Data management method, apparatus, device, and computer program product

Abstract

The invention provides a data management method, device and equipment and a computer program product, and relates to the technical field of computers and Internet. The data management method comprises the steps of creating standard metadata for target data; generating a data model of the target data based on the standard metadata; and inputting the target data into the data model based on the standard metadata to generate a physical table corresponding to the target data. The embodiment of the invention can improve the management efficiency of the target data.

Description

(19) State Intellectual Property Office (12) Invention Patent Application (10) Application Publication Number (43) Application Publication Date (21) Application Number 202511193976.X (22) Application Date 2025.08.25 (71) Applicant China Telecom International Limited Address 28 / F, Everbright Centre, 108 Gloucester Road, Wanchai, Hong Kong (72) Inventors Yang Hongbin Wu Shunde Jiang Hua Wu Qiang Huang Xiaolian (74) Patent Agency Beijing Lvzhi Intellectual Property Agency Co., Ltd. 11438 Patent Attorney Wang Lin (51) Int.Cl. G06F 16 / 28 (2019.01) G06F 16 / 21 (2019.01) G06F 16 / 22 (2019.01) (54) Invention Title Data Management Method, Apparatus, Device and Computer Program Product (57) Abstract This disclosure provides a data management method, apparatus, device and computer program product, relating to the field of computer and Internet technology. A data management method includes: creating standard metadata for target data; generating a data model of the target data based on the standard metadata; and inputting the target data into the data model based on the standard metadata to generate a physical table corresponding to the target data. This disclosure can improve the management efficiency of target data. (Claims: 2 pages; Description: 13 pages; Drawings: 7 pages; CN 121092640 A 2025.12.09 CN 1 21 09 26 40 A) 1. A data management method, characterized in that it includes: creating standard metadata for target data; generating a data model of the target data based on the standard metadata; and inputting the target data into the data model based on the standard metadata to generate a physical table corresponding to the target data. 2. The method according to claim 1, characterized in that a data model table is defined in the data model; the standard metadata includes table metadata and attribute metadata, wherein the table metadata is data used to describe the physical table; the attribute metadata is data used to describe the fields in the physical table; wherein generating a data model of the target data based on the standard metadata includes: a low-code generator generating a low-code script based on the standard metadata; wherein the low-code script is used to generate the table name of the data model table based on the table metadata, and to generate the fields of the data model table based on the attribute metadata; running the low-code script to generate the data model.3. The method according to claim 1, characterized in that a data model table is defined in the data model; wherein the standard metadata includes attribute metadata; wherein, inputting the target data into the data model based on the standard metadata to generate a physical table corresponding to the target data includes: obtaining the target data; generating N attribute instance data based on the target data and the attribute metadata; N is an integer greater than or equal to 1; inserting the N attribute instance data into the data model table according to the correspondence between the attribute metadata and the fields in the data model table to generate the physical table. 4. The method according to claim 3, characterized in that the N attribute instance data includes first attribute instance data, the attribute metadata includes first attribute metadata, the first attribute instance data is generated based on the first attribute metadata, and the first attribute metadata includes data validation rules; wherein, generating N attribute instance data based on the target data and the attribute metadata includes: validating the first attribute instance data using the data validation rules in the first attribute metadata to determine whether the first attribute instance data conforms to the validation rules. 5. The method according to claim 3, wherein the N attribute instance data includes second attribute instance data, the attribute metadata includes second attribute metadata, the second attribute instance data is generated based on the second attribute metadata, and the second attribute metadata includes encoding rules; wherein generating N attribute instance data based on the target data and the attribute metadata includes: determining that there are null values ​​in the second attribute instance data; encoding the null values ​​in the second attribute instance data according to the encoding rules in the second attribute metadata to complete the second attribute instance data. 6. The method according to claim 1, wherein the method further includes: modifying the standard metadata in response to a metadata modification instruction to obtain modified standard metadata; modifying the physical table based on the modified standard metadata. 7. The method according to claim 1, wherein creating standard metadata for the target data includes: displaying a metadata addition interface; defining the standard metadata by dragging or filling in the data addition interface. 8. A data management device, characterized in that it comprises: a metadata creation module for creating standard metadata for target data; a data model generation module for generating a data model of the target data based on the standard metadata; and a physical table generation module for inputting the target data into the data model based on the standard metadata to generate a physical table corresponding to the target data.9. An electronic device, characterized in that it comprises: a memory; and a processor coupled to the memory, the processor being configured to perform a data management method as claimed in any one of claims 1-7 based on computer program instructions stored in the memory. 10. A computer-readable storage medium storing computer program instructions, characterized in that the computer program instructions, when executed by a processor, implement the data management method as claimed in any one of claims 1-7. 11. A computer program product comprising computer program instructions stored in a computer-readable storage medium, characterized in that the computer program instructions, when executed by a processor, implement the method as claimed in any one of claims 1-7. Claims 2 / 2 Page 3 CN 121092640 A Data Management Method, Apparatus, Device and Computer Program Product Technical Field

[0001] This disclosure relates to the field of computer and Internet technology, and more particularly to a data management method, apparatus, electronic device, computer-readable storage medium and computer program product. Background Art

[0002] This section is intended to provide background or context for embodiments of the present disclosure set forth in the claims. The description herein is not an admission of prior art by virtue of its inclusion in this section.

[0003] Data management, such as Master Data Management (MDM), is the core of enterprise data governance, used to uniformly manage key business data (such as customers, products, suppliers, etc.).

[0004] Traditional data management platforms usually require complex code development and configuration, and have the following problems: High development cost: requires professional developers to write a large amount of code, and the development cycle is long; Poor flexibility: when business needs change, modifying and expanding the data model requires redevelopment; Difficult maintenance: high code complexity, high maintenance and upgrade costs; Poor user experience: non-technical personnel find it difficult to participate in data configuration and management. Summary of the Invention

[0005] The purpose of this disclosure is to provide a data management method, apparatus, electronic device, computer-readable storage medium, and computer program product that can improve data management efficiency and reduce data management difficulty.

[0006] Other features and advantages of this disclosure will become apparent from the following detailed description, or may be learned in part by practice of this disclosure.

[0007] This disclosure provides a data management method, including: creating standard metadata for target data; generating a data model of the target data based on the standard metadata; and inputting the target data into the data model based on the standard metadata to generate a physical table corresponding to the target data.

[0008] In some embodiments, a data model table is defined in the data model; the standard metadata includes table metadata and attribute metadata, wherein the table metadata is data used to describe the physical table; the attribute metadata is data used to describe the fields in the physical table; wherein generating a data model for the target data based on the standard metadata includes: a low-code generator generating a low-code script based on the standard metadata; wherein the low-code script is used to generate the table name of the data model table based on the table metadata, and to generate the fields of the data model table based on the attribute metadata; running the low-code script to generate the data model.

[0009] In some embodiments, a data model table is defined in the data model; wherein the standard metadata includes attribute metadata; wherein entering the target data into the data model based on the standard metadata to generate a physical table corresponding to the target data includes: obtaining the target data; generating N attribute instance data based on the target data and the attribute metadata; N is an integer greater than or equal to 1; inserting the N attribute instance data into the data model table according to the correspondence between the attribute metadata and the fields in the data model table to generate the physical table.

[0010] In some embodiments, the N attribute instance data includes first attribute instance data, the attribute metadata includes first attribute metadata, the first attribute instance data is generated based on the first attribute metadata, and the attribute metadata includes data validation rules; wherein, generating N attribute instance data based on the target data and the attribute metadata includes: validating the first attribute instance data using the data validation rules in the first attribute metadata to determine whether the first attribute instance data conforms to the validation rules.

[0011] In some embodiments, the N attribute instance data includes second attribute instance data, the attribute metadata includes second attribute metadata, the second attribute instance data is generated based on the second attribute metadata, and the second attribute metadata includes encoding rules; wherein, generating N attribute instance data based on the target data and the attribute metadata includes: determining that there are null values ​​in the second attribute instance data; encoding the null values ​​in the second attribute instance data according to the encoding rules in the second attribute metadata to fill in the null values ​​in the second attribute instance data.

[0012] In some embodiments, the method further includes: modifying the standard metadata in response to a metadata modification instruction to obtain modified standard metadata; and modifying the physical table based on the modified standard metadata.

[0013] In some embodiments, creating standard metadata for target data includes: displaying a metadata addition interface; defining the standard metadata by dragging or filling in the data addition interface.

[0014] This disclosure provides a data management device, including: a metadata creation module, a data model generation module, and a physical table generation module.

[0015] Wherein, the metadata creation module is used to create standard metadata for target data; the data model generation module can be used to generate a data model of the target data based on the standard metadata; the physical table generation module can be used to input the target data into the data model based on the standard metadata to generate a physical table corresponding to the target data.

[0016] This disclosure proposes an electronic device, which includes: a memory and a processor; the memory is used to store computer program instructions; the processor calls the computer program instructions stored in the memory to implement the data management method described above.

[0017] This disclosure proposes a computer-readable storage medium storing computer program instructions thereon to implement the data management method described above.

[0018] This disclosure provides a computer program product or computer program, which includes computer program instructions stored in a computer-readable storage medium. The computer program instructions are read from the computer-readable storage medium, and the processor executes the computer program instructions to implement the above-described data management method.

[0019] The data management method, apparatus, electronic device, computer-readable storage medium, and computer program product provided by this disclosure effectively improve the standardization and automation level of data management by establishing standard metadata and automatically generating corresponding data models and physical tables, reducing the complexity of manual configuration and development and maintenance costs.

[0020] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this disclosure. Brief Description of the Drawings

[0021] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. Obviously, the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without creative effort.

[0022] FIG1 illustrates a scenario applicable to the data management method or data management device of the present disclosure, page 2 / 13, CN 121092640 A.

[0023] FIG2 is a flowchart illustrating a data management method according to an exemplary embodiment.

[0024] FIG3 is a flowchart illustrating a data model generation method according to an exemplary embodiment.

[0025] FIG4 is a flowchart illustrating a physical table generation method according to an exemplary embodiment.

[0026] FIG5 is a structural schematic diagram illustrating a data management method according to an exemplary embodiment.

[0027] FIG6 is a logical diagram illustrating the implementation process of generating a model based on metadata according to an exemplary embodiment.

[0028] FIG7 is a logical diagram illustrating the specific process of compliance of master data entry according to an exemplary embodiment.

[0029] FIG8 is a logical diagram illustrating the automatic completion of master data according to encoding rules according to an exemplary embodiment.

[0030] FIG9 is a logical diagram illustrating the process of converting dynamic attributes of master data to physical tables according to an exemplary embodiment.

[0031] FIG10 is a block diagram illustrating a data management device according to an exemplary embodiment.

[0032] FIG11 shows a structural schematic diagram of an electronic device suitable for implementing embodiments of the present disclosure. Detailed Description

[0033] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The same reference numerals in the figures denote the same or similar parts, and therefore repeated descriptions of them will be omitted.

[0034] Those skilled in the art will recognize that embodiments of this disclosure can be a system, apparatus, device, method, or computer program product. Therefore, this disclosure can be embodied in the following forms: entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0035] The features, structures, or characteristics described in this disclosure can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a full understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced with one or more specific details omitted, or other methods, components, apparatuses, steps, etc., can be employed. In other cases, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring aspects of this disclosure.

[0036] In this embodiment of the disclosure, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works together with other related parts to achieve a predetermined goal, and can be implemented wholly or partially by using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units.Furthermore, each module or unit can be part of a whole module or unit that includes the functionality of that module or unit.

[0037] The accompanying drawings are merely illustrative diagrams of this disclosure, and the same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, or in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0038] The flowcharts shown in the accompanying drawings are merely illustrative examples and do not necessarily include all contents and steps, nor do they necessarily have to be performed in the order described. For example, some steps can be broken down, while some steps can be combined or partially combined, and the actual order of execution may change depending on the actual situation.

[0039] In the description of this disclosure, unless otherwise stated, " / " means "or", for example, A / B can mean A or B. The term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, "at least one" refers to one or more, and "multiple" refers to two or more. The terms "first," "second," etc., do not limit the quantity or execution order, and are not necessarily different. The terms "comprising," "including," and "having" are used to indicate an open-ended meaning of inclusion and refer to the existence of additional elements / components / etc. besides those listed.

[0040] Embodiments of this disclosure can be implemented by a terminal and / or a server. The terminal can obtain data from a computer device and display that data. The computer device can interact with the terminal, and can be a server where the application resides, or it can belong to the terminal (i.e., the terminal's backend), etc., without limitation.

[0041] The terminal can be a mobile phone or a laptop, or a playback device in a vehicle, etc., without limitation. The terminal can be considered as a playback device in a vehicle, and the terminal can display target applications, etc. The terminal is only one of the examples, and the terminal in this disclosure is not limited to the examples. The target application in this disclosure can be any application that can display multimedia information.

[0042] It is understood that the terminal mentioned in the embodiments of this disclosure can be a computer device, and the computer device in the embodiments of this disclosure includes, but is not limited to, a terminal or a server.In other words, a computer device can be a server or a terminal, or a system composed of servers and terminals. The terminal mentioned above can be an electronic device, including but not limited to mobile phones, tablets, desktop computers, laptops, handheld computers, in-vehicle devices, augmented reality / virtual reality (AR / VR) devices, head-mounted displays, smart TVs, wearable devices, smart speakers, digital cameras, webcams, and other mobile internet devices (MIDs) with network access capabilities, or terminals in scenarios such as trains, ships, and flights.

[0043] The server mentioned above can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, vehicle-to-everything (V2X) communication, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0044] Optionally, the data involved in the embodiments of this disclosure can be stored in a computer device, or the data can be stored based on cloud storage technology, without limitation.

[0045] In order to better understand the above-mentioned objectives, features and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, in the absence of conflict, the embodiments of this disclosure and the features in the embodiments can be combined with each other.

[0046] The following first explains some of the terms involved in the embodiments of this disclosure so that those skilled in the art can understand them.

[0047] Metadata is data about data, used to provide background information, structure, attributes and management methods of data, making data easier to understand, manage and use.

[0048] Low-code is a software development method that allows developers to automatically generate interfaces and quickly build applications in a certain way, thereby reducing the workload of traditional programming.

[0049] The foregoing has introduced some nouns and concepts involved in the embodiments of this disclosure. The following introduces the technical features involved in the embodiments of this disclosure. Specification 4 / 13 pages 7 CN 121092640 A

[0050] The exemplary embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0051] FIG1 shows a schematic diagram of a scenario that can be applied to the data management method or data management device of the present disclosure.

[0052] Please refer to FIG1, which shows a schematic diagram of an implementation environment provided by an exemplary embodiment of the present disclosure.

[0053] As shown in FIG1, the system architecture 100 may include terminal devices 101, 102, and 103, a network 104, and a server 105. The network 104 is used as a medium to provide a communication link between the terminal devices 101, 102, and 103 and the server 105. The network 104 may include various connection types, such as wired or wireless communication links or fiber optic cables, etc.

[0054] Users can use the terminal devices 101, 102, and 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Among them, the terminal devices 101, 102, and 103 may be various electronic devices with displays and supporting web browsing, including but not limited to smartphones, tablets, laptops, desktop computers, wearable devices, virtual reality devices, smart home devices, etc.

[0055] The server 105 may be a server that provides various services, such as a backend management server that supports the devices operated by users using the terminal devices 101, 102, and 103. The backend management server can analyze and process the received requests and other data, and feed the processing results back to the terminal device.

[0056] The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. This disclosure does not limit this.

[0057] The server 105 can, for example, create standard metadata for the target data; the server 105 can, for example, generate a data model of the target data based on the standard metadata; the server 105 can, for example, input the target data into the data model based on the standard metadata to generate a physical table corresponding to the target data.

[0058] It should be understood that the number of terminal devices, networks and servers in Figure 1 is only illustrative. The server 105 can be a single physical server or composed of multiple servers. Depending on actual needs, it can have any number of terminal devices, networks and servers.

[0059] FIG2 is a flowchart illustrating a data management method according to an exemplary embodiment. The method provided in this disclosure can be executed by any electronic device with computing power. For example, the method can be executed by the server or terminal device in the embodiment of FIG1 above, or it can be executed by both the server and the terminal device. In the following embodiments, the server is used as the execution subject for illustration, but this disclosure is not limited thereto.

[0060] Referring to FIG2, the data management method provided in this disclosure may include the following steps.

[0061] Step S202: Create standard metadata for the target data.

[0062] The target data can be master data in enterprise management or other data; this application does not limit this.

[0063] Master data refers to core business entities that need to be shared and used consistently across multiple departments, business units, systems, and processes. Here are some typical examples of master data: material / product master data, customer master data, etc. This application does not limit the specific content of master data.

[0064] In some embodiments, metadata can be created for the target data using the following methods: displaying a metadata addition interface; defining standard metadata by dragging or filling in the data addition interface.

[0065] In some embodiments, a metadata addition interface can be displayed through a visual interface, and then standard metadata can be defined by dragging or filling in the metadata addition interface.

[0066] Specifically, metadata definition and modeling can be achieved through the following methods: providing a visual interface that supports the user manual (page 5 / 13, CN 121092640 A) in defining metadata for the master data model, including entities, attributes, relationships, etc. Supports dynamic expansion of metadata, allowing users to add or modify metadata at any time according to business needs.

[0067] Entities can be core business objects to be managed, such as target data.

[0068] Attributes can be single data items describing the characteristics or properties of an entity. They define the specific information contained in the entity. Attributes can be attribute content to be managed, corresponding to fields in the physical table.

[0069] Relationships define the business association between different entities or within the same entity. They describe how data is connected and are key to building a data model network.

[0070] In some embodiments, taking employee data as target data as an example, we can illustrate what the standard metadata of target data can include.

[0071] In some embodiments, the standard metadata can include multiple attribute metadata. As shown in Table 1, the standard metadata corresponding to employee data can include multiple attributes, such as employee ID, employee name, employee code, and employee email; each attribute can correspond to one attribute metadata (e.g., the row containing each attribute in Table 1 can be the attribute metadata corresponding to that attribute).

[0072] As shown in Table 1, the standard metadata corresponding to employee data may include metadata code number, metadata code, metadata name, business field, business name, type, length, whether nullable, encoding rules, and verification rules, etc.

[0073] In some embodiments, the metadata code and metadata name can be used to generate the table name of the physical table. There is a one-to-one correspondence between the metadata code and / or the metadata name and the table name of the physical table. That is, determining the metadata code or the metadata name can determine the corresponding physical table or the table name of the physical table.

[0074] In some embodiments, the business field can be a metadata attribute, which can correspond one-to-one with the fields in the physical table.

[0075] In some embodiments, each business field can correspond to a business name, which can be a unique identifier.

[0076] In some embodiments, the standard metadata may also include rules for restricting attributes (or fields), such as the encoding rules, verification rules and other rules in Table 1. This application does not impose any restrictions on these rules.

[0077] Table 1

[0078]

[0079] Step S204: Generate a data model of the target data based on the standard metadata.

[0080] In some embodiments, the standard metadata can be regarded as a "blueprint" or "recipe" for building a data model. A model generation engine automatically parses this blueprint and executes instructions to create a physical data structure, thereby replacing the process of manually writing SQL (Structured Query Language) scripts.

[0081] Step S206: Input the target data into the data model based on the standard metadata to generate the physical table corresponding to the target data on page 6 / 13 of the specification, 9 CN 121092640 A.

[0082] The above embodiment, by providing a visual interface to define standard metadata and automatically generating data models and physical tables based on the metadata, realizes the automation and standardization of data management, significantly reduces development costs and professional technical dependence, improves system flexibility, maintainability and business personnel participation, and effectively solves the problems of long development cycle, poor adaptability and maintenance difficulty in traditional data management methods.

[0083] Figure 3 is a flowchart of a data model generation method according to an exemplary embodiment.

[0084] In some embodiments, the data model table can be a table defined in the data model.

[0085] In some embodiments, the standard metadata includes table metadata and attribute metadata. The table metadata can be data used to describe the physical table, and the attribute metadata can be data used to describe the fields in the physical table.

[0086] Referring to Figure 3, the above data model generation method may include the following steps.

[0087] Step S302: The low-code generator generates a low-code script based on standard metadata; wherein the low-code script is used to generate the table name of the data model table based on table metadata, and to generate the fields of the data model table based on attribute metadata.

[0088] Step S304: Run the low-code script to generate the data model.

[0089] Specifically, the master data model generation can be achieved through the following process: an SQL generator (a low-code generator) can generate SQL scripts based on standard metadata; wherein, physical model table names are generated through metadata names and / or encodings in the standard metadata; relevant fields of the physical table are generated through attributes in the standard metadata, a complete physical table creation script is output, and the database is connected through a database driver to execute the generated SQL script and automatically create the physical table. See Figure 6 for a detailed process diagram of the implementation of the model generation based on metadata.

[0090] In some embodiments, the master data model can be automatically generated based on standard metadata and stored in a metadata repository.

[0091] In some embodiments, version management of the master data model can be supported, recording the historical versions of each modification.

[0092] The method provided in this embodiment automatically converts standard metadata into executable scripts through a low-code generator, and generates data models and physical table structures accordingly, realizing the automation and standardization of data model design, significantly reducing the need for manual coding, improving model construction efficiency and consistency, and supporting version management to ensure the traceability of changes and system maintainability.

[0093] FIG4 is a flowchart illustrating a physical table generation method according to an exemplary embodiment.

[0094] Referring to FIG4, the above-described physical table generation method may include the following steps.

[0095] In some embodiments, a data model table may be defined in the data model.

[0096] In some embodiments, standard metadata may include attribute metadata.

[0097] Step S402: Obtain target data.

[0098] Step S404: Generate N attribute instance data based on the target data and attribute metadata. N is an integer greater than or equal to 1.

[0099] In some embodiments, the obtained original "target data" (usually semi-structured or unstructured data records) may be parsed, cleaned, transformed, and mapped according to the rules and standards defined by the "attribute metadata" to finally generate standardized attribute instance data (i.e., neat data records) that meet the requirements of the data model.

[0100] In some embodiments, the N attribute instance data may include first attribute instance data (such as employee name data), the attribute metadata includes first attribute metadata, the first attribute instance data is generated based on the first attribute metadata, and the first attribute metadata includes data validation rules. Then the target data can be processed based on the attribute metadata to generate the first attribute instance data.In some embodiments, generating N attribute instance data based on target data and attribute metadata may include: validating the first attribute instance data using data validation rules in the first attribute metadata to determine whether the first attribute instance data conforms to the validation rules. For example, the corresponding attribute instance data can be validated using the validation rules in Table 1.

[0102] In some embodiments, the N attribute instance data includes second attribute instance data, the attribute metadata includes second attribute metadata, the second attribute instance data is generated based on the second attribute metadata, and the second attribute metadata includes encoding rules.

[0103] In some embodiments, generating N attribute instance data based on target data and attribute metadata may include: determining that there are null values ​​in the second attribute instance data; encoding the null values ​​in the second attribute instance data according to the encoding rules in the second attribute metadata to complete the second attribute instance data. For example, the corresponding null values ​​can be encoded using the encoding rules in Table 1. For example, assuming the encoding rule for the metadata name of a certain attribute is "extract the first three digits of the employee's email as the metadata name of the data", if the metadata name of the attribute is empty, then the metadata name of the high attribute can be automatically generated according to the above rule.

[0104] Step S406, according to the correspondence between the attribute metadata and the fields in the data model table, insert N attribute instance data into the data model table to generate a physical table.

[0105] In some embodiments, the physical table corresponding to the standard metadata can be found according to the mapping relationship between the metadata encoding and / or the metadata name and the table name of the physical table.

[0106] In some embodiments, the above N attribute instance data can be inserted one by one into the corresponding field position in the data model table according to the correspondence between the business fields and / or the business names in the standard metadata and the field names in the physical table to generate a physical table.

[0107] In some embodiments, the above physical table can be modified or the target data can be managed and modified by the following methods: in response to the metadata modification instruction, the standard metadata is modified to obtain the modified standard metadata, such as performing modification, deletion, addition and other operations; the physical table is modified based on the modified standard metadata.

[0108] In some embodiments, the physical table may be editable, allowing users to directly manage the physical table, such as performing modifications, deletions, and additions.

[0109] Hereinafter, this application will explain a data management method in conjunction with specific embodiments.

[0110] Hereinafter, this application will use target data as the main data as an example for explanation, but this is not a limitation.

[0111] FIG5 is a schematic diagram of the structure of a data management method according to an exemplary embodiment.

[0112] As shown in Figure 5, the above data management method may include the following steps.

[0113] 1. Metadata definition and modeling: Provide a visual interface to support users in defining metadata for the master data model, including entities, attributes, relationships, etc. Support dynamic expansion of metadata; users can add or modify metadata at any time according to business needs. As shown in Figure 5, a target data (OBJ) and N attributes (ATTR) can be defined in the metadata.

[0114] 2. Master data model generation: Automatically generate the master data model based on the user-defined metadata and store it in the metadata repository. Support version management of the master data model and record the historical version of each modification. The main function of the SQL generator is to generate SQL scripts based on the defined metadata; generate physical model table names through metadata names and codes; generate relevant fields of physical tables through metadata attributes; output a complete physical table creation script; connect to the database through the database driver; execute the generated SQL script; and automatically create physical tables. See Figure 6 for a detailed process diagram of the implementation process of generating models based on metadata. As shown in Figure 6, table names can be generated according to metadata names and / or metadata codes, and table fields can be generated according to metadata attributes (or attribute metadata). Instruction manual, page 8 / 13, CN 121092640 A

[0115] 3. Master data management function configuration: Provides a low-code configuration interface, supporting users to configure master data management functions through visual operation, including data entry, data verification, data query, data synchronization, etc. Supports configuration of data verification and data processing logic based on rule engine. The master data compliance verification module mainly verifies whether the master data fields entered in the master data management interface conform to the specifications; in the master data management interface, after clicking save, the verification center calls the rule executor according to the verification rules associated with the master data fields to determine whether the value entered in the current interface conforms to the verification rules. See Figure 7 for details: Specific process logic diagram of master data entry compliance; The master data completion module mainly automatically completes the current field value according to the encoding rules associated with the master data fields by default. See Figure 8 for details: Logic diagram of master data automatically completing data according to encoding rules.

[0116] 4. Dynamic management of master data to physical table: The master data management interface is dynamically generated based on metadata. After saving, the metadata attributes generate N attribute instance master data. The physical table conversion module obtains N attribute instance data of the current metadata instance as the dimension. According to the current metadata encoding, it locates the table corresponding to the current master data. According to the metadata encoding attribute, it corresponds to the field of the current physical table, generates an INSERT script, and writes it to the master data physical table. See Figure 9 for details: Logic diagram of dynamic attribute to physical table conversion process of master data.

[0117] This embodiment provides a method for low-code management of master data based on metadata, providing low-code management support for the entire lifecycle of master data, including data creation, data update, data archiving, data deletion, etc. The overall scheme is shown in Figure 5, a logic diagram of low-code management of master data based on metadata.

[0118] The present application will describe the above method in detail below with reference to specific embodiments.

[0119] Configuring employee metadata, the method for low-code management of employee master data based on employee metadata may specifically include the following steps.

[0120] Step 1: Based on the employee business model, enter the employee standard metadata into the system, clarify the restrictions and coding rules for each business field of the employee, as shown in Table 1.

[0121] Step 2: Enter the master data management interface, select the entered employee metadata, and automatically generate an editable page based on the standard employee metadata using low-code capabilities.

[0122] Step 3: Dynamically maintain the employee master data using the interface generated based on low-code capabilities.

[0123] Step 4: After completion, the low-code backend accepts the data and verifies the compliance of the master data entry based on the standard employee verification. Interface prompts are provided for entries that do not conform to business rules, and adjustments are made according to the business rules.

[0124] Step 5: Compliance verification. The employee email field is associated with the "email_format" verification rule (whether the data is in email format). The verification center rule executor is triggered to execute the "email_format" verification rule and verify whether the data 123@qq.com is compliant.

[0125] Step 6: Field completion. The employee code field is associated with the "staff_nbr_rule" encoding rule. The encoding rule executor is triggered to execute the "staff_nbr_rule" encoding rule and automatically generate the employee code: 1234.

[0126] Step 7: After successful verification, for business fields with encoding rules, the business field values ​​are automatically completed according to the encoding rules and saved to the master data attribute instance table, as shown in Table 2.

[0127] Table 2 Specification 9 / 13 Page 12 CN 121092640 A

[0128]

[0129] Step 8: The data entered based on the low-code master data management interface is automatically converted into physical table data (corresponding metadata staff table) according to the data converter, as shown in Table 3.

[0130] Table 3

[0131] staff_id staff_name staff_nbr staff_email 100000 Li Si 1234 123@qq.com

[0132] This embodiment provides a method for low-code management of master data based on metadata. Through dynamic configuration and visual operation of metadata, the development cost and maintenance difficulty of master data management are reduced, and the flexibility and user experience of master data management are improved.Specific objectives include: achieving low-code configuration and management of the master data model; supporting dynamic expansion and modification of metadata; providing low-code management support for the entire lifecycle of master data; and improving the flexibility and maintainability of master data management.

[0133] It should be particularly noted that each step in each embodiment of the above data management method can be mutually intersected, substituted, added, or deleted. Therefore, these reasonable permutations and combinations of data management methods should also fall within the protection scope of this disclosure, and the protection scope of this disclosure should not be limited to the above embodiments.

[0134] It should be noted that the protection scope of this application should include, but is not limited to, the specific implementation methods described in the embodiments. Any alternative solution that uses a different name but substantially performs the same function and achieves the same technical effect falls within the protection scope defined by the claims of this application.

[0135] Based on the same inventive concept, this disclosure also provides a data management device, as described in the following embodiments. Since the principle of solving the problem in this device embodiment is similar to that in the above method embodiments, the implementation of this device embodiment can refer to the implementation of the above method embodiments, and the repeated parts will not be described again.

[0136] FIG10 is a block diagram of a data management device according to an exemplary embodiment. Referring to FIG10, the data management device 1000 provided in this embodiment may include: a metadata creation module 1001, a data model generation module 1002, and a physical table generation module 1003.

[0137] Wherein, the metadata creation module 1001 can be used to create standard metadata for target data; the data model generation module 1002 can be used to generate a data model of the target data based on the standard metadata; the physical table generation module 1003 can be used to input the target data into the data model based on the standard metadata to generate a physical table corresponding to the target data.

[0138] It should be noted here that the above-mentioned metadata creation module 1001, data model generation module 1002, and physical table generation module 1003 correspond to S202 to S206 in the method embodiment. The examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in the above method embodiment. It should be noted that the above modules, as part of the device, can be executed in a computer system such as a set of computer-executable instructions.

[0139] In some embodiments, a data model table is defined in the data model; the standard metadata package specification 10 / 13 pages 13 CN 121092640 A includes table metadata and attribute metadata, wherein the table metadata is data used to describe the physical table; and the attribute metadata is data used to describe the fields in the physical table; wherein the data model generation module 1002 may include: a script generation submodule and a data model generation submodule.

[0140] The script generation submodule can be used by the low-code generator to generate a low-code script based on the standard metadata; wherein the low-code script is used to generate the table name of the data model table based on the table metadata, and to generate the fields of the data model table based on the attribute metadata; the data model generation submodule can be used to run the low-code script to generate the data model.

[0141] In some embodiments, a data model table is defined in the data model; wherein the standard metadata includes attribute metadata; wherein the physical table generation module 1003 may include: a target data acquisition submodule, an attribute instance generation submodule, and an insertion submodule.

[0142] The target data acquisition submodule can be used to acquire the target data; the attribute instance generation submodule can be used to generate N attribute instance data based on the target data and the attribute metadata; N is an integer greater than or equal to 1; the insertion submodule can be used to insert the N attribute instance data into the data model table according to the correspondence between the attribute metadata and the fields in the data model table to generate the physical table.

[0143] In some embodiments, the N attribute instance data includes first attribute instance data, the attribute metadata includes first attribute metadata, the first attribute instance data is generated based on the first attribute metadata, and the first attribute metadata includes data verification rules; wherein, the attribute instance generation submodule may include: a verification unit.

[0144] Wherein, the verification unit may be used to verify the first attribute instance data through the data verification rules in the first attribute metadata to determine whether the first attribute instance data conforms to the verification rules.

[0145] In some embodiments, the N attribute instance data includes second attribute instance data, the attribute metadata includes second attribute metadata, the second attribute instance data is generated based on the second attribute metadata, and the second attribute metadata includes encoding rules; wherein, the attribute instance generation submodule may include: a null value determination unit and an encoding unit.

[0146] Wherein, the null value determination unit may be used to determine that there are null values ​​in the second attribute instance data; the encoding unit may be used to encode the null values ​​in the second attribute instance data according to the encoding rules in the second attribute metadata to complete the second attribute instance data.

[0147] In some embodiments, the data management device 1000 may further include: a modification instruction acquisition model and a modification module.

[0148] The modification instruction acquisition module can be used to modify the standard metadata in response to the metadata modification instruction to obtain the modified standard metadata; the modification module can be used to modify the physical table based on the modified standard metadata.

[0149] In some embodiments, creating standard metadata for target data includes: displaying a metadata addition interface; defining the standard metadata by dragging or filling in the data addition interface.

[0150] Since the functions of the device 1000 have been described in detail in their corresponding method embodiments, this disclosure will not repeat them here.

[0151] The modules and / or sub-modules and / or units involved in the embodiments of this disclosure can be implemented by software or by hardware. The described modules and / or sub-modules and / or units can also be disposed in a processor. Wherein, the names of these modules and / or sub-modules and / or units do not constitute a limitation on the module and / or sub-module and / or unit itself in some cases.

[0152] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functions and operations of possible implementations of systems, methods and computer programs according to various embodiments of this disclosure. In this respect, each block in the flowchart or block diagram may represent a portion of a module or program segment, which contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the figures. For example, two blocks shown consecutively may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and combinations of blocks in the block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer program instructions.

[0153] Furthermore, the above figures are merely illustrative illustrations of the processes included in the methods according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0154] FIG11 shows a schematic diagram of the structure of an electronic device suitable for implementing embodiments of the present disclosure. It should be noted that the electronic device 1100 shown in FIG11 is only an example and should not impose any limitation on the functionality and scope of use of the embodiments of this disclosure.

[0155] As shown in FIG11, the electronic device 1100 includes a central processing unit (CPU) 1101, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1102 or a program loaded from a storage portion 1108 into a random access memory (RAM) 1103. Various programs and data required for the operation of the electronic device 1100 are also stored in the RAM 1103.CPU 1101, ROM 1102, and RAM 1103 are interconnected via bus 1104. Input / output (I / O) interface 1105 is also connected to bus 1104.

[0156] The following components are connected to I / O interface 1105: input section 1106 including keyboard, mouse, etc.; output section 1107 including cathode ray tube (CRT), liquid crystal display (LCD), etc., and speaker, etc.; storage section 1108 including hard disk, etc.; and communication section 1109 including network interface card, such as LAN card, modem, etc. Communication section 1109 performs communication processing via a network such as the Internet. Drive 1110 is also connected to I / O interface 1105 as needed. Removable media 1111, such as disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 1110 as needed so that computer programs read from there are installed into storage section 1108 as needed.

[0157] In particular, according to embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing computer program instructions for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1109, and / or installed from removable medium 1111. When the computer program is executed by central processing unit (CPU) 1101, it performs the functions defined in the system of the present disclosure.

[0158] It should be noted that the computer-readable storage medium shown in the present disclosure can be a computer-readable signal medium or a computer-readable storage medium or any combination thereof. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure (pages 12 / 13, CN 121092640 A), a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable computer program instructions.The transmitted data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable storage medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The computer program instructions contained on the computer-readable storage medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0159] As another aspect, this disclosure also provides a computer-readable storage medium, which can be included in the device described in the above embodiments; or it can exist independently and not assembled into the device. The computer-readable storage medium carries one or more programs, which, when executed by the device, enable the device to perform functions including: creating standard metadata for target data; generating a data model of the target data based on the standard metadata; and inputting the target data into the data model based on the standard metadata to generate a physical table corresponding to the target data.

[0160] According to one aspect of this disclosure, a computer program product or computer program is provided, the computer program product or computer program including computer program instructions stored in a computer-readable storage medium. The computer program instructions are read from the computer-readable storage medium, and a processor executes the computer program instructions to implement the methods provided in various optional implementations of the above embodiments.

[0161] Through the above description of the embodiments, those skilled in the art will readily understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions of the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several computer program instructions to cause an electronic device (such as a server or terminal device, etc.) to execute the methods according to the embodiments of this disclosure.

[0162] Other embodiments of this disclosure will be readily conceived by those skilled in the art upon consideration of the specification and practice disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

[0163] It should be understood that this disclosure is not limited to the detailed structures, drawing arrangements or implementation methods shown herein, but rather is intended to cover various modifications and equivalent arrangements contained within the spirit and scope of the appended claims.Instruction Manual 13 / 13 Page 16 CN 121092640 A Figure 1 Figure 2 Instruction Manual Appendix 1 / 7 Page 17 CN 121092640 A Figure 3 Figure 4 Instruction Manual Appendix 2 / 7 Page 18 CN 121092640 A Figure 5 Figure 6 Instruction Manual Appendix 3 / 7 Page 19 CN 121092640 A Figure 7 Instruction Manual Appendix 4 / 7 Page 20 CN 121092640 A Figure 8 Instruction Manual Appendix 5 / 7 Page 21 CN 121092640 A Figure 9 Figure 10 Instruction Manual Appendix 6 / 7 Page 22 CN 121092640 A Figure 11 Instruction Manual Appendix 7 / 7 Page 23 CN 121092640 A Data Management Method, Apparatus, Device, and Computer Program Product The present disclosure provides a data management method, an apparatus, a device, and a computer program product, relating to the fields of computer and Internet technologies. The data management method includes: creating standard metadata for target data; generating a data model of the target data based on the standard metadata; and inputting the target data into the data model based on the standard metadata to generate a physical table corresponding to the target data. Embodiments of the present disclosure can improve the management efficiency of target data. Abstract.

Claims

1. A data management method, characterized in that, include: Create standard metadata for the target data; A data model for the target data is generated based on the standard metadata. The target data is entered into the data model based on the standard metadata to generate the physical table corresponding to the target data.

2. The method according to claim 1, characterized in that, The data model defines a data model table; the standard metadata includes table metadata and attribute metadata, wherein the table metadata is data used to describe the physical table; The attribute metadata is data used to describe the fields in the physical table; wherein, the data model for generating the target data based on the standard metadata includes: The low-code generator generates a low-code script based on the standard metadata; wherein the low-code script is used to generate the table name of the data model table based on the table metadata, and to generate the fields of the data model table based on the attribute metadata; Run the low-code script to generate the data model.

3. The method according to claim 1, characterized in that, The data model defines a data model table; the standard metadata includes attribute metadata; and the process of inputting the target data into the data model based on the standard metadata to generate a physical table corresponding to the target data includes: Obtain the target data; Based on the target data and the attribute metadata, generate N attribute instance data; N is an integer greater than or equal to 1; According to the correspondence between the attribute metadata and the fields in the data model table, the N attribute instance data are inserted into the data model table to generate the physical table.

4. The method according to claim 3, characterized in that, The N attribute instance data include first attribute instance data, and the attribute metadata includes first attribute metadata. The first attribute instance data is generated based on the first attribute metadata, and the first attribute metadata includes data validation rules. Specifically, generating N attribute instance data based on the target data and the attribute metadata includes: The data of the first attribute instance is validated using the data validation rules in the first attribute metadata to determine whether the data of the first attribute instance conforms to the validation rules.

5. The method according to claim 3, characterized in that, The N attribute instance data include second attribute instance data, the attribute metadata includes second attribute metadata, the second attribute instance data is generated based on the second attribute metadata, and the second attribute metadata includes encoding rules; wherein, generating N attribute instance data based on the target data and the attribute metadata includes: It has been determined that a null value exists in the instance data of the second attribute; Null values ​​in the second attribute instance data are encoded according to the encoding rules in the second attribute metadata to complete the second attribute instance data.

6. The method according to claim 1, characterized in that, The method further includes: In response to a metadata modification instruction, the standard metadata is modified to obtain the modified standard metadata; Modify the physical table based on the modified standard metadata.

7. The method according to claim 1, characterized in that, Create standard metadata for the target data, including: Displays the new metadata interface; On the data addition interface, the standard metadata can be defined by dragging and dropping or filling in.

8. A data management device, characterized in that, include: The metadata creation module is used to create standard metadata for target data; The data model generation module is used to generate a data model of the target data based on the standard metadata. The physical table generation module is used to input the target data into the data model based on the standard metadata in order to generate the physical table corresponding to the target data.

9. An electronic device, characterized in that, include: Memory; as well as A processor coupled to the memory, the processor being used to execute the data management method as described in any one of claims 1-7 based on computer program instructions stored in the memory.

10. A computer-readable storage medium storing computer program instructions thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the data management method as described in any one of claims 1-7.

11. A computer program product comprising computer program instructions stored in a computer-readable storage medium, characterized in that, When the computer program instructions are executed by the processor, they implement the method of any one of claims 1-7.

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