be repeated here.

[0204] In one embodiment, the maturity assessment device further comprises: a determination module and a second strategy building module, wherein:

[0205] A determination module, configured to determine at least one second data governance indicator corresponding to each first data governance indicator according to a preset indicator set and a mapping relationship;

[0206] The second strategy building module is used to build each comparison data governance strategy according to each first data governance indicator, each second data governance indicator and at least one second data governance goal.

[0207] The maturity assessment device provided in the embodiment of the present application can be used to execute the technical solution in the above-mentioned maturity assessment method embodiment of the present application. Its implementation principle and technical effect are similar and will not be repeated here.

[0208] In one embodiment, the second data governance indicator includes a first sub-indicator; the determination module includes: a first acquisition unit, a first search unit and a first screening unit, wherein:

[0209] A first acquisition unit, used to acquire multiple reference data governance targets;

[0210] A first search unit is used to search for data governance indicators corresponding to data governance objectives that match each reference data governance objective in the mapping relationship as multiple candidate data governance indicators;

[0211] The first screening unit is used to screen at least one candidate data governance indicator in the indicator set from the candidate data governance indicators as each first sub-indicator.

[0212] The maturity assessment device provided in the embodiment of the present application can be used to execute the technical solution in the above-mentioned maturity assessment method embodiment of the present application. Its implementation principle and technical effect are similar and will not be repeated here.

[0213] In one embodiment, the first acquisition unit is specifically used for:

[0214] Perform similarity processing on the multiple original data governance objectives and each first data governance objective to determine a similarity value between each original data governance objective and each first data governance objective;

[0215] A plurality of reference data governance objectives whose similarity values ​​are greater than a preset similarity threshold are selected from each original data governance objective.

[0216] The maturity assessment device provided in the embodiment of the present application can be used to execute the technical solution in the above-mentioned maturity assessment method embodiment of the present application. Its implementation principle and technical effect are similar and will not be repeated here.

[0217] In one embodiment, the second data governance indicator includes a second sub-indicator; the determination module includes: a second acquisition unit, a second search unit, and a second screening unit, wherein:

[0218] A second acquisition unit, used to acquire multiple third data governance targets;

[0219] A second searching unit is used to search the mapping relationship for data governance indicators corresponding to data governance objectives that match each third data governance objective as multiple candidate data governance indicators;

[0220] The second screening unit is used to screen at least one candidate data governance indicator in the indicator set from the candidate data governance indicators as each second sub-indicator.

[0221] The maturity assessment device provided in the embodiment of the present application can be used to execute the technical solution in the above-mentioned maturity assessment method embodiment of the present application. Its implementation principle and technical effect are similar and will not be repeated here.

[0222] In one embodiment, the second acquisition unit is specifically used for:

[0223] Acquire multiple original data governance objectives; and divide the historical data governance issues into multiple problem sets; each original data governance objective covers at least one problem set;

[0224] For any original data governance goal, if there is no overlap between at least one problem set covered by the original data governance goal and at least one problem set covered by each first data governance goal, the original data governance goal is determined as the third data governance goal.

[0225] The maturity assessment device provided in the embodiment of the present application can be used to execute the technical solution in the above-mentioned maturity assessment method embodiment of the present application. Its implementation principle and technical effect are similar and will not be repeated here.

[0226] The specific definition of the maturity assessment device can be found in the definition of the maturity assessment method above, which will not be repeated here. Each module in the above maturity assessment device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0227] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in FIG11. The computer device includes a processor, a memory, and a network interface connected via a system bus. Among them, the processor of the computer device is used to provide processing capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store each data to be governed, each data governance strategy to be evaluated, and each control data governance strategy. The network interface of the computer device is used to communicate with an external endpoint through a network connection. When the computer program is executed by the processor, a maturity assessment method is implemented.

[0228] Those skilled in the art will understand that the structure shown in FIG. 11 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0229] In one embodiment, a computer device is also provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the technical solution in the above-mentioned maturity assessment method embodiment of the present application is implemented. The implementation principle and technical effect are similar and will not be repeated here.

[0230] In one embodiment, a computer-readable storage medium is also provided, on which a computer program is stored. When the computer program is executed by a processor, the technical solution of the maturity assessment method mentioned above in the present application is implemented. The implementation principle and technical effect are similar and will not be repeated here.

[0231] In one embodiment, a computer program product is also provided, including a computer program. When the computer program is executed by a processor, the technical solution of the maturity assessment method mentioned above in the present application is implemented. The implementation principle and technical effect are similar and will not be repeated here.

[0232] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0233] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0234] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A maturity assessment method, characterized in that: The method comprises: Performing data governance processing on each data to be governed according to at least one data governance strategy to be evaluated to obtain a plurality of first governed data; and performing data governance processing on each data to be governed according to a reference data governance strategy corresponding to each of the data governance strategies to be evaluated to obtain a plurality of second governed data; the reference data governance strategy is a pre-constructed data governance strategy that is similar or complementary to the corresponding data governance strategy to be evaluated; Based on each of the first governed data and each of the second governed data, a maturity assessment is performed on each of the data governance policies to be assessed, and a maturity assessment result of each of the data governance policies to be assessed is determined.

2. The method according to claim 1, characterized in that The step of performing maturity assessment on each of the data governance policies to be assessed based on each of the first governed data and each of the second governed data, and determining a maturity assessment result of each of the data governance policies to be assessed, includes: Determine, according to the actual data type of each of the to-be-governed data, a processing strategy corresponding to the error rate between each of the first-governed data and each of the second-governed data; According to each of the processing strategies, determining an error rate between each of the first treated data and each of the second treated data; The maturity evaluation result of each of the data governance policies to be evaluated is determined according to the error rate between each of the first governed data and each of the second governed data.

3. The method according to claim 2, characterized in that Determining the maturity evaluation result of each of the to-be-evaluated data governance strategies according to the error rate between each of the first-governed data and each of the second-governed data includes: For any first governed data, if the error rate between the first governed data and the corresponding second governed data is greater than a preset threshold, it is determined that the maturity assessment result of the data governance policy to be assessed corresponding to the first governed data is unreliable; If the error rate between the first governed data and the corresponding second governed data is less than or equal to the preset threshold, it is determined that the maturity assessment result of the data governance policy to be assessed is reliable.

4. The method according to any one of claims 1 to 3, characterized in that The process of constructing each of the data governance strategies to be evaluated includes: Build mapping relationships based on governance requirement information, different data governance indicators, and different data governance goals corresponding to different standard data types; According to the actual data types of the data to be managed, searching in the mapping relationship for data management targets corresponding to standard data types that match the actual data types as multiple first data management targets; Each of the data governance strategies to be evaluated is constructed according to at least one first data governance indicator corresponding to each of the actual data types and each of the first data governance objectives.

5. The method according to claim 4, characterized in that The construction process of each of the control data governance strategies includes: Determine, according to a preset indicator set and the mapping relationship, at least one second data governance indicator corresponding to each of the first data governance indicators; Each of the comparison data governance policies is constructed according to each of the first data governance indicators, each of the second data governance indicators and at least one second data governance goal.

6. The method according to claim 5, characterized in that The second data governance indicator includes a first sub-indicator; and determining at least one second data governance indicator corresponding to each of the first data governance indicators according to the preset indicator set and the mapping relationship includes: Get multiple reference data governance objectives; Searching for data governance indicators corresponding to data governance objectives that match each of the reference data governance objectives in the mapping relationship as multiple candidate data governance indicators; Selecting at least one candidate data governance indicator in the indicator set from the candidate data governance indicators as each of the first sub-indicators; Correspondingly, the obtaining of multiple reference data governance objectives includes: Perform similarity processing on the multiple original data governance objectives and each first data governance objective to determine a similarity value between each original data governance objective and each first data governance objective; The multiple reference data governance objectives whose similarity values ​​are greater than a preset similarity threshold are selected from each of the original data governance objectives.

7. The method according to claim 5, characterized in that The second data governance indicator includes a second sub-indicator; the determining, according to the preset indicator set and the mapping relationship, at least one second data governance indicator corresponding to each of the first data governance indicators includes: Acquire multiple third-party data governance objectives; Searching for data governance indicators corresponding to data governance objectives that match each of the third data governance objectives in the mapping relationship as multiple candidate data governance indicators; Selecting at least one candidate data governance indicator in the indicator set from the candidate data governance indicators as each of the second sub-indicators; Correspondingly, the obtaining of multiple third data governance objectives includes: Acquire multiple original data governance objectives; and divide the historical data governance issues into multiple problem sets; each original data governance objective covers at least one problem set; For any original data governance goal, if there is no overlap between at least one problem set covered by the original data governance goal and at least one problem set covered by each of the first data governance goals, the original data governance goal is determined as the third data governance goal.

8. A maturity assessment device, characterized in that: The device comprises: A processing module, configured to perform data governance processing on each data to be governed according to at least one data governance strategy to be evaluated, to obtain a plurality of first governed data; and to perform data governance processing on each data to be governed according to a reference data governance strategy corresponding to each of the data governance strategies to be evaluated, to obtain a plurality of second governed data; the reference data governance strategy is a pre-constructed data governance strategy that is similar to or complementary to the corresponding data governance strategy to be evaluated; The maturity assessment module is used to perform maturity assessment on each of the data governance policies to be assessed based on each of the first governed data and each of the second governed data, and determine the maturity assessment results of each of the data governance policies to be assessed.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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