Data asset management method and device, equipment, storage medium and program product

Abstract

The invention discloses a data asset management method and device, equipment, a storage medium and a program product, and relates to the technical field of data processing, and the method comprises the steps: obtaining an enterprise-level data model; performing business processing on the enterprise-level data model to obtain multiple pieces of intermediate object data; identifying a data asset based on the plurality of intermediate object data and a preset data use range; and classifying and grading the data assets to obtain the data assets with different data values. According to the method, the data assets can be dynamically identified by identifying a complete business processing process on the basis of preset business logic, and high-value data is identified for enterprises and organizations through classification and level-to-level management of the data assets, so that the threshold of data value mining is greatly reduced, and the data is prompted to really become core assets of the enterprise organizations.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to data asset management methods, devices, equipment, storage media, and program products. Background Art

[0002] In the current information age, as the digital transformation of the entire industry accelerates, the generation of information data has also exploded. At the same time, the importance and investment in the discovery of value contained in data have been raised to an unprecedented level, especially the tremendous progress in artificial intelligence technology, which has brought unlimited imagination to the value that data can generate. Data has become an emerging asset in the process of digital transformation of the economy and society, and is becoming a strategic resource for the development of the digital economy, and is also the core asset of social organizations.

[0003] Under the current wave of digital transformation, corporate organizations have accumulated massive amounts of data, but how to maximize the value of existence from massive amounts of data has always been an urgent demand of various corporate organizations. Summary of the invention

[0004] The main purpose of this application is to provide a data asset management method, device, equipment, storage medium and program product, aiming to solve the technical problem of how to identify the potential value of data assets from various types of data.

[0005] Get enterprise-level data models;

[0006] Performing business processing on the enterprise-level data model to obtain a plurality of intermediate object data;

[0007] Based on the plurality of intermediate object data and the preset data usage scope, identifying data assets;

[0008] The data assets are classified and graded to obtain data assets of different data values.

[0009] In one embodiment, before the step based on the plurality of intermediate object data and the preset data usage range, the method further includes:

[0010] Define the scope of data usage based on the subject domain and usage of the enterprise-level data model

[0011] In one embodiment, the step of identifying data assets based on the plurality of intermediate object data and the preset data usage scope includes:

[0012] Combine multiple intermediate object data to obtain external service object data;

[0013] Determine whether the external service object data complies with the preset data usage scope;

[0014] If the external service object data conforms to the preset data usage scope, the external service object data is used as a data asset.

[0015] In one embodiment, after the step of using the external service object data as data assets, the method further includes:

[0016] An enterprise-wide data model that identifies non-data assets;

[0017] Access restrictions are imposed on the enterprise-level data model of the non-data asset according to preset access permissions.

[0018] In one embodiment, the step of classifying and grading the data assets to obtain data assets of different data values ​​includes:

[0019] Based on the value assessment dimension of data assets, data assets are classified, identified and managed in a graded manner to obtain data assets with different data values.

[0020] In one embodiment, the steps of classifying and identifying data assets and hierarchically managing data assets based on the evaluation dimension of data value to obtain data assets of different data values ​​include:

[0021] Defining the value assessment dimension of the data asset based on the number of accesses and the number of accesses to the data asset;

[0022] According to the value assessment dimension, the data assets are classified and identified to obtain data assets of different categories;

[0023] The different categories of data assets are managed in a hierarchical manner to obtain data assets of different data values.

[0024] In addition, to achieve the above purpose, the present application also proposes a data asset management device, the data asset management device comprising:

[0025] The identification module is used to identify data assets in the data warehouse based on preset business logic;

[0026] The management module is used to perform hierarchical management on the data assets and obtain data assets of different data values.

[0027] In addition, to achieve the above objectives, the present application also proposes a data asset management device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the data asset management method described above.

[0028] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the data asset management method described above are implemented.

[0029] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the data asset management method described above.

[0030] The embodiments of the present application provide a data asset management method, device, equipment, storage medium and program product, which specifically include: obtaining an enterprise-level data model; performing business processing on the enterprise-level data model to obtain multiple intermediate object data; identifying data assets based on multiple intermediate object data and a preset data usage scope; classifying and grading data assets to obtain data assets of different data values. The method is based on preset business logic processing steps, and can dynamically identify data assets by identifying the complete business processing process, and by classifying and grading data assets, it can identify high-value data for enterprises and organizations, greatly reducing the threshold for data value discovery, and enabling data to truly become the core asset of enterprise organizations. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0032] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0033] Figure 1 A flowchart of the first embodiment of the data asset management method of this application is provided;

[0034] Figure 2 A schematic diagram of the working principle of the business logic unit of the data asset management method provided in Example 1 of the present application;

[0035] Figure 3 A flowchart of the second embodiment of the data asset management method of this application is provided;

[0036] Figure 4 This is a schematic diagram of the module structure of the data asset management device according to an embodiment of the present application;

[0037] Figure 5Schematic diagram of the device structure of the hardware operating environment involved in the data asset management method in the embodiment of the present application. DETAILED DESCRIPTION

[0038] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0039] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0040] The main solutions of the embodiments of the present application are: obtaining an enterprise-level data model; performing business processing on the enterprise-level data model to obtain multiple intermediate object data; identifying data assets based on multiple intermediate object data and a preset data usage scope; classifying and grading data assets to obtain data assets with different data values.

[0041] In the current information age, as the digital transformation of the entire industry accelerates, the generation of information data has also exploded. At the same time, the importance and investment in the discovery of value contained in data have been raised to an unprecedented level, especially the tremendous progress in artificial intelligence technology, which has brought unlimited imagination to the value that data can generate. Data has become an emerging asset in the process of digital transformation of the economy and society, and is becoming a strategic resource for the development of the digital economy, and is also the core asset of social organizations.

[0042] Data includes numbers, text, images, videos, audio and other aspects, and the premise for data to be used and to play its value is that it can be interpreted. The data model abstractly describes the characteristics of data from three aspects: static characteristics, dynamic behavior and constraints, so that the specific content and interrelationships of the data can be understood.

[0043] Data models abstract data features. In the current massive data at the enterprise level, the number of data models also ranges to tens of thousands or even millions, including high-value data and low-value data. How to identify the most valuable data in the same massive data models, maximize the value of the massive data accumulated by the enterprise, and make data the real core asset of the enterprise organization has always been the difficulty and pain point of current data value mining.

[0044] This application provides a solution to obtain an enterprise-level data model in an enterprise-level data warehouse; perform business processing on the enterprise-level data model to obtain multiple intermediate object data, and identify data assets based on multiple intermediate object data and preset data usage scopes; classify and grade data assets to obtain data assets with different data values. Since the data model in the enterprise-level data warehouse is always in a dynamic change process, automated data asset identification and usage management are realized, thereby solving the problem of changing massive data from disorder to order, and focusing on identifying high-value data assets.

[0045] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, etc. The following takes a personal computer as an example to illustrate this embodiment and the following embodiments.

[0046] Based on this, the present application embodiment provides a data asset management method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the data asset management method of the present application.

[0047] In this embodiment, the data asset management method includes steps S10 to S40:

[0048] Step S10, obtaining an enterprise-level data model;

[0049] Optionally, during the data processing of the big data platform, the result data output corresponding to each data model will reference other data sources, which is called upstream; it may also be the source of other data models, which we call downstream. There are two types of downstream: one is the automated batch processing downstream, and the other is the downstream for flexible query by data analysts. Through this upstream and downstream reference relationship, a directed acyclic graph of data flow or access relationship on the big data platform is formed.

[0050] Step S20, performing business processing on the enterprise-level data model to obtain a plurality of intermediate object data;

[0051] Alternatively, in an enterprise-level data warehouse, the processing of a business result is often a comprehensive process that requires the use of enterprise-level data models from multiple sources and is divided into multiple steps for processing to obtain the final data result. Each link in this processing process is classified as a business logic unit.

[0052] In each business logic unit, business processing is performed on the enterprise-level data model, and multiple intermediate object data are generated during the processing.

[0053] Step S30, identifying data assets based on the plurality of intermediate object data and a preset data usage scope;

[0054] It should be noted that data assets refer to data that can be used and have clear value, which are called data assets.

[0055] In order to effectively identify data assets in massive data and further identify the potential value of data assets, this embodiment proposes a method for identifying data assets according to a preset data usage scope.

[0056] Before executing step S30, the data usage scope needs to be predefined to obtain a preset data usage scope, and the preset data usage scope is used in step S30 to improve the recognition accuracy and efficiency of data assets.

[0057] Optionally, the scope of data usage is defined according to the subject domain of enterprise-level data and the usage of business products. The subject domain refers to the classification of enterprise-level data according to specific themes or functional areas, which usually reflect the main business activities or concerns of the enterprise. By dividing the data by subject domain, the design of the data warehouse can be made clearer and more orderly, which is convenient for users to understand and query; the usage of business products refers to the relevant data on the actual use of products or services provided by the enterprise by consumers, including but not limited to the number of users and growth trends, user activity indicators, user behavior analysis, product performance, etc.

[0058] The scope of data usage is defined in combination with the usage of subject domains and business products. That is, in an enterprise-level data warehouse, the enterprise-level data model is divided according to the usage of subject domains or business products. Only data that can be used across subject domains or products has potential value, that is, it is identified as a data asset.

[0059] After obtaining the predefined data usage scope, the enterprise-level data is sent to the business logic unit, where the enterprise-level data is processed and processed to generate intermediate object data, and data assets are identified based on the intermediate object data and the predefined data usage scope. Figure 2 , Figure 2 A schematic diagram of the working principle of the business logic unit provided by the method of this embodiment.

[0060] In a feasible implementation, step S30 may include steps S31 to S33:

[0061] Step S31, combining multiple intermediate object data to obtain external service object data;

[0062] It should be noted that the intermediate result data refers to a temporary data set generated during the execution of each business logic unit.

[0063] Optionally, according to the upstream and downstream access relationship of the data model, trace upstream to the point where the upstream data model is a data asset. If the upstream data model only serves one data asset, the intermediate object data corresponding to the data model is processed to obtain the final data result, i.e., the external service object data. If the upstream data model serves multiple data assets, multiple intermediate result data corresponding to the upstream data model service are combined according to the service status of the field to obtain the external service object data.

[0064] Step S32, determining whether the external service object data complies with a preset data usage scope;

[0065] Optionally, based on a preset data usage scope, it is determined whether the external service object data meets the data usage requirements.

[0066] Specifically, if the external service object data meets one of the following conditions, it will be identified as a data asset: ① The data model is accessed across business subject domains, that is, automated batch access. The more cross-business subject domains are accessed, the higher the sharing of the data model is, and the greater the corresponding asset value is. ② For data models that are only accessed within the business subject domain, the number of automated batch accesses and flexible queries within a fixed time T exceed the thresholds P1 and P2.

[0067] Step S33: If the external service object data conforms to the preset data usage scope, the external service object data is used as a data asset.

[0068] Optionally, once it is confirmed that the intermediate result data meets the preset data usage scope, the corresponding processed enterprise-level data can be formally marked as a data asset. It should be noted that the intermediate object data generated by the processing process in the business logic unit is only used within this field and is not counted as a data asset.

[0069] Step S40, classify and grade the data assets to obtain data assets of different data values.

[0070] Optionally, enterprise-level data identified as data assets may be classified, identified, and managed in a graded manner according to the evaluation dimensions of the data value of data services provided downstream, so that high-value data assets can be identified in a focused manner.

[0071] Furthermore, the step of "classifying and identifying and hierarchically managing the data value of the data services provided downstream according to the evaluation dimension" further includes steps S41 to S43:

[0072] Step S41, defining the value assessment dimension of the data asset according to the number of accesses and the number of accesses of the data asset;

[0073] Optionally, defining the value assessment dimensions of data assets is a key step in ensuring that the enterprise can identify and prioritize high-value data.

[0074] In this embodiment, the value assessment dimensions of data assets are defined according to the frequency, quantity, importance and other dimensions of data services provided by the downstream. Among them, the frequency of access or use of data assets is defined, and the access pattern of data is tracked by using log analysis tools by recording the number of queries for data within a certain period of time. The number of data accesses by different users or systems is defined. The use of data is recorded by counting and recording the number of different users or systems using the data. The importance of achieving business goals is defined, and the importance of data is determined through business impact analysis.

[0075] Step S42, classifying and identifying the data assets according to the value assessment dimension to obtain data assets of different categories;

[0076] Optionally, the importance of data assets identified from the enterprise-level data model is defined according to the number and frequency of accesses. The more data assets are accessed, the higher their value is. Strengthening the corresponding data asset construction and management can maximize the value they contain and make them more widely used. In terms of the value of data assets, the enterprise-level data model is divided into high-quality assets, high-efficiency assets, medium-efficiency assets, low-efficiency assets and non-data assets through a hierarchical classification method to clearly show their value.

[0077] For example, the access criteria for each type of data asset are as follows:

[0078] Premium assets: batch processing cross-region access exceeds 10, and the number of flexible data analysis queries exceeds 1,000 in the past three months;

[0079] Efficient assets: batch processing cross-region access exceeds 5, and the number of flexible data analysis queries exceeds 600 in the past three months;

[0080] Medium-efficiency assets: batch processing cross-region access exceeds 1, and the number of flexible data analysis queries exceeds 100 in the past three months;

[0081] Inefficient assets: There is batch processing cross-region access, and the number of flexible queries for data analysis in the past three months exceeds 10;

[0082] Non-data assets: Data models that are not included in the category of data assets are classified as non-data assets.

[0083] Step S43, hierarchically managing the data assets of different categories to obtain data assets of different data values.

[0084] Optionally, for high-quality and efficient assets, during the asset construction process, the asset manager is required to fully maintain the attribute information of the data asset, including detailed caliber description, data scope included in the asset, data security level, data quality and data timeliness, and data usage recommendations, in order to enable all types of data users to quickly and independently complete data exploration and find target data. In the data asset display, high-quality and efficient assets are recommended with the highest priority to give full play to the maximum value of high-quality and efficient assets.

[0085] In summary, the method of this embodiment is an automated identification and management method for data assets in an enterprise-level data warehouse. This method has been fully implemented by our company and has the characteristics of being customizable, easy to use, and high-performance. Compared with the original manual identification and construction of data assets and management scenarios, its accuracy, efficiency, and released labor costs have all been improved several times.

[0086] Through the above-mentioned embodiment method, in the enterprise-level data warehouse, the data asset is dynamically identified for the massive enterprise-level data, and hierarchical construction and management are performed. Since the data model in the enterprise-level data warehouse is always in a dynamic change process, automatic data asset identification and use management are realized, thereby solving the problem of massive data from disorder to order, and focusing on identifying high-value data assets.

[0087] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 3 After step S33, the data asset management method further includes steps S331 to S332:

[0088] Step S331, identifying the enterprise-level data model of non-data assets;

[0089] Optionally, in the business logic unit, except for the data models identified as data assets, all other data models are non-data asset data models.

[0090] Step S332: restricting access to the enterprise-level data model of the non-data asset according to preset access rights.

[0091] It should be noted that the core idea of ​​the unrestricted-is-shared principle is that if a data asset does not have explicitly set access permissions or permission controls, then by default the data asset should be considered accessible and usable by all members of the organization.

[0092] Optionally, the data of external service objects identified as data assets within the business logic unit will be identified as data assets, and key construction will be strengthened. In accordance with the principle of "unrestricted or shared", the premise of data security management will be combined, access will be opened, and all elements of asset construction will be improved.

[0093] For data models that are not identified as data assets, including intermediate object data, access and use are strictly restricted and, in principle, access is limited to the business subject domain.

[0094] Through the above-mentioned embodiment method, the principle of "unrestricted sharing" is effectively used to promote information sharing, while restricting access to the data model of non-data assets to ensure data security and compliance. This helps to improve work efficiency and reduce the risks caused by improper data processing.

[0095] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the data asset management method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0096] This application also provides a data asset management device, please refer to Figure 4 , the data asset management device comprises:

[0097] An acquisition module 10 is used to acquire an enterprise-level data model;

[0098] A processing module 20, configured to perform business processing on the enterprise-level data model to obtain a plurality of intermediate object data;

[0099] An identification module 30, configured to identify data assets based on the plurality of intermediate object data and a preset data usage scope;

[0100] The management module 40 is used to classify and grade the data assets to obtain data assets of different data values.

[0101] The data asset management device provided by the present application adopts the data asset management method in the above embodiment, which can solve the technical problem of identifying the potential value of data assets from various types of data. Compared with the prior art, the beneficial effects of the data asset management device provided by the present application are the same as the beneficial effects of the data asset management method provided by the above embodiment, and the other technical features in the data asset management device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0102] The present application provides a data asset management device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the data asset management method in the above-mentioned embodiment one.

[0103] Reference below Figure 5 , which shows a schematic diagram of the structure of a data asset management device suitable for implementing an embodiment of the present application. The data asset management device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The data asset management device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0104] like Figure 5 As shown, the data asset management device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the data asset management device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the data asset management device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a data asset management device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0105] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0106] The data asset management device provided by this application adopts the data asset management method in the above embodiment, which can solve the technical problem of identifying the potential value of data assets from various types of data. Compared with the prior art, the beneficial effects of the data asset management device provided by this application are the same as the beneficial effects of the data asset management method provided by the above embodiment, and the other technical features in the data asset management device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0107] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0108] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0109] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the data asset management method in the above-mentioned embodiment.

[0110] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, 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), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0111] The computer-readable storage medium may be included in the data asset management device; or may exist independently without being assembled into the data asset management device.

[0112] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the data asset management device, the data asset management device enables the data asset management device to: identify data assets based on preset business logic; classify and grade the data assets to obtain data assets with different data values.

[0113] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0114] 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 application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the 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 square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square 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 square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0115] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0116] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned data asset management method, and can solve the technical problem of how to identify the potential value of data assets from various types of data. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the data asset management method provided in the above-mentioned embodiment, and will not be repeated here.

[0117] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned data asset management method when executed by a processor.

[0118] The computer program product provided by this application can solve the technical problem of identifying the potential value of data assets from various types of data. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the data asset management method provided by the above embodiment, which will not be repeated here.

[0119] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A data asset management method, characterized in that: The method comprises: Get enterprise-level data models; Performing business processing on the enterprise-level data model to obtain a plurality of intermediate object data; Based on the plurality of intermediate object data and the preset data usage scope, identifying data assets; The data assets are classified and graded to obtain data assets of different data values.

2. The method according to claim 1, characterized in that Before the step based on the plurality of intermediate object data and the preset data usage scope, the method further includes: Define the scope of data usage based on the subject domain and usage corresponding to the enterprise-level data model.

3. The method according to claim 2, characterized in that The step of identifying data assets based on the plurality of intermediate object data and the preset data usage scope comprises: Combine multiple intermediate object data to obtain external service object data; Determine whether the external service object data complies with the preset data usage scope; If the external service object data conforms to the preset data usage scope, the external service object data is used as a data asset.

4. The method according to claim 3, characterized in that After the step of using the external service object data as data assets, the method further includes: An enterprise-wide data model that identifies non-data assets; Access restrictions are imposed on the enterprise-level data model of the non-data asset according to preset access permissions.

5. The method according to claim 1, characterized in that The step of classifying and grading the data assets to obtain data assets of different data values ​​comprises: Based on the value assessment dimension of data assets, data assets are classified, identified and managed in a graded manner to obtain data assets with different data values.

6. The method according to claim 5, characterized in that The steps of classifying and identifying data assets and managing them in different levels based on the evaluation dimension of data value and obtaining data assets with different data values ​​include: Defining the value assessment dimension of the data asset based on the number of accesses and the number of accesses to the data asset; According to the value assessment dimension, the data assets are classified and identified to obtain data assets of different categories; The different categories of data assets are managed in a hierarchical manner to obtain data assets of different data values.

7. A data asset management device, characterized in that: The device comprises: Acquisition module, used to obtain enterprise-level data models; A processing module, used for performing business processing on the enterprise-level data model to obtain a plurality of intermediate object data; An identification module, configured to identify data assets based on the plurality of intermediate object data and a preset data usage scope; The management module is used to classify and grade the data assets and obtain data assets of different data values.

8. A data asset management device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the data asset management method according to any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the data asset management method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the data asset management method according to any one of claims 1 to 6 are implemented.

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