Data asset value evaluation method and device, equipment, storage medium and program product

Abstract

The invention provides a data asset value evaluation method and device, equipment, a storage medium and a program product, and can be applied to the technical field of big data and data asset value evaluation. The method comprises the steps that evaluation model information corresponding to data assets is acquired based on a processing flow corresponding to the data assets, and the evaluation model information comprises technology development index information, financial prediction index information and application scene index information; constructing a data asset value evaluation reference model based on the technical development index information, the financial prediction index information and the application scene index information; and configuring the data asset value evaluation reference model by using the model parameter setting, and generating a data asset value evaluation application model. Wherein the model parameter setting is associated with the cost information and the income information of the data assets; and evaluating the value evaluation object by using the data asset value evaluation application model, and generating an evaluation result corresponding to the value evaluation object.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to a data asset value assessment method, device, equipment, storage medium and program product. Background Art

[0002] With the rapid development of technologies such as the Internet of Things, cloud computing, and artificial intelligence, the amount of data is showing an explosive growth trend. Various sensors, smart devices, social media, etc. are constantly generating large amounts of data, providing rich resources for the development of data assets.

[0003] The purpose of data asset valuation is to quantify the economic value of data assets and provide value support for data transactions, investment decisions, mergers and acquisitions, etc. Through value assessment, enterprises can more wisely plan the direction of resource investment, optimize investment decisions, and ensure that the investment can produce the greatest economic benefits. At the same time, the evaluation results can also reveal important information such as data quality, relevance and availability to enterprises, thereby supporting more efficient data management activities. However, data asset valuation also faces many challenges. The lack of effective data asset valuation models or technical reference models has resulted in inconsistent technical standards, large fluctuations in valuation values, long valuation times, and poor applicability of valuation results. Summary of the invention

[0004] In view of the above-mentioned problems of the prior art, the present invention provides a data asset value assessment method, device, equipment, storage medium and program product.

[0005] According to a first aspect of the present invention, there is provided a data asset value assessment method, comprising: based on a processing flow corresponding to the data asset, obtaining assessment model information corresponding to the data asset, wherein the assessment model information includes technology development indicator information, financial forecast indicator information, and application scenario indicator information;

[0006] Constructing a data asset value assessment benchmark model based on the technology development indicator information, the financial forecast indicator information, and the application scenario indicator information;

[0007] The data asset value assessment benchmark model is configured using model parameter settings to generate a data asset value assessment application model, wherein the model parameter settings are associated with the cost information and revenue information of the data asset;

[0008] And use the data asset value assessment application model to assess the value assessment object and generate an assessment result corresponding to the value assessment object.

[0009] According to an embodiment of the present invention, the data asset value assessment benchmark model is configured using model parameter settings to generate a data asset value assessment application model, including: obtaining the cost information and the revenue information corresponding to the data assets within a target time range; and configuring the data asset value assessment benchmark model based on the cost information, the revenue information and the model parameter settings to obtain the data asset value assessment application model.

[0010] According to an embodiment of the present invention, the cost information includes data infrastructure cost information and human resource cost information, and the benefit information includes data product design information and data product value information; wherein, the data asset value assessment benchmark model is configured based on the cost information, the benefit information and the model parameter settings to obtain the data asset value assessment application model, including: determining the benefit configuration parameters corresponding to the data assets based on the data product design information corresponding to the data assets and the data product value information; determining the cost configuration parameters based on the data infrastructure cost information and the human resource cost information; and configuring the data asset value assessment benchmark model using the benefit configuration parameters, the cost configuration parameters and the model parameter settings to generate the data asset value assessment application model.

[0011] According to an embodiment of the present invention, the processing flow information includes data asset acquisition flow information and data asset application flow information, and the technical development indicator information includes quality level information, application degree information and business support information corresponding to the data assets; wherein, obtaining the evaluation indicator information corresponding to the data assets based on the processing flow information corresponding to the data assets includes: obtaining the data asset acquisition information and the data asset application information in the processing flow information; and generating the quality level information, the application degree information and the business support information corresponding to the data assets based on the data asset acquisition information, the data asset application information and the technical development indicator information.

[0012] According to an embodiment of the present invention, the processing flow information also includes data asset sharing process information, and the financial forecasting indicator information includes development and operation cost information, transaction circulation value information and marketing value information corresponding to the data assets; wherein, obtaining the evaluation indicator information corresponding to the data assets based on the processing flow information corresponding to the data assets also includes: obtaining the data asset sharing process information and the data asset application process information in the processing flow information; and generating the development and operation cost information, the transaction circulation value information and the marketing value information corresponding to the data assets based on the data asset sharing process information, the data asset application process information and the financial forecasting indicator information.

[0013] According to an embodiment of the present invention, the application scenario indicator information includes applicability information, validity information and security information corresponding to the data asset; wherein, obtaining the evaluation indicator information corresponding to the data asset based on the processing flow information corresponding to the data asset also includes: obtaining the data asset application flow information in the processing flow information; and generating the applicability information, the validity information and the security information corresponding to the data asset based on the data asset application flow information and the application scenario indicator information.

[0014] According to an embodiment of the present invention, determining the revenue configuration parameters corresponding to the data assets based on the data product design information and the data product value information corresponding to the data assets includes: determining the weight information corresponding to the data product design information based on the data product value information and preset assignment rules; comparing the weight information with a preset weight threshold to obtain a comparison result; and determining the revenue configuration parameters corresponding to the data product design information when the comparison result meets preset conditions.

[0015] A second aspect of the present invention provides a data asset value assessment device, characterized in that the device comprises:

[0016] A data asset value assessment indicator information acquisition module, used to acquire evaluation indicator information corresponding to the data asset based on the processing flow information corresponding to the data asset, wherein the evaluation indicator information includes technology development indicator information, financial forecast indicator information and application scenario indicator information;

[0017] A data asset value assessment benchmark model construction module, used to construct a data asset value assessment benchmark model based on the technology development indicator information, the financial forecast indicator information and the application scenario indicator information;

[0018] A data asset value assessment application model generation module, used to configure the data asset value assessment benchmark model using model parameter settings to generate a data asset value assessment application model, wherein the model parameter settings are associated with the cost information and revenue information of the data assets;

[0019] And a data asset value assessment result generation module is used to evaluate the value assessment object using the data asset value assessment application model and generate an assessment result corresponding to the value assessment object.

[0020] A third aspect of the present invention provides an electronic device, comprising: one or more processors; a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the method.

[0021] The fourth aspect of the present invention further provides a computer-readable storage medium having a computer program or instructions stored thereon, wherein the computer program or instructions implement the steps of the method when executed by a processor.

[0022] The fifth aspect of the present invention also provides a computer program product, comprising a computer program or instructions, which implement the steps of the method when executed by a processor.

[0023] According to a data asset value assessment method, device, equipment, storage medium and program product provided by the present invention, by obtaining evaluation index information corresponding to the data asset including technical development index information, financial forecast index information and application scenario index information based on the processing flow information corresponding to the data asset, a data asset value assessment benchmark model can be constructed based on the multi-dimensional evaluation index information, thereby improving the accuracy of the model assessment, and then the data asset value assessment benchmark model can be configured using the model parameter setting, the cost information and the income information of the data asset, so as to obtain the data asset value assessment application model and evaluate the value assessment object. Since the data asset value assessment application model is updated and optimized based on the model parameter setting, the quantified cost information and the income information, the accuracy of the data asset value assessment application model and the evaluation result is further improved, and the evaluation result output by the optimized data asset value assessment application model can more accurately characterize the degree of adaptation of the value assessment object to the user's needs, reduce the operation links of the user using different types of evaluation methods to verify the evaluation results, reduce the user's interactive operation costs, and improve the efficiency of computer equipment in automatically executing data asset value assessment, while avoiding the idle waste of purchased data assets, improving the utilization rate and economy of data assets, and improving the user's experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The contents and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0025] Figure 1 A diagram schematically shows an application scenario of data asset value assessment according to an embodiment of the present invention;

[0026] Figure 2 A flowchart of a data asset value assessment method according to an embodiment of the present invention is schematically shown;

[0027] Figure 3 A schematic diagram of data asset processing flow information according to an embodiment of the present invention is shown schematically;

[0028] Figure 4 A system architecture diagram of a data asset value assessment method according to an embodiment of the present invention is schematically shown;

[0029] Figure 5 A schematic diagram of a data asset value assessment device according to an embodiment of the present invention is shown;

[0030] Figure 6 A block diagram of an electronic device suitable for implementing a data asset value assessment method according to an embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0031] Below, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of embodiments of the present invention. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of concepts of the present invention.

[0032] The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0033] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0034] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0035] In the technical solution of the present invention, the user information (including but not limited to user personal information, user image information, user device information, such as location information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0036] In the scenario of using personal information for automated decision-making, the methods, devices, and systems provided by the embodiments of the present invention provide users with corresponding operation portals for users to choose to agree or reject the automated decision-making results; if the user chooses to reject, the expert decision-making process will be entered. The expression "automated decision-making" here refers to the activity of automatically analyzing and evaluating an individual's behavioral habits, interests and hobbies, or economic, health, credit status, etc. through computer programs, and making decisions. The expression "expert decision-making" here refers to the activity of making decisions by people who specialize in a certain field, have specialized experience, knowledge and skills, and have reached a certain level of professionalism.

[0037] The inventors have found that the determination of data asset value in the related art, due to the lack of an effective data asset value assessment model or technical reference model, has resulted in inconsistent technical standards, large fluctuations in assessment value, long assessment time, and poor applicability of assessment results. In view of this, the present invention obtains evaluation index information corresponding to the data asset based on the processing flow information corresponding to the data asset, including technical development index information, financial forecast index information, and application scenario index information, so that a data asset value assessment benchmark model can be constructed based on multi-dimensional evaluation index information, thereby improving the accuracy of model assessment, and then the data asset value assessment benchmark model can be configured using model parameter settings, data asset cost information, and revenue information, to obtain a data asset value assessment application model and assess the value assessment object. Since the data asset value assessment application model is updated and optimized based on the model parameter settings, quantified cost information and benefit information, the accuracy of the data asset value assessment application model and the evaluation results is further improved. The evaluation results output by the optimized data asset value assessment application model can more accurately characterize the degree of adaptation between the value assessment object and user needs, reduce the user's use of different types of evaluation methods to verify the evaluation results, reduce the user's interactive operation costs, and improve the efficiency of computer equipment in automatically executing data asset value assessments. At the same time, it can avoid the idle waste of purchased data assets and improve the utilization and economy of data assets.

[0038] Embodiments of the present invention provide a data asset value assessment method, apparatus, device, storage medium and program product, the method comprising: obtaining evaluation index information corresponding to the data asset based on processing flow information corresponding to the data asset, wherein the evaluation index information comprises technical development index information, financial forecast index information and application scenario index information; constructing a data asset value assessment benchmark model based on the technical development index information, financial forecast index information and application scenario index information; configuring the data asset value assessment benchmark model using model parameter settings to generate a data asset value assessment application model, wherein the model parameter settings are associated with the cost information and benefit information of the data asset; and evaluating the value assessment object using the data asset value assessment application model to generate an assessment result corresponding to the value assessment object.

[0039] Figure 1 The following schematically shows an application scenario diagram of data asset value assessment according to an embodiment of the present invention.

[0040] like Figure 1As shown, the application scenario according to this embodiment may include a first access device 101, a second access device 102, a third access device 103, an Internet device 104, and a data asset operation device 105. The Internet device 104 is used to provide a medium for a communication link between the first access device 101, the second access device 102, the third access device 103, and the data asset operation device 105. The Internet device 104 may include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0041] The user can use at least one of the first access device 101, the second access device 102, and the third access device 103 to interact with the data asset operation device 105 through the Internet device 104 to receive or send messages, etc. Various communication client applications can be installed on the first access device 101, the second access device 102, and the third access device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only for example).

[0042] The first access device 101, the second access device 102, and the third access device 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0043] The data asset operation device 105 may be a server that provides various data asset operation services, such as a background management server (only as an example) that provides support for websites browsed by users using the first access device 101, the second access device 102, and the third access device 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the access device.

[0044] It should be noted that the data asset value assessment method provided in the embodiment of the present invention can generally be executed by the data asset operation device 105. Accordingly, the data asset value assessment device provided in the embodiment of the present invention can generally be set in the data asset operation device 105. The data asset value assessment method provided in the embodiment of the present invention can also be executed by a server or server cluster that is different from the data asset operation device 105 and can communicate with the first access device 101, the second access device 102, the third access device 103 and / or the data asset operation device 105. Accordingly, the data asset value assessment device provided in the embodiment of the present invention can also be set in a server or server cluster that is different from the data asset operation device 105 and can communicate with the first access device 101, the second access device 102, the third access device 103 and / or the data asset operation device 105.

[0045] It should be understood that Figure 1 The number of access devices, Internet devices, and data asset operation devices in the embodiment is only for illustration. Any number of access devices, Internet devices, and data asset operation devices may be provided according to implementation requirements.

[0046] Figure 2 A flow chart of a data asset value assessment method according to an embodiment of the present invention is schematically shown.

[0047] like Figure 2 As shown, the data asset value assessment of this embodiment includes operations S210 to S240.

[0048] In operation S210, based on the processing flow information corresponding to the data asset, evaluation index information corresponding to the data asset is obtained, wherein the evaluation index information includes technology development index information, financial forecast index information, and application scenario index information.

[0049] According to an embodiment of the present invention, processing flow information may include data asset acquisition flow information, data asset inventory and registration flow information, data asset processing flow information, data asset sharing flow information, data asset application flow information, data asset security flow information, and data asset disposal and scrapping flow information. Technical development indicator information includes quality level information, application degree information, and business support information corresponding to data assets; financial forecasting indicator information may include development and operation cost information, transaction circulation value information, and marketing value information corresponding to data assets; application scenario indicator information may include applicability information, effectiveness information, and security information corresponding to the data assets. Evaluation indicator information can be used to construct a benchmark model for data asset value assessment.

[0050] In operation S220, a data asset value assessment benchmark model is constructed based on the technology development index information, the financial forecast index information, and the application scenario index information.

[0051] According to an embodiment of the present invention, a data asset value assessment benchmark model can be constructed based on technology development indicator information, financial forecast indicator information and application scenario indicator information.

[0052] In operation S230, the data asset value assessment benchmark model is configured using model parameter settings to generate a data asset value assessment application model, wherein the model parameter settings are associated with the cost information and the revenue information of the data asset.

[0053] According to an embodiment of the present invention, the cost information of data assets can represent the cost of data assets in the entire life cycle within the target time period, and can be calculated based on the financial forecasting indicator model. The income information of data assets can represent the discounted income information and business value of data assets within the target time period. Then, the data asset value assessment benchmark model is optimized and updated based on the cost configuration parameters, discount coefficients and income configuration parameters to obtain a data asset value assessment application model.

[0054] In operation S240, the value assessment object is assessed using the data asset value assessment application model to generate an assessment result corresponding to the value assessment object.

[0055] According to an embodiment of the present invention, the value assessment object may be a data asset pre-acquired in a future time period. The assessment result may be represented by a corresponding assessment index value, and different levels of assessment results may be determined according to different value ranges.

[0056] According to an embodiment of the present invention, by obtaining evaluation index information corresponding to the data asset based on the processing flow information corresponding to the data asset, including technical development index information, financial forecast index information and application scenario index information, a data asset value assessment benchmark model can be constructed based on the multi-dimensional evaluation index information, thereby improving the accuracy of the model assessment, and then the data asset value assessment benchmark model can be configured using the model parameter settings, the cost information and the income information of the data asset, to obtain the data asset value assessment application model and evaluate the value assessment object. Since the data asset value assessment application model is updated and optimized based on the model parameter settings, quantified cost information and income information, the accuracy of the data asset value assessment application model and the evaluation results is further improved, so that the evaluation results output by the optimized data asset value assessment application model can more accurately represent the degree of adaptation of the value assessment object to user needs.

[0057] According to an embodiment of the present invention, a data asset value assessment benchmark model is configured using model parameter settings to generate a data asset value assessment application model, including: obtaining cost information and revenue information corresponding to data assets within a target time range; and configuring the data asset value assessment benchmark model based on the cost information, revenue information and model parameter settings to obtain a data asset value assessment application model.

[0058] According to an embodiment of the present invention, cost information may include data infrastructure cost information and human resource cost information corresponding to data assets, so that cost configuration parameters can be determined based on the data infrastructure cost information and human resource cost information. Revenue information may include discounted revenue information and data product value information, so that the discount factor can be determined based on the discounted revenue information within the target time period, and the revenue configuration parameters can be determined based on the data product value information of the data assets within the historical time period. The quality level parameter can be used to quantify the data quality level, which can be the degree of improvement of the quality of the data after processing, cleaning or other quality improvement steps relative to the original data resource. In practical applications, calculations can be performed based on specific quality indicators, which can include using the Delphi method to evaluate from four dimensions of completeness, effectiveness, consistency and uniqueness to obtain quality level parameters (e.g., 0.5 to 1.0).

[0059] The cost configuration parameters and quality level parameters can be used to further determine the benchmark configuration parameters, so as to optimize and update the data asset value assessment benchmark model based on the benchmark configuration parameters, discount coefficient and income configuration parameters, and then obtain the data asset value assessment application model. The data asset value assessment application model is further used to assess the value assessment object to obtain the assessment result V. The calculation method of the assessment result V is shown in the following formula (1):

[0060]

[0061] Among them, V is the assessed value of the data asset, m is the mth income period in the future time period, n is the life cycle of the data asset to generate income, Fm is the income and loss brought by the data asset in the next m years, f(Q, C) is the benchmark configuration parameter, Q is the quality level parameter, C is the cost configuration parameter, k is the discount factor, and A is the income configuration parameter.

[0062] According to an embodiment of the present invention, by configuring and optimizing the data asset value assessment benchmark model, more assessment index parameters can be introduced, thereby improving the accuracy and reliability of the assessment results. At the same time, the updated and optimized data asset value assessment application model is more adaptable to user needs and can better adapt to data assets in various application scenarios.

[0063] According to an embodiment of the present invention, cost information includes data infrastructure cost information and human resource cost information, and revenue information includes data product design information and data product value information; wherein, the data asset value assessment benchmark model is configured based on the cost information, revenue information and model parameter settings to obtain a data asset value assessment application model, including: determining the revenue configuration parameters corresponding to the data assets according to the data product design information and data product value information corresponding to the data assets; determining the cost configuration parameters according to the data infrastructure cost information and human resource cost information; and configuring the data asset value assessment benchmark model using the revenue configuration parameters, cost configuration parameters and model parameter settings to generate a data asset value assessment application model.

[0064] According to an embodiment of the present invention, different data assets have corresponding data product design information and data product value information. Based on the different data product design information and data product value information, it can be determined whether the data assets need to use revenue configuration parameters, and on this basis, the revenue configuration parameters corresponding to different data assets can be further determined.

[0065] In a feasible embodiment, for data assets that require the use of revenue configuration parameters, the calculation indicators of the revenue configuration parameters can be further determined based on the scarcity, accuracy and timeliness of the data resources. The calculation indicators may include dimension weights, dimensions, weights and indicator values, and then based on the calculation indicators, the revenue configuration parameters corresponding to the data assets can be further determined.

[0066] In a feasible embodiment, the revenue configuration parameter also includes a discount factor, and the discount factor can be determined according to discounted revenue information within the target time period.

[0067] According to an embodiment of the present invention, the cost configuration parameter may be determined based on the cost of the data asset in the entire life cycle within the target time period.

[0068] After determining the cost configuration parameters and quality level parameters, the benchmark configuration parameters can be further determined, and then the data asset value assessment benchmark model can be optimized and updated according to the benchmark configuration parameters, discount factors and revenue configuration parameters to obtain the data asset value assessment application model.

[0069] According to an embodiment of the present invention, processing flow information includes acquisition flow information and application flow information, and technical development indicator information includes quality level information, application degree information and business support information corresponding to data assets; wherein, based on the processing flow information corresponding to the data assets, obtaining evaluation indicator information corresponding to the data assets includes: obtaining data asset application information and data asset acquisition information in the processing flow information; and generating quality level information, application degree information and business support information corresponding to the data assets based on the data asset application information, data asset acquisition information and technical development indicators.

[0070] According to an embodiment of the present invention, data asset application information can characterize the corresponding data quality level information during the actual business application process of data in a historical time period; data asset acquisition information can characterize the purpose of data and the acquisition cost information during the acquisition process of data in a historical time period. Quality level information, application degree information and business support information can be obtained by weighting and summing the data asset application information and data asset acquisition information of data quality in a historical time period through technical development indicators, and the specific weight indicators can be determined according to actual conditions. Quality level information may include accuracy information, quality information and timeliness information of data assets; application degree information may include quality scores, service quality scores and usage frequency scores of data assets; business support information may include information on production and operation support, cost reduction, product quality improvement, business decision-making and safe production of data assets.

[0071] According to an embodiment of the present invention, the processing flow information also includes shared process information, and the financial forecast indicator information includes development and operation cost information, transaction circulation value information and marketing value information corresponding to the data assets; wherein, based on the processing flow information corresponding to the data assets, obtaining the evaluation indicator information corresponding to the data assets also includes: obtaining the shared process information and data asset application information in the processing flow information; and generating the development and operation cost information, transaction circulation value information and marketing value information corresponding to the data assets based on the shared process information, the data asset application information and the financial forecast indicator model.

[0072] According to an embodiment of the present invention, shared process information can characterize relevant information such as data management and operation and maintenance costs when data assets are shared among various departments and branches of an organization during a historical time period. Development and operation cost information may include evaluation information on data asset acquisition costs, processing costs, operation and maintenance costs, management costs, and risk costs; transaction circulation value information may include circulation value evaluation information of data assets; and marketing value information may include economic benefit value evaluation information of data assets. Data asset application information may also include the applicability of data assets, data circulation, and the income generated by data. Development and operation cost information, transaction circulation value information, and marketing value information may characterize financial forecast indicator information of data assets in future time periods, which can be obtained by weighting and summing the shared process information and data asset application information in historical time periods through financial forecast indicators, and the specific weight indicators may be determined according to actual conditions.

[0073] Figure 3 A schematic diagram of a data asset processing flow according to an embodiment of the present invention is shown schematically.

[0074] like Figure 3 As shown, the data asset processing flow may include operations S310 to S370, which are specifically as follows.

[0075] In operation S310, data resources are acquired from other external organizations, and the purpose of the data resources is clarified to evaluate the business value and acquisition cost of the data resources.

[0076] In operation S320, data assets are counted and registered for the acquired data resources, and the acquisition cost of the data resources can be estimated.

[0077] In operation S330, by performing data asset processing on the registration data, the processing cost of the data resources can be estimated and data quality management can be performed to improve the accuracy and usability of the data.

[0078] In operation S340, a data lake is constructed using the processed data resources, and the data is processed accordingly, such as data processing, data processing, and data aggregation, to achieve data asset sharing in the data lake.

[0079] In operation S350, each branch within the organization can use the data resources in the data lake to apply the data, and at the same time, the accuracy, data quality and data timeliness of the data resources can be evaluated according to the actual application scenario; further, the applicability of the data, the data circulation and the benefits generated by the data can be evaluated.

[0080] In operation S360, data asset security management and control is performed based on relevant issues of data resources in actual application scenarios.

[0081] In operation S370, a determination is made on the disposal and scrapping of data assets based on the timeliness, quality, and applicability of the data.

[0082] Through the relevant information of each stage of the data asset processing process, the changes in data resources can be monitored in real time or regularly, and corresponding evaluation indicators can be provided to help users understand the dynamic changes in data. At the same time, the evaluation indicators provided by the data processing process can provide important references for decision-making, helping decision makers understand the availability, applicability and value of data, so as to better formulate decisions and strategies and improve product and service quality.

[0083] According to an embodiment of the present invention, application scenario indicator information includes applicability information, validity information and security information corresponding to the data assets; wherein, based on the processing flow information corresponding to the data assets, obtaining the evaluation indicator information corresponding to the data assets also includes: obtaining the data asset application information in the processing flow information; and based on the data asset application information and the application evaluation indicators, generating the applicability information, validity information and security information corresponding to the data assets.

[0084] According to an embodiment of the present invention, the applicability information can characterize the applicability analysis results of data assets in the future time period; the validity information can characterize the data accuracy, timeliness and data asset application evaluation results of data assets in the future time period; the security information can characterize the security benefit value of data assets in the future time period. The applicability information, validity information and security information can be obtained by weighting and weighting the data asset application information in the historical time period by applying evaluation indicators, and the specific weight indicators can be determined according to actual conditions.

[0085] Figure 4 A system architecture diagram of a data asset value assessment method according to an embodiment of the present invention is schematically shown.

[0086] like Figure 4 As shown, the data asset value assessment benchmark model 400 may include technology development indicators 410, financial forecast indicators 420, and application scenario indicators 430. By acquiring the technology development information and technology development indicators 410 of data assets in the historical time period, the quality level information 411, application level information 412, and business support information 413 of data assets in the future time period can be evaluated, wherein the quality level information 411 may include the accuracy information, quality information, and timeliness information of the data assets; the application level information 412 may include the quality score, service quality score, and usage frequency score of the data assets; the business support information 413 may include information on production and operation support, cost reduction, product quality improvement, business decision-making, and safe production of data assets.

[0087] According to an embodiment of the present invention, by acquiring the financial information and financial forecast indicators 420 of data assets in a historical time period, the development and operation cost information 421, transaction circulation value information 422 and marketing value information 423 of the data assets in a future time period can be evaluated; wherein, the development and operation cost information 421 may include evaluation information on the acquisition cost, processing cost, operation and maintenance cost, management cost and risk cost of the data assets; the transaction circulation value information 422 may include the circulation value evaluation information of the data assets; and the marketing value information 423 may include the economic benefit value evaluation information of the data assets.

[0088] According to an embodiment of the present invention, by acquiring usage information and application scenario indicators 430 of data assets in a historical time period, the applicability information 431, validity information 432 and security information 433 of data assets in a future time period can be evaluated, wherein the applicability information 431 can characterize the applicability analysis results of data assets in the future time period; the validity information 432 can characterize the data accuracy, timeliness and data asset application evaluation results of data assets in the future time period; and the security information 433 can characterize the security benefit value of data assets in the future time period.

[0089] According to an embodiment of the present invention, based on the data product design information and data product value information corresponding to the data assets, the revenue configuration parameters corresponding to the data assets are determined, including: determining the weight information corresponding to the data product design information based on the data product value information and preset assignment rules; comparing the weight information with the preset weight threshold to obtain a comparison result; and determining the revenue configuration parameters corresponding to the data product design information when the comparison result meets the preset conditions.

[0090] According to an embodiment of the present invention, the preset value assignment rule may be a rule for assigning corresponding values ​​to data assets based on the dimensional weights of different types of data assets within a historical time period.

[0091] Based on the data asset value assessment method, the present invention also provides a data asset value assessment device. Figure 5 The device is described in detail.

[0092] Figure 5 The structure block diagram of the data asset value assessment device according to an embodiment of the present invention is schematically shown.

[0093] like Figure 5 As shown, the data asset value assessment device of this embodiment includes a data asset value assessment indicator information acquisition module 510, a data asset value assessment benchmark model construction module 520, a data asset value assessment application model generation module 530 and a data asset value assessment result generation module 540.

[0094] The data asset value evaluation index information acquisition module 510 is used to acquire the evaluation index information corresponding to the data asset based on the processing flow information corresponding to the data asset, wherein the evaluation index information includes technology development index information, financial forecast index information, and application scenario index information. In an embodiment, the data asset value evaluation index information acquisition module 510 can be used to perform the operation S210 described above, which will not be repeated here.

[0095] The data asset value assessment benchmark model construction module 520 is used to construct a data asset value assessment benchmark model based on the technology development index information, the financial forecast index information and the application scenario index information. In an embodiment, the data asset value assessment benchmark model construction module 520 can be used to perform the operation S220 described above, which will not be repeated here.

[0096] The data asset value assessment application model generation module 530 is used to configure the data asset value assessment benchmark model using the model parameter settings to generate a data asset value assessment application model, wherein the model parameter settings are associated with the cost information and revenue information of the data asset. In an embodiment, the data asset value assessment application model generation module 530 can be used to perform the operation S230 described above, which will not be repeated here.

[0097] The data asset value assessment result generation module 540 is used to evaluate the value assessment object using the data asset value assessment application model and generate an assessment result corresponding to the value assessment object. In an embodiment, the data asset value assessment result generation module 540 can be used to perform the operation S240 described above, which will not be repeated here.

[0098] According to an embodiment of the present invention, through the data asset value assessment indicator information acquisition module 510, the data asset value assessment benchmark model construction module 520, the data asset value assessment application model generation module 530 and the data asset value assessment result generation module 540 in the data asset value assessment device, by obtaining the evaluation indicator information corresponding to the data asset based on the processing flow information corresponding to the data asset, including the technical development indicator information, the financial forecast indicator information and the application scenario indicator information, so that the data asset value assessment benchmark model can be constructed based on the multi-dimensional evaluation indicator information, thereby improving the accuracy of the model evaluation, and then the data asset value assessment benchmark model can be configured by using the model parameter settings, the cost information and the benefit information of the data assets, so as to obtain the data asset value assessment application model and evaluate the value assessment object.

[0099] According to an embodiment of the present invention, processing process information includes obtaining process information and applying process information, and technology development indicator information includes quality level information, application degree information and business support information corresponding to data assets; wherein, the data asset value assessment indicator information acquisition module 510 includes: a first information generation submodule and a second information acquisition submodule.

[0100] The first information generation submodule is used to generate quality level information, application degree information and business support information corresponding to the data assets based on data asset application information, data asset acquisition information and technical development indicators.

[0101] The second information acquisition submodule is used to acquire data asset application information and data asset acquisition information in the processing flow information.

[0102] According to an embodiment of the present invention, the processing process information also includes shared process information, and the financial forecast indicator information includes development and operation cost information, transaction circulation value information and marketing value information corresponding to the data assets; wherein, the data asset value assessment indicator information acquisition module 510 also includes: a second information generation submodule and a third information acquisition submodule.

[0103] The second information generation submodule is used to generate development and operation cost information, transaction circulation value information and marketing value information corresponding to the data assets based on shared process information, data asset application information and financial forecast indicators.

[0104] The third information acquisition submodule is used to obtain the shared process information and data asset application information in the processing process information.

[0105] According to an embodiment of the present invention, application scenario indicator information includes applicability information, validity information and security information corresponding to the data assets; wherein, the data asset value assessment indicator information acquisition module 510 also includes: a data asset application information acquisition submodule and a third information generation submodule.

[0106] The data asset application information acquisition submodule is used to obtain the data asset application information in the processing flow information.

[0107] The third information generation submodule is used to generate applicability information, validity information and security information corresponding to the data assets based on the data asset application information and the usage indicator evaluation model.

[0108] According to an embodiment of the present invention, the data asset value assessment application model generation module 530 includes: a first information acquisition submodule and a data asset value assessment benchmark model update submodule.

[0109] The first information acquisition submodule is used to obtain cost information and revenue information corresponding to the data assets within a target time range.

[0110] The data asset value assessment benchmark model update submodule is used to configure the data asset value assessment benchmark model based on cost information, revenue information and model parameter settings to obtain a data asset value assessment application model.

[0111] According to an embodiment of the present invention, cost information includes data infrastructure cost information and human resource cost information, and revenue information includes data product design information and data product value information; wherein, the data asset value assessment benchmark model update submodule includes: a revenue configuration parameter determination unit, a cost configuration parameter determination unit and a data asset value assessment application model generation unit.

[0112] The revenue configuration parameter determination unit is used to determine the revenue configuration parameters corresponding to the data assets based on the data product design information and data product value information corresponding to the data assets.

[0113] The cost configuration parameter determination unit is used to determine the cost configuration parameters according to the data infrastructure cost information and the human resource cost information.

[0114] The data asset value assessment application model generation unit is used to configure the data asset value assessment benchmark model using the revenue configuration parameters, cost configuration parameters and model parameter settings to generate a data asset value assessment application model.

[0115] According to an embodiment of the present invention, a revenue configuration parameter determination unit includes: a weight information determination subunit, a comparison subunit and a revenue configuration parameter determination subunit.

[0116] The weight information determination subunit is used to determine the weight information corresponding to the data product design information based on the data product value information and preset assignment rules.

[0117] The comparison subunit is used to compare the weight information with a preset weight threshold to obtain a comparison result.

[0118] The revenue configuration parameter determination subunit is used to determine the revenue configuration parameters corresponding to the data product design information when the comparison result meets the preset conditions.

[0119] According to an embodiment of the present invention, any multiple modules among the data asset value assessment indicator information acquisition module 510, the data asset value assessment benchmark model construction module 520, the data asset value assessment application model generation module 530 and the data asset value assessment result generation module 540 can be combined in one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present invention, at least one of the data asset value assessment indicator information acquisition module 510, the data asset value assessment benchmark model construction module 520, the data asset value assessment application model generation module 530 and the data asset value assessment result generation module 540 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in an appropriate combination of any of them. Alternatively, at least one of the data asset value assessment indicator information acquisition module 510, the data asset value assessment benchmark model construction module 520, the data asset value assessment application model generation module 530 and the data asset value assessment result generation module 540 can be at least partially implemented as a computer program module, which can execute the corresponding function when the computer program module is executed.

[0120] Figure 6 A block diagram of an electronic device suitable for implementing a data asset value assessment method according to an embodiment of the present invention is schematically shown.

[0121] like Figure 6 As shown, the electronic device according to an embodiment of the present invention includes an operation processor 608, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 610 or a program loaded from a built-in storage component 611 into a random access memory (RAM) 609. The operation processor 608 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The operation processor 608 may also include an onboard memory for caching purposes. The operation processor 608 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0122] In RAM 609, various programs and data required for the operation of the electronic device are stored. The operation processor 608, ROM 610 and RAM 609 are connected to each other through a communication bus 607. The operation processor 608 performs various operations of the method flow according to the embodiment of the present invention by executing the program in ROM 610 and / or RAM 609. It should be noted that the program can also be stored in one or more memories other than ROM 610 and RAM 609. The operation processor 608 can also perform various operations of the method flow according to the embodiment of the present invention by executing the program stored in the one or more memories.

[0123] According to an embodiment of the present invention, the electronic device may further include an input / output (I / O) interface 606, which is also connected to the communication bus 607. The electronic device may further include one or more of the following components connected to the input / output (I / O) interface 606: an input component 601 including a keyboard, a mouse, etc.; an output component 602 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a built-in storage component 611 including a hard disk, etc.; and a communication component 605 including an Internet device interface card such as a LAN card, a modem, etc. The communication component 605 performs communication processing via an Internet device such as the Internet. The storage drive component 604 is also connected to the input / output (I / O) interface 606 as needed. An extended storage component 603, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the storage drive component 604 as needed, so that the computer program read therefrom is installed into the built-in storage component 611 as needed.

[0124] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the embodiments; or may exist independently without being assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, and when the one or more programs are executed, the method according to the embodiments of the present invention is implemented.

[0125] According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present invention, the computer-readable storage medium may include the ROM 610 and / or RAM 609 described above and / or one or more memories other than ROM 610 and RAM 609.

[0126] The embodiment of the present invention also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement a data asset value assessment method provided by the embodiment of the present invention.

[0127] The functions defined in the system / device of the embodiment of the present invention are performed when the computer program is executed by the operation processor 608. According to the embodiment of the present invention, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0128] In one embodiment, the computer program may be based on a tangible storage medium such as an optical storage device, a magnetic storage device, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of a signal on an Internet device medium, and downloaded and installed through the communication component 605, and / or installed from the extended storage component 603. The program code contained in the computer program may be transmitted using any appropriate Internet device medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0129] In such an embodiment, the computer program can be downloaded and installed from an Internet device through the communication component 605, and / or installed from the extended storage component 603. When the computer program is executed by the operation processor 608, the functions defined in the system of the embodiment of the present invention are performed. According to the embodiment of the present invention, the system, device, apparatus, module, unit, etc. described above can be implemented by a computer program module.

[0130] According to an embodiment of the present invention, the program code for executing the computer program provided by the embodiment of the present invention can be written in any combination of one or more programming languages, specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, such as Java, C++, python, "C" language or similar programming languages. The program code can be executed completely on the user computing device, partially on the user device, partially on the remote computing device, or completely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of Internet device, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0131] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0132] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present invention may be combined and / or combined in various ways, even if such combinations and / or combinations are not explicitly described in the present invention. In particular, the features described in the various embodiments and / or claims of the present invention may be combined and / or combined in various ways without departing from the spirit and teachings of the present invention. All of these combinations and / or combinations fall within the scope of the present invention.

[0133] The embodiments of the present invention are described above. However, these embodiments are only for the purpose of illustration, and are not intended to limit the scope of the present invention. Although each embodiment is described above, it does not mean that the measures in each embodiment cannot be used in combination. The scope of the present invention is defined by the attached claims and their equivalents. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A data asset value assessment method, characterized in that: The method includes: based on the processing flow corresponding to the data asset, obtaining the evaluation model information corresponding to the data asset, wherein the evaluation model information includes technology development index information, financial forecast index information and application scenario index information; constructing a data asset value evaluation benchmark model based on the technology development index information, the financial forecast index information and the application scenario index information; configuring the data asset value evaluation benchmark model using model parameter settings to generate a data asset value evaluation application model. The model parameter settings are associated with the cost information and revenue information of the data asset; and evaluating the value evaluation object using the data asset value evaluation application model to generate an evaluation result corresponding to the value evaluation object.

2. The method according to claim 1, characterized in that The data asset value assessment benchmark model is configured using model parameter settings to generate a data asset value assessment application model, including: obtaining the cost information and the revenue information corresponding to the data assets within a target time range; and configuring the data asset value assessment benchmark model based on the cost information, the revenue information and the model parameter settings to obtain the data asset value assessment application model.

3. The method according to claim 2, characterized in that The cost information includes data infrastructure cost information and human resource cost information, and the benefit information includes data product design information and data product value information; wherein, the data asset value assessment benchmark model is configured based on the cost information, the benefit information and the model parameter settings to obtain the data asset value assessment application model, including: determining the benefit configuration parameters corresponding to the data asset according to the data product design information corresponding to the data asset and the data product value information; determining the cost configuration parameters according to the data infrastructure cost information and the human resource cost information; and configuring the data asset value assessment benchmark model using the benefit configuration parameters, the cost configuration parameters and the model parameter settings to generate the data asset value assessment application model.

4. The method according to claim 1, characterized in that: The processing flow information includes data asset acquisition flow information and data asset application flow information, and the technical development indicator information includes quality level information, application degree information and business support information corresponding to the data assets; wherein, obtaining the evaluation indicator information corresponding to the data assets based on the processing flow information corresponding to the data assets includes: obtaining the data asset acquisition information and the data asset application information in the processing flow information; and generating the quality level information, the application degree information and the business support information corresponding to the data assets based on the data asset acquisition information, the data asset application information and the technical development indicator information. The processing flow information also includes data asset sharing flow information, and the financial forecasting indicator information includes development and operation cost information, transaction circulation value information, and marketing value information corresponding to the data asset; wherein, based on the processing flow information corresponding to the data asset, obtaining the evaluation indicator information corresponding to the data asset also includes: obtaining the data asset sharing flow information and the data asset application flow information in the processing flow information; and generating the development and operation cost information, transaction circulation value information, and marketing value information corresponding to the data asset based on the data asset sharing flow information, the data asset application flow information, and the financial forecasting indicator information. The application scenario indicator information includes applicability information, validity information, and security information corresponding to the data asset; wherein, based on the processing flow information corresponding to the data asset, obtaining the evaluation indicator information corresponding to the data asset also includes: obtaining the data asset application flow information in the processing flow information; and generating the applicability information, validity information, and security information corresponding to the data asset based on the data asset application flow information and the application scenario indicator information.

5. The method according to claim 3, characterized in that: The method of determining the revenue configuration parameters corresponding to the data asset based on the data product design information and the data product value information corresponding to the data asset comprises: determining the weight information corresponding to the data product design information based on the data product value information and preset assignment rules; comparing the weight information with a preset weight threshold to obtain a comparison result; and determining the revenue configuration parameters corresponding to the data product design information when the comparison result satisfies preset conditions.

6. A data asset value assessment device, characterized in that: The device includes: a data asset value assessment index information acquisition module, which is used to acquire the assessment index information corresponding to the data asset based on the processing flow information corresponding to the data asset, wherein the assessment index information includes technical development index information, financial forecast index information and application scenario index information; a data asset value assessment benchmark model construction module, which is used to construct a data asset value assessment benchmark model based on the technical development index information, the financial forecast index information and the application scenario index information; a data asset value assessment application model generation module, which is used to configure the data asset value assessment benchmark model using model parameter settings to generate a data asset value assessment application model, wherein the model parameter settings are associated with the cost information and benefit information of the data asset; and a data asset value assessment result generation module, which is used to evaluate the value assessment object using the data asset value assessment application model to generate an assessment result corresponding to the value assessment object.

7. An electronic device comprising: one or more processors; A memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 7.

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

9. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction 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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