Data asset value evaluation method and device based on data-in-data platform

Abstract

The invention provides a data asset value evaluation method and device based on a data-in-data platform, and the method comprises the steps: obtaining a plurality of use parameters of target data in a data use region, and calculating the data use value of the target data according to the plurality of use parameters of the target data; moving the data of which the data use value meets the requirement to a data buffer area of a data middle table, and performing data treatment on the target data to obtain a plurality of content evaluation parameters; calculating the data content value of the target data based on the plurality of content evaluation parameters of the target data; calculating a data asset evaluation value of the target data according to the data use value and the data content value of the target data; according to the invention, automatic identification of the data and evaluation of the data asset value are realized, comprehensive and accurate evaluation of the data asset value of the data is realized, and the problem of limitation in the prior art is solved.

Description

Technical Field

[0001] This application relates to the field of information technology, and particularly to a method and device for evaluating the value of data assets based on a data middle platform. Background Art

[0002] With the rapid development of information technology, data has become an important asset of enterprises, and the evaluation of data asset value has become an important basis for enterprise decision-making, resource allocation, and market transactions. How to accurately evaluate the value of data assets in the data middle platform has become an important issue faced by enterprises. The evaluation of data assets plays a key role in the high-quality development of the digital economy. It is not only an important means to ensure the orderly circulation and value excavation of data elements, but also of great significance to promote the market-oriented allocation of data elements. The evaluation of data assets is not only a measurement and analysis of the value of enterprise data, but also an important tool to promote enterprise data management and decision-making, which is of great significance to the competitiveness and future development of enterprises. The evaluation of data assets is one of the important pre-work for promoting data assetization, and has particularity and complexity compared with traditional asset evaluation. The key means of evaluating the value of data assets refers to the professional service behavior of asset evaluation institutions and their asset evaluation professionals to comply with laws, administrative regulations, and asset evaluation standards, and to evaluate and estimate the value of data assets for specific purposes on the evaluation benchmark date according to the entrustment, and issue an asset evaluation report.

[0003] According to the content of the "Guiding Opinions on Data Asset Evaluation" formulated by the China Appraisal Society, data assets refer to data resources that are legally owned or controlled by a specific entity, can be measured in currency, and can bring direct or indirect economic benefits. The importance of data asset evaluation lies in that with the booming development of the data economy, data assets have become a key factor in the competitiveness of enterprises. Accurately evaluating the value of data assets helps enterprises rationally allocate resources, improve operational efficiency, and provide strong support for major decisions such as financing, mergers and acquisitions, and listing of enterprises.

[0004] There are usually three methods for the existing data asset evaluation: the cost method, the market method, and the income method. The cost method is to evaluate based on the formation cost of data assets. This method takes into account the costs such as data collection, storage, processing, and maintenance. For some data assets, it is still reasonable to use the cost method for value evaluation. The expression of the cost method model is: P = TC × (1 + ROIC) × U, where TC is the total cost, ROIC is the rate of return on invested capital, and U is the usage premium. The market method is to evaluate the value by comparing the transaction prices of similar data assets in the market. This method relies on the transaction data and price information of similar data assets in the market. In terms of the calculation formula, we may use: Evaluation value = Comparable case value × Technical correction coefficient × Value density correction coefficient × Date correction coefficient × Capacity correction coefficient × Other correction coefficients. The income method is to evaluate the value by predicting the future income that data assets can generate. Although the situation of directly obtaining income from data is relatively rare, the income of data assets can be reasonably estimated based on market trends and analysis.

[0005] The data middle platform is an important architecture for enterprise data management and application, aiming to integrate data resources inside and outside the enterprise, provide data services, and support data analysis and applications. The data middle platform usually includes modules such as data collection, data storage, data processing, data analysis, and data services, and can provide comprehensive data support for enterprises. In the data asset evaluation, the role of the data middle platform is mainly reflected in the following aspects:

[0006] Data integration: The data middle platform can integrate data resources inside and outside the enterprise, provide a unified data view, and help to comprehensively evaluate the value of data assets.

[0007] Data processing: The data middle platform provides powerful data processing capabilities, can clean, transform, and integrate data, improve data quality, and provide a reliable data basis for data asset evaluation.

[0008] Data analysis: The data middle platform provides data analysis tools and methods, can conduct in-depth analysis of data assets, mine data value, and provide a scientific basis for data asset evaluation.

[0009] Data services: The data middle platform provides data service interfaces, can support various data applications, and helps to realize the value monetization of data assets.

[0010] Although the existing data asset evaluation methods can meet the needs of enterprises to a certain extent, there are still some limitations:

[0011] Single evaluation method: The existing data asset evaluation methods often adopt a single cost method, market method, or income method, and it is difficult to comprehensively reflect the value of data assets.

[0012] Low data quality: Data quality directly affects the accuracy of data asset evaluation. Existing data asset evaluation methods often do not have strict enough requirements for data quality, resulting in inaccurate evaluation results.

[0013] Low evaluation efficiency: Existing data asset evaluation methods often require a large amount of manual operation, with low evaluation efficiency and difficulty in meeting the needs of large-scale data asset evaluation.

[0014] Lack of dynamic evaluation: Existing data asset evaluation methods often adopt static evaluation methods, which are difficult to reflect the dynamic changes in the value of data assets. Summary of the Invention

[0015] This application aims to solve at least one of the technical problems in the related art to some extent.

[0016] To this end, the first object of this application is to propose a data asset value evaluation method based on a data middle platform to accurately and comprehensively evaluate the value of data assets and solve the limitations in the related art.

[0017] The second object of this application is to propose a data asset value evaluation device based on a data middle platform.

[0018] The third object of this application is to propose an electronic device.

[0019] The fourth object of this application is to propose a computer-readable storage medium.

[0020] The fifth object of this application is to propose a computer program product.

[0021] To achieve the above object, the first aspect embodiment of this application proposes a data asset value evaluation method based on a data middle platform, including:

[0022] Obtain multiple usage parameters of target data stored in the data usage area of the data middle platform;

[0023] According to the multiple usage parameters of the target data, calculate the data usage value of the target data through a usage value calculation model;

[0024] If the data usage value of the target data meets the first value threshold, move the target data to the data buffer area of the data middle platform and perform data governance on the target data to obtain multiple content evaluation parameters of the target data;

[0025] Based on the multiple content evaluation parameters of the target data, calculate the data content value of the target data through a content value calculation model;

[0026] According to the data usage value and data content value of the target data, the data asset evaluation value of the target data is calculated through a value evaluation model.

[0027] To achieve the above object, an embodiment of the second aspect of the present application provides a data asset value evaluation device based on a data middle platform, including:

[0028] An initial data acquisition module, configured to acquire multiple usage parameters of target data stored in the data usage area of the data middle platform;

[0029] A usage value calculation module, configured to calculate the data usage value of the target data through a usage value calculation model according to the multiple usage parameters of the target data;

[0030] A data governance module, configured to move the target data to the data buffer area of the data middle platform and perform data governance on the target data to obtain multiple content evaluation parameters of the target data if the data usage value of the target data meets a first value threshold;

[0031] A content value calculation module, configured to calculate the data content value of the target data through a content value calculation model based on the multiple content evaluation parameters of the target data;

[0032] A data asset evaluation module, configured to calculate the data asset evaluation value of the target data through a value evaluation model according to the data usage value and data content value of the target data.

[0033] To achieve the above object, an embodiment of the third aspect of the present application provides an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method described in the first aspect.

[0034] To achieve the above object, an embodiment of the fourth aspect of the present application provides a computer-readable storage medium, in which computer execution instructions are stored, and when the computer execution instructions are executed by a processor, they are used to implement the method described in the first aspect.

[0035] To achieve the above object, an embodiment of the fifth aspect of the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the method described in the first aspect.

[0036] The data asset value evaluation method, device, electronic device and storage medium provided by this application obtain multiple usage parameters of target data in the data usage area, calculate the data usage value of the target data according to the multiple usage parameters of the target data; move the data whose data usage value meets the requirements to the data buffer area of the data middle platform and perform data governance on the target data to obtain multiple content evaluation parameters; calculate the data content value of the target data based on the multiple content evaluation parameters of the target data; then calculate the data asset evaluation value of the target data according to the data usage value and data content value of the target data; realizing the automatic identification of data and the evaluation of data asset value, and realizing the comprehensive and accurate evaluation of the data asset value of data; moreover, storing data with different values in different partitions to improve the security of valuable data; this method has the advantages of being scientific, reasonable, easy to operate, etc., and can provide an enterprise with a comprehensive and accurate evaluation system to help the enterprise better manage and utilize data assets.

[0037] It can accurately and efficiently evaluate the value of data assets. Without manual intervention, it can automatically identify and evaluate data assets and their corresponding values through the functions of the data middle platform, and physically partition and isolate data assets from ordinary data to improve the security of data assets.

[0038] Additional aspects and advantages of this application will be given in part in the following description, become apparent in part from the following description, or be understood through the practice of this application. Brief Description of the Drawings

[0039] The above and / or additional aspects and advantages of this application will become apparent and easy to understand from the following description of the embodiments in conjunction with the drawings, where:

[0040] Figure 1 is a schematic flowchart of a data asset value evaluation method based on a data middle platform provided by an embodiment of this application;

[0041] Figure 2 is a block diagram of a data asset value evaluation device based on a data middle platform provided by an embodiment of this application;

[0042] Figure 3 is a block diagram of an electronic device provided by an embodiment of this application. Detailed Embodiments

[0043] The embodiments of this application will be described in detail below. Examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and are intended to explain this application and should not be construed as limiting this application.

[0044] The following describes a data asset value evaluation method, apparatus, and device based on a data middle platform according to embodiments of the present application with reference to the accompanying drawings.

[0045] Figure 1 It is a schematic flowchart of a data asset value evaluation method based on a data middle platform provided by an embodiment of the present application.

[0046] It should be noted that the execution subject of the data asset value evaluation method based on the data middle platform in the embodiments of the present application is the data asset value evaluation apparatus based on the data middle platform in the embodiments of the present application. The data asset value evaluation apparatus based on the data middle platform can be configured in an electronic device so that the electronic device can execute the data asset value evaluation function based on the data middle platform.

[0047] As Figure 1 shown, the data asset value evaluation method based on the data middle platform includes the following steps:

[0048] Step 101, obtain multiple usage parameters of target data stored in the data usage area of the data middle platform.

[0049] In the embodiments of the present application, the physical medium of the data warehouse where the data middle platform actually stores data is divided into three areas, namely the data usage area, the data buffer area, and the data asset area. Among them, the data usage area is the main area for the data middle platform to store data, with a large capacity, fast operation and query speed, ensuring the access performance of the data, but with low security. The initial storage location of all data entering the data middle platform is in the data usage area. The data buffer area is used to store data whose value needs to be verified in the data middle platform, with medium performance and security. The data asset area is used to store data identified by the data middle platform as having asset value, with higher security and focusing on the protection of data assets.

[0050] In some embodiments, the multiple usage parameters include the data usage volume, the data modification volume, and the data download volume.

[0051] Step 102, calculate the data usage value of the target data through a usage value calculation model according to the multiple usage parameters of the target data.

[0052] In some embodiments, the usage value calculation model is expressed as follows:

[0053]

[0054] Among them, v_usage represents the data usage value, which is a value in the range of (-1, 1); data_type represents the data type, and data_usage represents the data usage amount, which is used to characterize the number of times this data is called or browsed by other systems and modules; data_modify represents the data modification amount, which is used to characterize the number of times this data is modified; data_download represents the data download amount, which is used to characterize the number of times this data is downloaded.

[0055] Step 103, if the data usage value of the target data meets the first value threshold, move the target data to the data buffer of the data middle platform and perform data governance on the target data to obtain multiple content evaluation parameters of the target data.

[0056] The v_usage values of most worthless or low-value data are negative. For example, if the first value threshold is 0.4, when v_usage is greater than this threshold, move the data storage location from the data usage area to the data buffer and modify the value of the data address data_address. For the data that enters the data buffer, the data middle platform performs data cleaning and governance work to obtain the corresponding parameter values of this data, including multiple content evaluation parameters.

[0057] In some embodiments, the multiple content evaluation parameters include accuracy, integrity, consistency, reliability, data type, data business domain index, security, normativeness, effectiveness, sustainability, and user score.

[0058] Step 104, based on the multiple content evaluation parameters of the target data, calculate the data content value of the target data through the content value calculation model.

[0059] In some embodiments, the content value calculation model is expressed as follows:

[0060]

[0061] Among them,

[0062] Among them, v_content is the value of data content, A is the determinant, data_accuracy is the accuracy, which is used to measure whether the data accurately reflects the actual business situation; data_integrity is the integrity, which is used to evaluate whether the data contains all necessary fields and information; data_consistency is the consistency, which is used to evaluate the information consistency of data at different sources and different time points; data_reliability is the reliability, which is used to reflect the stability and credibility of the data; data_type is the data type, which is used to evaluate the diversity of data, such as structured data, unstructured data, etc., and has been stored previously; data_area is the data business area index, which is used to evaluate the importance of the business area to which the data belongs; data_security is the security, which is used to ensure that the data is not accessed by unauthorized personnel, and this value is calculated by the security module of the data center; data_standard is the standardization, which is used to evaluate whether data management follows industry standards and best practices; data_valid is the validity, which is used to evaluate whether the data governance strategy is effectively implemented and achieves the expected effect; data_Sustainability is the sustainability, which is used to evaluate whether the data governance strategy can be maintained and improved in the long term; data_rating is the user rating, which is obtained by the system's statistical positive and negative feedback of users on this data, and p1, p2 are parameters for adjusting the weight, which can be adjusted according to the actual business situation.

[0063] In some embodiments, the accuracy is represented by the following formula:

[0064]

[0065] Among them, a T,t represents the accuracy rate of calculating sub-data t when completing sub-data T.

[0066] In some embodiments, the integrity is represented by the following formula:

[0067]

[0068] Among them, b T,t represents the integrity of calculating sub-data t when completing sub-data T

[0069] In some embodiments, the consistency is represented by the following formula:

[0070]

[0071] Among them, c T,t represents the consistency degree of calculating sub-data t when completing sub-data T.

[0072] In some embodiments, reliability is expressed by the following formula:

[0073]

[0074] Among them, d T,t Indicates the reliable score of sub-data t calculated when sub-data T is completed, Represents the reliability score of a random sub-data t randomly extracted by the system module.

[0075] In some embodiments, data_area corresponds to different values according to different business fields, and no formula calculation is required.

[0076] In some embodiments, security is represented by the following formula:

[0077]

[0078] Among them, e T,t Indicates that the security score of sub-data t is calculated when sub-data T is completed.

[0079] In some embodiments, the normality is expressed by the following formula:

[0080]

[0081] Among them, f T,t Indicates that the canonical score of sub-data t is calculated when sub-data T is completed.

[0082] In some embodiments, the value of validity data_valid is 0 or 1, 1 represents valid, and 0 represents invalid.

[0083] In some embodiments, sustainability is represented by the following formula:

[0084]

[0085] Among them, g T,t Indicates that the sustainability score of sub-data t is calculated when sub-data T is completed.

[0086] As a way of implementation, the accuracy, completeness, consistency and reliability of data can be determined by the quality of the data center.

[0087] Can

[0088] After the management module completes the calculation, the data type, data business field index, security, standardization, effectiveness, sustainability and user rating can be calculated by the data middle platform system governance module.

[0089] In some embodiments, multiple usage parameters of the target data, multiple content evaluation parameters, data usage value, and data content value are all stored in the data information repository table in the data middle platform. The data information repository table also includes data name and data address.

[0090] The data stored in the data middle platform includes structured data and unstructured data such as documents. A data information repository table is maintained in the data middle platform, and this table is used to store relevant parameters for evaluating the value of data assets. For example, the fields included in this table may include but are not limited to: data name, data type, data usage volume, data modification volume, data download volume, data address, data usage value, accuracy, integrity, consistency, reliability, data business domain index, security, standardization, effectiveness, sustainability, user rating, and data content value.

[0091] Step 105, according to the data usage value and data content value of the target data, calculate the data asset evaluation value of the target data through the value evaluation model.

[0092] In some embodiments, the value evaluation model is expressed as follows:

[0093]

[0094] Among them, v is the data asset evaluation value, v_usage represents the data usage value, v_content is the data content value, a and b are weight parameters, and the data middle platform system can adjust these weight parameters according to the actual situation of the business system; n represents the number of data.

[0095] In some embodiments, if the data asset evaluation value of the target data meets the second value threshold, move the target data to the data asset area in the data middle platform.

[0096] In some embodiments, after obtaining the data asset evaluation value of the target data, it includes:

[0097] Determine the asset type to which the target data belongs according to the data asset evaluation value of the target data and the asset type threshold.

[0098] Exemplarily, taking the calculated v value in a hundred-point system as an example, for 0 - 60, the data value is relatively low, and it is evaluated as a non-data asset, and this data is usually stored in the data usage area; for 60 - 80, it has a certain data value, and it is evaluated as a low-value data asset, and this data is usually stored in the data buffer area; for 80 - 100, it has a relatively high data value, and it is evaluated as a high-value data asset, and this data is usually stored in the data security area.

[0099] After obtaining the data asset evaluation value of the data, that is, the evaluation result, the evaluation result can be applied to multiple aspects such as data asset management, data governance, and data application. For example, in terms of data asset management, according to the evaluation result, classify, grade, and label the data assets to improve the utilization rate and management efficiency of the data assets. In terms of data governance, according to the evaluation result, optimize the data governance strategy and management process to improve the level and ability of data governance. In terms of data application, according to the evaluation result, explore the application value of the data and promote the application and innovation of the data in business decision-making, product development, marketing, etc.

[0100] By implementing this embodiment, multiple usage parameters of the target data in the data usage area are obtained, and the data usage value of the target data is calculated based on the multiple usage parameters of the target data; the data that meets the requirements in terms of data usage value is moved to the data buffer of the data middle platform, and multiple content evaluation parameters are obtained by performing data governance on the target data; the data content value of the target data is calculated based on the multiple content evaluation parameters of the target data; and then the data asset evaluation value of the target data is calculated according to the data usage value and the data content value of the target data; automatic identification of data and data asset value evaluation are realized, and a comprehensive and accurate evaluation of the data asset value of the data is achieved; moreover, data with different values are stored in different partitions to improve the security of valuable data; this method has the advantages of being scientific, reasonable, and easy to operate, and can provide an enterprise with a comprehensive and accurate evaluation system to help the enterprise better manage and utilize data assets.

[0101] To implement the above embodiment, the present application also proposes a data asset value evaluation device based on a data middle platform. Figure 2 It is a block diagram of a data asset value evaluation device based on a data middle platform provided by an embodiment of the present application. As Figure 2 shown, the data asset value evaluation device based on the data middle platform may include: an initial data acquisition module 201, a usage value calculation module 202, a data governance module 203, a content value calculation module 204, and a data asset evaluation module 205.

[0102] Among them, the initial data acquisition module 201 is used to acquire multiple usage parameters of the target data stored in the data usage area of the data middle platform;

[0103] The usage value calculation module 202 is used to calculate the data usage value of the target data through a usage value calculation model according to the multiple usage parameters of the target data;

[0104] The data governance module 203 is used to move the target data to the data buffer of the data middle platform and perform data governance on the target data to obtain multiple content evaluation parameters if the data usage value of the target data meets the first value threshold;

[0105] The content value calculation module 204 is used to calculate the data content value of the target data through a content value calculation model based on multiple content evaluation parameters of the target data;

[0106] The data asset evaluation module 205 is used to calculate the data asset evaluation value of the target data through a value evaluation model according to the data usage value and the data content value of the target data.

[0107] Furthermore, in a possible implementation manner of the embodiment of the present application, the data asset evaluation module 205 is further used for:

[0108] If the data asset evaluation value of the target data meets the second value threshold, move the target data to the data asset area of the data middle platform.

[0109] Furthermore, in a possible implementation manner of the embodiment of the present application, the multiple usage parameters include data usage volume, data modification volume, and data download volume, and the usage value calculation model is expressed as follows:

[0110]

[0111] Among them, v_usage represents the data usage value, data_type represents the data type, data_usage represents the data usage volume, which is used to characterize the number of times the data is called or browsed by other systems and modules; data_modify represents the data modification volume, which is used to characterize the number of times the data is modified; data_download represents the data download volume, which is used to characterize the number of times the data is downloaded.

[0112] Furthermore, in a possible implementation manner of the embodiment of the present application, the multiple content evaluation parameters include accuracy, integrity, consistency, reliability, data type, data business domain index, security, standardization, effectiveness, sustainability, and user score, and the content value calculation model is expressed as follows:

[0113]

[0114] Among them,

[0115] Among them, v_content is the value of data content, A is the determinant, data_accuracy is the accuracy, which is used to measure whether the data accurately reflects the actual business situation; data_integrity is the integrity, which is used to evaluate whether the data contains all necessary fields and information; data_consistency is the consistency, which is used to evaluate the information consistency of the data at different sources and different time points; data_reliability is the reliability, which is used to reflect the stability and credibility of the data; data_type is the data type, which is used to evaluate the diversity of the data; data_area is the data business area index, which is used to evaluate the importance of the business area to which the data belongs; data_security is the security, which is used to ensure that the data is not accessed by unauthorized personnel, and this value is calculated by the security module of the data middle platform; data_standard is the standardization, which is used to evaluate whether the data management follows industry standards and best practices; data_valid is the effectiveness, which is used to evaluate whether the data governance strategy is effectively implemented and achieves the expected effect; data_Sustainability is the sustainability, which is used to evaluate whether the data governance strategy can be maintained and improved in the long term; data_rating is the user rating, which is obtained by the system's statistics of the positive and negative feedback of users on this data, and p1, p2 are parameters for adjusting the weights.

[0116] Further, in a possible implementation manner of the embodiment of the present application, the value evaluation model is expressed as follows:

[0117]

[0118] Among them, v is the asset evaluation value of the data asset, v_usage represents the data usage value, v_content is the data content value, and a, b are weight parameters.

[0119] Further, in a possible implementation manner of the embodiment of the present application, multiple usage parameters, multiple content evaluation parameters, data usage value, and data content value of the target data are all stored in the data information library table of the data middle platform, and the data information library table also includes the data name and data address.

[0120] Further, in a possible implementation manner of the embodiment of the present application, the data asset evaluation module 205 is further used for:

[0121] Determine the asset type to which the target data belongs according to the asset evaluation value of the target data and the asset type threshold.

[0122] It should be noted that the foregoing explanation of the embodiments of the data asset value evaluation method based on the data middle platform is also applicable to the data asset value evaluation device based on the data middle platform in this embodiment, and will not be elaborated here.

[0123] To implement the above embodiments, the present application also proposes an electronic device. Please refer to Figure 3 , Figure 3 which is a block diagram of the electronic device provided by the embodiments of the present application. As Figure 3 shown, the electronic device 300 includes: a processor 301, and a memory 302 communicatively connected to the processor 301; the memory 302 stores computer-executable instructions; the processor 301 executes the computer-executable instructions stored in the memory to implement the method provided by the foregoing embodiments.

[0124] To implement the above embodiments, the present application also proposes a computer-readable storage medium storing computer-executable instructions, and the computer-executable instructions are used to implement the method provided by the foregoing embodiments when executed by a processor.

[0125] To implement the above embodiments, the present application also proposes a computer program product including a computer program, and the computer program implements the method provided by the foregoing embodiments when executed by a processor.

[0126] In the description of the foregoing embodiments, the descriptions with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, without conflict, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0127] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, "a plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0128] Any process or method description represented in a flowchart or otherwise described herein can be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a customized logical function or process. The scope of the preferred embodiments of the present application includes additional implementations where functions may be executed not in the order shown or discussed, including in a substantially simultaneous manner or in a reverse order according to the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0129] The logic and / or steps represented in a flowchart or otherwise described herein, for example, can be considered a sequenced list of executable instructions for implementing a logical function and can be embodied specifically in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device.

[0130] It should be understood that various parts of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system.

[0131] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the method of implementing the above embodiments can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium, and when executed, includes one or a combination of the steps of the method embodiments.

[0132] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A data asset value evaluation method based on a data middle platform, characterized in that Including the following steps: Obtain multiple usage parameters of the target data stored in the data usage area of the data middle platform; According to the multiple usage parameters of the target data, calculate the data usage value of the target data through a usage value calculation model; If the data usage value of the target data meets the first value threshold, move the target data to the data buffer area of the data middle platform and perform data governance on the target data to obtain multiple content evaluation parameters of the target data; Based on the multiple content evaluation parameters of the target data, calculate the data content value of the target data through a content value calculation model; According to the data usage value and data content value of the target data, calculate the data asset evaluation value of the target data through a value evaluation model.

2. The method according to claim 1, wherein After obtaining the data asset evaluation value of the target data, it includes: If the data asset evaluation value of the target data meets the second value threshold, move the target data to the data asset area of the data middle platform.

3. The method according to claim 1, wherein The multiple usage parameters include data usage volume, data modification volume, and data download volume, and the usage value calculation model is expressed as follows: Among them, v_usage represents the data usage value, data_type represents the data type, data_usage represents the data usage volume, which is used to characterize the number of times the data is called or browsed by other systems and modules; data_modify represents the data modification volume, which is used to characterize the number of times the data is modified; data_download represents the data download volume, which is used to characterize the number of times the data is downloaded.

4. The method according to claim 1, wherein The multiple content evaluation parameters include accuracy, integrity, consistency, reliability, data type, data business domain index, security, standardization, effectiveness, sustainability, and user score, and the content value calculation model is expressed as follows: Among them, Among them, v_content is the value of data content, A is the determinant, data_accuracy is the accuracy, which is used to measure whether the data accurately reflects the actual business situation; data_integrity is the integrity, which is used to evaluate whether the data contains all necessary fields and information; data_consistency is the consistency, which is used to evaluate the information consistency of the data from different sources and at different time points; data_reliability is the reliability, which is used to reflect the stability and credibility of the data; data_type is the data type, which is used to evaluate the diversity of the data; data_area is the data business area index, which is used to evaluate the importance of the business area to which the data belongs; data_security is the security, which is used to ensure that the data is not accessed by unauthorized personnel, and this value is calculated by the security module of the data middle platform; data_standard is the standardization, which is used to evaluate whether data management follows industry standards and best practices; data_valid is the effectiveness, which is used to evaluate whether the data governance strategy is effectively implemented and achieves the expected effect; data_Sustainability is the sustainability, which is used to evaluate whether the data governance strategy can be maintained and improved in the long term; data_rating is the user rating, which is obtained by the system's statistics of the positive and negative feedback of users on this data, and p1, p2 are parameters for adjusting the weights.

5. The method according to claim 1, wherein The value evaluation model is expressed as follows: Among them, v is the asset evaluation value of the data asset, v_usage represents the data usage value, v_content is the data content value, and a, b are weight parameters.

6. The method according to claim 1, wherein Multiple usage parameters, multiple content evaluation parameters, data usage value, and data content value of the target data are all stored in the data information database table of the data middle platform, and the data information database table also includes the data name and data address.

7. The method according to claim 1, characterized in that, After obtaining the asset evaluation value of the target data, it includes: Determine the asset type to which the target data belongs according to the asset evaluation value of the target data and the asset type threshold.

8. A data asset value evaluation device based on a data middle platform, characterized in that, It includes: An initial data acquisition module, which is used to acquire multiple usage parameters of the target data stored in the data usage area of the data middle platform; A usage value calculation module, which is used to calculate the data usage value of the target data through a usage value calculation model according to the multiple usage parameters of the target data; A data governance module, which is used to move the target data to the data buffer area of the data middle platform and perform data governance on the target data to obtain multiple content evaluation parameters of the target data if the data usage value of the target data meets the first value threshold; A content value calculation module, which is used to calculate the data content value of the target data through a content value calculation model based on the multiple content evaluation parameters of the target data; A data asset evaluation module, which is used to calculate the asset evaluation value of the target data through a value evaluation model according to the data usage value and data content value of the target data.

9. An electronic device, characterized in that, It includes: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1-7.

10. A computer program product, characterized in that, It includes a computer program which, when executed by a processor, implements the method according to any one of claims 1-7.

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