Data asset management method and device, equipment and storage medium
By refining data asset objectives and building a custom management page, the problems of flexibility and universality in data asset management in existing technologies have been solved, enabling cross-industry data sharing and circulation, and improving the management efficiency and value of data assets.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- GUANGZHOU ALBATROSS INFORMATION TECH CO LTD
- Filing Date
- 2025-12-26
- Publication Date
- 2026-05-01
AI Technical Summary
Existing data asset management technologies lack flexibility and versatility, making it difficult to adapt to industry changes and cross-industry and cross-domain data asset management needs, thus limiting the circulation and maximization of data assets' value.
By acquiring user-defined data asset goals, defining data items, measurement data items, and descriptive data items, refining data asset goals, building a custom management page, and publishing data assets to the management platform, cross-industry data sharing and circulation can be achieved.
It enhances the flexibility and adaptability of data asset management, and promotes the widespread circulation and value maximization of data assets in different industry environments.
Smart Images
Figure CN121958412A_ABST
Abstract
Description
A data asset management method, apparatus, device, and storage medium Technical Field
[0001] This application relates to the field of data asset management technology, and in particular to a data asset management method, apparatus, device and storage medium. Background Technology
[0002] In today's digital age, data has become a core asset for enterprises and industries across all sectors. The effective construction and management of data assets is crucial for corporate decision-making, business optimization, and innovative development. With the rapid development of information technology, the volume of data is exploding, and data sources are becoming increasingly diversified, encompassing multiple channels from traditional databases to emerging IoT devices and social media. Various industries are actively exploring how to better manage and utilize these data assets to enhance their competitiveness and operational efficiency. Data asset construction and management technologies have emerged to meet this need, providing powerful support for enterprises' digital transformation by collecting, storing, analyzing, and applying data.
[0003] However, existing data asset management technologies have many limitations in practical applications. While these technologies can achieve data asset construction and management to a certain extent, they are often limited to specific industries or fields. They are typically developed based on in-depth analysis of the data characteristics and business processes of a particular industry or field, resulting in specialized data asset management tools. In these tools, conditional logic is directly hard-coded into the code, lacking sufficient flexibility. Once the industry environment changes, or enterprises need to expand into new business areas, these tools often struggle to adapt to new requirements, necessitating extensive redevelopment and adjustments. Furthermore, this industry- or field-specific approach to data asset management cannot meet the needs of cross-industry and cross-field data asset management and application, limiting the circulation and sharing of data assets on a broader scale and severely restricting the maximization of data asset value.
[0004] To overcome the bottlenecks of existing technologies, the urgent technical problem to be solved is how to build a data asset management technology that is both universal and flexible. Summary of the Invention
[0005] This application provides a data asset management method, apparatus, device, and storage medium to solve the aforementioned technical problems.
[0006] In view of this, the first aspect of this application provides a data asset management method, the method comprising: S101, obtaining a data asset target set by a user; S102, refining the data asset target by defining data items, measuring data items, describing data items, and defining self-defined data items, forming a data asset sub-target containing several target items and their corresponding target data items; S103, obtaining the data category of the data asset customized by the user based on the data asset sub-target, and constructing a management page for the data asset by the user according to the data category; S104, publishing the data asset to a data asset management platform through the management page.
[0007] Optionally, the definition data item is used to identify the unique identifier and / or item attribute of the target item; the measurement data item is used to identify the life cycle stage of the target item; the description data item is used to describe the content of the target item; and the user-defined data item is assigned by the user to any one of the following types: definition data item, measurement data item, or description data item, according to its actual function.
[0008] Optionally, step S103 further includes: providing a reference for the definition data item, measurement data item, and description data item to which the target data item belongs by importing a data asset target setting template recommended to the user based on the industry field on the management page, and allowing the user to actually define and confirm the definition data item, measurement data item, and description data item to which the target data item belongs.
[0009] Optionally, step S104 specifically includes: S401, generating a corresponding data collection template for the data asset selected according to the data category on the management page; S402, after collecting data through the data collection template, publishing it to the data asset management platform in combination with the data category of the data asset, generating the data asset of the data category on the data asset management platform, and the user who published the data asset having the right to publish, control, and benefit from the data asset.
[0010] Optionally, step S401 further includes: determining the data publishing scope of the data asset; and updating the data collection template according to the data publishing scope.
[0011] Optionally, after step S104, the method further includes: performing anomaly monitoring on the data asset on the management page to determine the completeness and accuracy of the data asset's publication.
[0012] Optionally, after step S104, the method further includes: visualizing the data assets by data item and generating data release results; and performing data analysis on the data assets, including open data analysis, data access analysis, and data revenue analysis.
[0013] A second aspect of this application provides a data asset management device, comprising: a target construction unit for acquiring user-defined data asset targets; a target refinement unit for refining the data asset targets using methods such as defining data items, measuring data items, describing data items, and defining custom data items, to form data asset sub-targets containing several target items and their corresponding target data items; a management unit for acquiring data categories of data assets customized by the user based on the data asset sub-targets, and constructing a management page for the user's data assets based on the data categories; and a publishing unit for publishing the data assets to a data asset management platform through the management page.
[0014] A third aspect of this application provides a data asset management device, the device comprising a processor and a memory: the memory is used to store program code and transmit the program code to the processor; the processor is used to execute the steps of the data asset management method as described in the first aspect above, according to the instructions in the program code.
[0015] A fourth aspect of this application provides a computer-readable storage medium for storing program code for performing the method described in the first aspect above.
[0016] As can be seen from the above technical solutions, the embodiments of this application have the following advantages: This application provides a data asset management method, apparatus, device, and storage medium. By obtaining the data asset target set by the user, the target direction of the constructed data asset is clarified, making it not limited to a specific industry. Then, through the definition methods of defining, measuring, describing, and self-setting data items, the target is refined into data asset sub-targets containing multiple target items and their target data items. This modular design provides scalability for different industries and fields. Users can customize data categories and build management pages according to sub-targets to meet the needs of different industries. Finally, the data assets are published to the management platform, realizing cross-industry data sharing and circulation. This step-by-step method not only improves the flexibility of data asset management but also enhances its adaptability in different industry environments, promoting the widespread circulation and value maximization of data assets. Attached Figure Description
[0017] Figure 1 is a flowchart of the data asset management method in the embodiment of this application; Figure 2 is a schematic diagram of the structure of the data asset management device in the embodiment of this application; Figure 3 is a schematic diagram of the structure of the data asset management equipment in the embodiment of this application. Detailed Implementation
[0018] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.
[0019] For ease of understanding, please refer to Figure 1. Figure 1 is a flowchart of the data asset management method in this application embodiment. As shown in Figure 1, specifically: S101, obtain the data asset goals set by the user; it should be noted that the overall vision and macro goals that the enterprise or organization expects to achieve in terms of data assets should be clearly defined. These goals should have a certain level of vision and foresight, and should be able to cover all aspects of data assets, such as data integrity, accuracy, availability, and security. At the same time, they should be consistent with the enterprise's strategic goals and provide directional guidance for the subsequent management and utilization of data assets.
[0020] For example, in the financial sector: building comprehensive, accurate, secure, and efficient data assets to support precise risk assessment, personalized financial service recommendations, efficient operational management, and regulatory-compliant reporting, thereby enhancing customer satisfaction and corporate competitiveness, and achieving sustainable business growth.
[0021] In the healthcare sector: Establish high-quality, standardized, and shareable medical data assets to support clinical diagnostic decision-making, medical research, disease monitoring and early warning, and optimal allocation of medical resources, thereby improving the quality and efficiency of medical services, promoting innovative development in the healthcare industry, and improving patients' health.
[0022] In the e-commerce sector: Build rich, accurate, and real-time updated e-commerce data assets, covering user behavior, product information, transaction records, etc., to achieve precise marketing, personalized recommendations, inventory management optimization, supply chain collaboration, etc., in order to improve user experience, increase user stickiness and sales, and enhance the company's competitiveness in the e-commerce market.
[0023] S102. By defining data items, measurement data items, description data items, and user-defined data items, the data asset target is refined to form a data asset sub-target containing several target items and their corresponding target data items. Further, the defined data items are used to identify the unique identifier and / or item attributes of the target items; the measurement data items are used to identify the life cycle stages of the target items; the description data items are used to describe the content of the target items; and the user-defined data items are assigned by the user to any one of the types of defined data items, measurement data items, or description data items according to their actual function.
[0024] It's important to note that by defining data items, measuring data items, and describing data items, the macro-level data asset objectives are broken down into specific, actionable, and measurable sub-objectives. This identifies the various target items included in the data assets (e.g., financial products and customer information in the financial sector; patient records and medical equipment in the medical sector; goods and users in the e-commerce sector). For each target item, a list of corresponding key target data items is created. These data items form the basis for subsequent data collection, management, and analysis. The data item list must be clear, accurate, and comprehensive, fully reflecting the composition and content of the data assets. In addition to the three types of data items mentioned above, when standard data items cannot meet the user's actual needs, the user can customize data items for the target items according to specific requirements. These data items may have different meanings and functions depending on the business scenario, but are ultimately assigned as defining data items, measuring data items, or describing data items based on their actual function.
[0025] For example: In the financial sector: target items: customer information, financial products, transaction records, etc.
[0026] Target data items: Customer information: customer name, ID number, contact information, occupation, income level, credit score, etc.
[0027] Financial products: product name, product type (such as savings, loan, wealth management, etc.), interest rate, term, risk level, etc.
[0028] Transaction records include: transaction time, transaction amount, transaction channel, transaction status, and counterparty.
[0029] Medical field: Target items: patient medical records, medical equipment, medicines, etc.
[0030] Target data items: Patient case records: patient name, gender, age, medical record number, symptoms, diagnosis, treatment plan, examination and test reports, etc.
[0031] Medical equipment: Equipment name, equipment model, manufacturer, purchase date, department using it, maintenance records, etc.
[0032] Drugs: Drug name, drug ingredients, drug specifications, manufacturer, approval number, expiration date, and inventory quantity, etc.
[0033] In the e-commerce sector: target items include products, users, and orders.
[0034] Target data items: Products: Product name, product category, product specifications, price, inventory quantity, sales volume, supplier information, etc.
[0035] User information includes: user name, user account, contact information, registration time, purchase preferences, browsing history, membership level, etc.
[0036] Order details: order number, order time, order amount, payment method, shipping address, shipping status, order rating, etc.
[0037] S103. Obtain the data category of the data asset customized by the user based on the data asset sub-target, and construct the user's management page for the data asset according to the data category; further, step S103 also includes: providing reference for the definition data item, measurement data item and description data item to which the target data item belongs by importing the data asset target setting template recommended to the user according to the industry field into the management page, and allowing the user to actually define and confirm the definition data item, measurement data item and description data item to which the target data item belongs.
[0038] It's important to note that users (who may be internal business personnel, data management personnel, etc.) categorize data assets based on sub-objectives and their own business needs. Data categories can be based on business domains, such as customer data, product data, sales data, and financial data; or they can be based on data usage, such as data for analysis, decision support data, and operational monitoring data. Users can flexibly define data categories according to their actual needs to meet data management and application requirements in different scenarios.
[0039] Based on user-defined data categories, a dedicated management page is provided for each user. This management page serves as the interface for users to interact with their data assets, allowing them to perform various operations and management tasks, such as data entry, querying, updating, and deletion. The management page should be designed to be simple, intuitive, and user-friendly, clearly displaying the status of data assets under different data categories.
[0040] For example, in an e-commerce company, users (such as data analysts) categorize customer data assets into three types based on data asset sub-objectives: "New Customer Data," "Active Customer Data," and "Churned Customer Data." The system then creates a customer data management page for the data analyst based on these data categories. This management page has three distinct areas corresponding to new customer data, active customer data, and churned customer data. Data analysts can easily view detailed information for different categories of customer data on this page. For instance, the new customer data area can display information such as the new customer's name, registration date, and initial purchase intention; the active customer data area can display information such as the purchase frequency and recently purchased products of active customers; and the churned customer data area can display information such as the time and reason for churn of churned customers.
[0041] To help users define data items more efficiently, the system offers an optional step: importing existing data asset target setting templates. These templates are based on industry best practices or summaries of past corporate experience and include examples and suggestions for defining, measuring, and describing common target data items. Users can refer to these templates and, in conjunction with their own specific circumstances, define and confirm the various data items to which their target data items belong. This avoids users defining data items from scratch, saving time and effort, and also helps ensure the standardization and consistency of data item definitions.
[0042] For example, in an e-commerce company, a data analyst imports a common customer data asset goal setting template used in the e-commerce industry onto the management page. Examples of defined customer target data items in this template include customer name, customer ID number, and customer contact information; examples of metric data items include customer purchase frequency, cumulative customer purchase amount, and customer return / exchange frequency; and examples of descriptive data items include customer satisfaction rating, customer loyalty level, and the consumption level of the customer's region. The data analyst refers to these examples and, combined with the company's own business characteristics and data asset sub-goals, defines and confirms the actual customer data items. For instance, the company believes that customer ID numbers are not very meaningful for the business and therefore does not use them; however, based on the company's specific definition of customer loyalty, the definition of customer loyalty level is adjusted to better reflect the company's actual situation.
[0043] S104. Publish data assets to the data asset management platform through the management page. It should be noted that after the user completes the definition and classification of data assets and builds the management page, these data assets are published to the data asset management platform through the management page. The data asset management platform is a system for centralized management and maintenance of data assets, providing support for the storage, sharing, use, and monitoring of data assets. Publishing data assets to this platform means that the data assets have officially entered the enterprise's data management system and can be accessed and used by other enterprises according to the prescribed permissions.
[0044] Further, step S104 specifically includes: S401, generating corresponding data collection templates for the data assets selected according to data categories on the management page; it should be noted that data collection is a crucial step in data asset construction. To ensure that the collected data meets the requirements of the data assets, corresponding data collection templates need to be generated according to the data categories. Data collection templates are tools used to guide data collection work, clarifying which data items need to be collected, the data format, the source of collection, the frequency of collection, and other information. Through data collection templates, the standardization and accuracy of data collection can be guaranteed, avoiding data omissions or errors.
[0045] In e-commerce companies, data analysts select and generate a data collection template for the "New Customer Data" category on the customer data management page. This template specifies the new customer data items to be collected, such as customer name, registered email address, registration date, and registration source; it also specifies the data format, such as text format for customer name and date format for registration date; it clarifies the data collection source, such as customer name and registered email address from customer registration forms, registration date automatically recorded by the system, and registration source from website traffic analysis tools; and it determines the data collection frequency, such as collecting new customer data immediately after successful registration and then updating customer activity status monthly thereafter.
[0046] S402. After data collection through the data collection template, the data is published to the data asset management platform in combination with the data asset category. The data asset of the data category is generated on the data asset management platform, and the user who published the data asset has the right to publish, control and benefit from the data asset.
[0047] It should be noted that, following the data collection template requirements, data is collected from various data sources. After preprocessing operations such as cleaning and transformation, the collected data is published to the data asset management platform according to the data asset categories. On the platform, the data is organized and stored according to different data categories, forming complete data assets. The platform stores and manages data according to data categories. Users have the right to publish, control, and benefit from the data assets, ensuring data security and compliance. When controlling data assets, users can quickly open data assets according to their defined data categories, achieving classified control of data assets.
[0048] For example, in the financial sector: After collecting customer information, financial product information, transaction records, and other data from various business systems using data collection templates, the data undergoes cleaning to remove duplicate and erroneous data. Then, based on data categories, customer basic information data, financial product information data, and transaction record data are published to the data asset management platform. The platform categorizes, stores, and manages these data according to their categories. For instance, in the customer basic information data category, it is easy to query and manage data such as the customer's name, ID number, and contact information.
[0049] In the medical field: After preprocessing, the collected patient case data, medical equipment data, and drug data are published to the data asset management platform according to data categories such as basic patient information, patient medical records, medical equipment information, and drug information. The platform stores and manages the data according to these categories. Medical staff and managers can quickly find the required patient case data, medical equipment data, and drug data through the platform, which facilitates medical decision-making and resource management.
[0050] In the e-commerce sector: After the collected product information, user information, order information, and other data are processed, they are published to the data asset management platform according to data categories such as product information, user information, and order information. The platform organizes and stores the data according to these categories. E-commerce company operators can use the platform to manage and analyze product sales, user purchasing behavior, and order processing status, providing data support for e-commerce operations.
[0051] Furthermore, step S401 also includes: determining the data release scope of the data assets; and updating the data collection template according to the data release scope.
[0052] It is important to note that before publishing data assets, the scope of publication must be determined, i.e., which data can be released externally, to ensure data security and compliance. Based on the determined scope of data publication, the data collection template should be updated, and the content and methods of data collection should be adjusted to ensure that the collected data meets the requirements for publication and authorization.
[0053] Furthermore, after step S104, the method also includes: monitoring data assets for anomalies on the management page to determine the integrity and accuracy of the data asset release.
[0054] It's important to note that after data assets are published to the data asset management platform, anomaly monitoring is necessary to ensure their quality and availability. Anomaly monitoring primarily checks for anomalies such as missing data, data errors, data duplication, and untimely updates. By monitoring these anomalies, potential problems during the publication or use of data assets can be identified promptly, allowing for appropriate corrective action. Simultaneously, it's crucial to ensure the completeness and accuracy of the published data assets, verifying that the data published to the platform is intact, its content is authentic and reliable, and it conforms to the definition and requirements of data assets. This helps ensure that the data assets can realize their full value in subsequent use.
[0055] Furthermore, after step S104, the process also includes: visualizing the data assets by data item and generating data release results; and conducting data analysis on the data assets, including open data analysis, data access analysis, and data revenue analysis.
[0056] It should be noted that each data item in the data asset can be visualized in intuitive charts, graphs, maps, etc., enabling users to quickly and clearly understand the content and characteristics of the data asset, facilitating data viewing and comprehension. Depending on different data categories and business needs, appropriate visualization methods can be selected, such as bar charts, line charts, pie charts, scatter plots, etc., to create data publication results, providing visual support for data sharing and application.
[0057] Open data analytics: Analyze the openness and usage of data assets, understand which data is made available to external users or organizations, the frequency and effectiveness of open data usage, assess the value and impact of open data, and provide a basis for adjusting and optimizing data openness strategies.
[0058] Data access analysis: Statistics and analysis of how data assets are accessed by internal departments or external users, including information such as the number of times data is accessed, the time of access, and the user or department that accessed the data. This helps to understand the data usage needs and patterns, identify data access hotspots and bottlenecks, and provide a reference for optimized data management and resource allocation.
[0059] Data benefit analysis: This assesses the benefits that data assets bring to a company or organization, including direct economic benefits (such as increased sales through data-driven marketing campaigns, and operational cost savings through data optimization) and indirect benefits (such as improved corporate image and enhanced competitiveness). Data benefit analysis can measure the value and return on investment of data assets, providing decision support for the continued investment and development of data assets.
[0060] Please refer to Figure 2, which is a schematic diagram of the data asset management device in this embodiment of the application. As shown in Figure 2, the device consists of: a target construction unit 201, used to obtain the data asset target set by the user; a target refinement unit 202, used to refine the data asset target by defining data items, measuring data items, describing data items, and defining self-defined data items, forming a data asset sub-target containing several target items and their corresponding target data items; a management unit 203, used to obtain the data category of the data asset customized by the user based on the data asset sub-target, and construct the user's data asset management page according to the data category; and a publishing unit 204, used to publish the data asset to the data asset management platform through the management page.
[0061] Another embodiment of the present invention provides a data asset management device, as shown in FIG3. The device 10 includes one or more processors 110 and a memory 120. FIG3 is described with one processor 110 as an example. The processor 110 and the memory 120 can be connected by a bus or other means. FIG3 is shown with a bus connection as an example.
[0062] Processor 110 is used to perform various control logics of device 10, and can be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), microcontroller, ARM (Acorn RISC Machine) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination of these components. Furthermore, processor 110 can also be any conventional processor, microprocessor, or state machine. Processor 110 can also be implemented as a combination of computing devices, such as a combination of DSP and microprocessor, multiple microprocessors, one or more microprocessors combined with DSP and / or any other such configuration.
[0063] The memory 120, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions corresponding to the method for constructing the multilingual phoneme representation model in this embodiment of the invention. The processor 110 executes various functional applications and data processing of the device 10 by running the non-volatile software programs, instructions, and units stored in the memory 120, thereby implementing the method for constructing the multilingual phoneme representation model in the above-described method embodiment.
[0064] The memory 120 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created according to the use of the device 10. Furthermore, the memory 120 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 120 may optionally include memory remotely located relative to the processor 110, and these remote memories may be connected to the device 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
[0065] One or more units are stored in memory 120. When executed by one or more processors 110, the following steps are implemented: S101, obtaining the data asset target set by the user; S102, refining the data asset target by defining data items, measuring data items, describing data items, and self-defined data items to form a data asset sub-target containing several target items and their corresponding target data items; S103, obtaining the data category of the data asset customized by the user based on the data asset sub-target, and constructing the user's data asset management page according to the data category; S104, publishing the data asset to the data asset management platform through the management page.
[0066] This invention provides a non-volatile computer-readable storage medium storing computer-executable instructions. When these computer-executable instructions are executed by one or more processors, they implement any one of the data asset management methods described in the above embodiments.
[0067] As examples, non-volatile storage media can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) as external cache memory. By way of illustration and not limitation, RAM can be obtained in many forms such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM (DRRAM). The memory components or memories disclosed in the operating environment described herein are intended to include one or more of these and / or any other suitable types of memory.
[0068] This application provides a data asset management method, apparatus, device, and storage medium. By acquiring user-defined data asset targets, the target direction of the constructed data assets is clarified, making it not limited to a specific industry. Then, through methods such as defining, measuring, describing, and customizing data items, the targets are refined into data asset sub-targets containing various target items and their target data items. This modular design provides scalability for different industries and fields. Users can customize data categories and build management pages based on sub-targets to meet the needs of different industries. Finally, the data assets are published to the management platform, realizing cross-industry data sharing and circulation. This step-by-step approach not only improves the flexibility of data asset management but also enhances its adaptability to different industry environments, promoting the widespread circulation and maximizing the value of data assets.
[0069] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.
[0070] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0071] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.
[0072] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.
[0073] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0074] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.
[0075] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.
[0076] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.
[0077] It should be noted that if any software tools or components not belonging to our company appear in the embodiments of this application, they are merely for illustrative purposes and do not represent actual use.
Claims
1. A data asset management method, characterized in that, include: S101. Obtain the user-defined data asset target; S102. Refine the data asset target by defining data items, measuring data items, describing data items, and custom data items, forming a data asset sub-target containing several target items and their corresponding target data items; S103. Obtain the data category of the data asset customized by the user based on the data asset sub-target, and construct the user's management page for the data asset according to the data category; S104. Publish the data asset to the data asset management platform through the management page.
2. The data asset management method according to claim 1, characterized in that, The defined data items are used to identify the unique identifier and / or attribute of the target item; the measurement data items are used to identify the life cycle stages of the target item; the description data items are used to describe the content of the target item; the user-defined data items are assigned by the user to any one of the following types: defined data items, measurement data items, or description data items, according to their actual function.
3. The data asset management method according to claim 1, characterized in that, Step S103 further includes: importing a data asset target setting template recommended to the user based on the industry field into the management page to provide a reference for the definition data item, measurement data item, and description data item to which the target data item belongs, and allowing the user to actually define and confirm the definition data item, measurement data item, and description data item to which the target data item belongs.
4. The data asset management method according to claim 1, characterized in that, Step S104 specifically includes: S401, generating a corresponding data collection template for the data asset selected according to the data category on the management page; S402, after collecting data through the data collection template, publishing it to the data asset management platform in combination with the data category of the data asset, generating the data asset of the data category on the data asset management platform, and the user who published the data asset having the right to publish, control and benefit from the data asset.
5. The data asset management method according to claim 4, characterized in that, Step S401 further includes: determining the data publishing scope of the data asset; and updating the data collection template according to the data publishing scope.
6. The data asset management method according to claim 1, characterized in that, Following step S104, the method further includes: performing anomaly monitoring on the data asset on the management page to determine the completeness and accuracy of the data asset's publication.
7. The data asset management method according to claim 1, characterized in that, The steps following step S104 further include: visualizing the data assets by data item and generating data release results; and performing data analysis on the data assets, including open data analysis, data access analysis, and data revenue analysis.
8. A data asset management device, characterized in that, include: Target building unit, used to acquire user-defined data asset targets; The target refinement unit is used to refine the data asset target by defining data items, measuring data items, describing data items and defining self-defined data items, forming a data asset sub-target that includes several target items and their corresponding target data items. The management unit is used to obtain the data category of the data asset customized by the user based on the data asset sub-target, and construct the user's management page for the data asset according to the data category; the publishing unit is used to publish the data asset to the data asset management platform through the management page.
9. A data asset management device, characterized in that, The device includes a processor and a memory: the memory is used to store program code and transmit the program code to the processor; the processor is used to execute the data asset management method according to any one of claims 1-7 according to the instructions in the program code.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store program code for executing the data asset management method according to any one of claims 1-7.