A data model management method and device, electronic equipment and storage medium

Abstract

The application discloses a data model management method and device, electronic equipment and storage medium, comprising: obtaining target database information; determining corresponding target data mapping and target data definition according to the target database information, the target data definition comprising data agreement and data element; generating corresponding target data model according to the target data mapping and the target data definition; dynamically managing the target data model, the dynamic management comprising dynamic updating of the target data mapping and the target data definition. The application can structurally manage data models, avoid problems such as unclear data model structure, non-uniform fields and incapability of supporting multiple databases, realize efficient management of data models, improve the efficiency and dynamic adaptability of data model management, and can be widely applied in the technical field of database systems.

Description

Technical Field

[0001] This application relates to the field of database system technology, and in particular to a data model management method, apparatus, electronic device and storage medium. Background Technology

[0002] In data-driven business scenarios, data model management is crucial for ensuring data consistency, flexibility, and cross-system collaboration. However, existing technologies still have significant shortcomings in data model management, mainly manifested in database compatibility limitations, lack of field standardization, and insufficient dynamic adaptability. These limitations restrict the efficiency and scalability of enterprise data governance, as detailed below:

[0003] 1) Database compatibility limitations: The data model is only designed for a single database type, and cannot achieve "design once, adapt to multiple databases";

[0004] 2) Insufficient dynamic adaptability: It only supports basic single-table CRUD operations, which cannot meet the needs of complex business scenarios such as multi-level table management and transaction management;

[0005] 3) Lack of field standardization: There is a risk that the same business field may have inconsistent attribute definitions such as naming and length in different tables, and there is a lack of a unified management mechanism for cross-table fields.

[0006] Therefore, the above technical problems urgently need to be solved. Summary of the Invention

[0007] The main objective of this application is to provide a data model management method, apparatus, electronic device, and storage medium that can realize structured management of data models and improve the efficiency and dynamic adaptability of data model management.

[0008] On one hand, embodiments of this application propose a data model management method, the method comprising:

[0009] Obtain target database information;

[0010] Based on the target database information, the corresponding target data mapping and target data definition are determined, wherein the target data definition includes data conventions and data elements;

[0011] Based on the target data mapping and the target data definition, a corresponding target data model is generated;

[0012] The target data model is dynamically managed, and the dynamic management includes the dynamic updating of the target data mapping and the target data definition.

[0013] In some embodiments, determining the corresponding target data mapping and target data definition based on the target database information includes:

[0014] Obtain multiple preset data mappings and the database types corresponding to each preset data mapping;

[0015] Based on the target database information, determine the corresponding target database type and target database identification information;

[0016] Based on the database type corresponding to each of the preset data mappings, determine the target data mapping that matches the target database type from among the multiple preset data mappings;

[0017] The target data definition is determined based on the target database identification information.

[0018] In some embodiments, determining the target data definition based on the target database identification information specifically includes:

[0019] Parse the target database identification information to determine multiple data items and the data attributes corresponding to each data item;

[0020] Based on the data attributes corresponding to the data items, establish data element items corresponding to each data item, as well as a set of data element attributes and data processing rules corresponding to each data element item;

[0021] Based on the set of data processing rules corresponding to each data element item, the multiple data element items are divided to determine multiple data element sets and a shared set of data processing rules corresponding to each data element set;

[0022] Establish data convention items corresponding to each of the data element sets, and determine the data convention attributes corresponding to the data convention items based on the shared data processing rule set corresponding to the data element sets.

[0023] For each data element item, a target data element set corresponding to the data element item is determined from multiple data element sets, and the data convention item corresponding to the target data element set is associated with the data element item.

[0024] In some embodiments, generating a corresponding target data model based on the target data mapping and the target data definition specifically includes:

[0025] Analyze the data element attributes corresponding to each data element item to determine the association attributes between data element items;

[0026] The target data is mapped and associated with each of the data element items;

[0027] The target data model is generated based on the target data mapping, the data element items associated with the target data mapping and the data convention items, the association attribute, and the data convention items.

[0028] In some embodiments, the dynamic management of the target data model specifically includes:

[0029] In response to a dynamic update operation on the target data model information, the updated target data model information is determined, wherein the target data model information includes the target data mapping and the target data definition, and the update operation includes information modification, information deletion and information addition.

[0030] The target data model is dynamically updated based on the updated target data model information.

[0031] In some embodiments, the method further includes:

[0032] Based on the target data model, determine the corresponding database table structure information;

[0033] The database table structure information is synchronously transmitted to the corresponding target database through the data interface.

[0034] In some embodiments, the step of dividing the multiple data element items according to the data processing rule set corresponding to each data element item, and determining multiple data element sets and a shared data processing rule set corresponding to each data element set, specifically includes:

[0035] Mark all the data element items as undivided, and obtain any data element item as the current judgment item;

[0036] The set of data processing rules corresponding to the current judgment item is obtained as the current rule set;

[0037] Based on the current set of rules, construct a corresponding set of data elements, and use the current set of rules as the shared data processing rule set corresponding to the set of data elements.

[0038] Based on the data processing rule set corresponding to each of the remaining data element items, a consistency judgment is made, and several shared data element items are determined from the multiple data element items, wherein the shared data element items are the data element items whose data processing rule set is consistent with the current rule set;

[0039] Mark each of the shared data element items and the current judgment item as having been divided and add them to the data element set;

[0040] Determine whether there are any undivided data element items, wherein the undivided data element items are the data element items in the undivided state;

[0041] When any of the undivided data element items exists, obtain any of the undivided data element items as the current judgment item, and then return to the step of obtaining the data processing rule set corresponding to the current judgment item as the current rule set, until there are no more undivided data element items.

[0042] When there is no undivided data element item, determine the set of shared data processing rules corresponding to each set of data elements, and the several data element items contained in each set of data elements.

[0043] On the other hand, embodiments of this application propose a data model management device, the device comprising:

[0044] The first module is used to obtain target database information;

[0045] The second module is used to determine the corresponding target data mapping and target data definition based on the target database information, wherein the target data definition includes data conventions and data elements;

[0046] The third module is used to generate a corresponding target data model based on the target data mapping and the target data definition;

[0047] The fourth module is used to dynamically manage the target data model, and the dynamic management includes the dynamic updating of the target data mapping and the target data definition.

[0048] On the other hand, embodiments of this application propose an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the data model management method described above.

[0049] On the other hand, embodiments of this application propose a computer-readable storage medium storing a computer program that, when executed by a processor, implements the data model management method described above.

[0050] The embodiments of this application include at least the following beneficial effects: The data model management method, apparatus, electronic device, and storage medium provided in this application acquire target database information, determine the corresponding target data mapping and target data definition based on the target database information, generate the corresponding target data model based on the target data mapping and target data definition, and dynamically manage the target data model. This application can perform structured management of data models, avoiding problems such as unclear data model structure, inconsistent fields, and inability to support multiple databases, achieving efficient management of data models and improving the efficiency and dynamic adaptability of data model management. Attached Figure Description

[0051] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 This is a flowchart of a data model management method provided in an embodiment of this application;

[0054] Figure 2 This is a schematic diagram of the structure of a data model management device provided in an embodiment of this application;

[0055] Figure 3 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0057] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0058] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0060] Reference Figure 1 , Figure 1 This is an optional flowchart of a data model management method provided in an embodiment of this application. The method may include, but is not limited to, steps S101 to S104:

[0061] Step S101: Obtain target database information;

[0062] Step S102: Based on the target database information, determine the corresponding target data mapping and target data definition. The target data definition includes data conventions and data elements.

[0063] Step S103: Generate the corresponding target data model based on the target data mapping and target data definition;

[0064] Step S104: Dynamically manage the target data model. Dynamic management includes dynamic updating of target data mapping and target data definition.

[0065] In some embodiments, the target database information may include, but is not limited to, database metadata information, database identification information, and database connection information. The database identification information may include, but is not limited to, basic database identifiers (including database name and instance name, etc.), database object identifiers (including table name, view name, index name, and trigger name, etc.), column-level identifiers (including field name, primary key identifier, and foreign key identifier, etc.), and other identifiers (including constraint name, sequence name, and synonym name, etc.). The database metadata information may include, but is not limited to, database technical attribute information, system configuration information, data model classification information, and application scenario information. The database connection information may include, but is not limited to, basic connection parameters, authentication information, database name, connection configuration options, and connection string, etc.

[0066] Based on the target database information, a data structure consisting of data mappings, data conventions, and data elements is constructed. Based on this data structure, a data model is generated. Optionally, the data mappings and data conventions have a one-to-many relationship, that is, multiple data conventions are associated with one data mapping. The data conventions and data elements also have a one-to-many or one-to-one relationship, that is, one data convention is associated with one or more data elements.

[0067] In some embodiments, step S102 may include, but is not limited to, steps S201 to S204:

[0068] Step S201: Obtain multiple preset data mappings and the database type corresponding to each preset data mapping;

[0069] Step S202: Determine the corresponding target database type and target database identification information based on the target database information;

[0070] Step S203: Based on the database type corresponding to each preset data mapping, determine the target data mapping that matches the target database type from multiple preset data mappings;

[0071] Step S204: Determine the target data definition based on the target database identification information.

[0072] In some embodiments, by maintaining data mapping compatible with database types and program data types, the data mapping enables the conversion, migration and integration of stored data in the target database, so that the target database can accurately store relevant data and avoid data truncation, precision loss or logical errors caused by type mismatch.

[0073] Optionally, the preset data mapping includes information such as mapping item name, database type, and program data type. Program data type refers to the data type used in database program objects such as stored procedures, functions, and triggers. The mapping item name can be set by the user. The database type is determined according to the specification definition of the database type, and the program data type is determined according to the specification definition of the program data type.

[0074] In step S203 of some embodiments, multiple preset data maps are stored in a mapping database. If there is no target data map among the multiple preset data maps that matches the target database type, the target program data type and the target database type are determined according to the target database information. A corresponding target data map is generated according to the target program data type and the target database type, and the target data map is added as a new preset data map and stored synchronously in the mapping database.

[0075] In some embodiments, step S204 may include, but is not limited to, steps S301 to S305:

[0076] Step S301: Parse the target database identification information to determine multiple data items and the data attributes corresponding to each data item;

[0077] Step S302: Based on the data attributes corresponding to the data items, establish the data element items corresponding to each data item, as well as the data element attributes and data processing rule set corresponding to each data element item;

[0078] Step S303: Based on the data processing rule set corresponding to each data element item, divide the multiple data element items to determine multiple data element sets and the shared data processing rule set corresponding to each data element set;

[0079] Step S304: Establish data convention items corresponding to each data element set, and determine the data convention attributes corresponding to the data convention items based on the shared data processing rule set corresponding to the data element set.

[0080] Step S305: For each data element item, determine the target data element set corresponding to the data element item from multiple data element sets, and associate the data convention item corresponding to the target data element set with the data element item.

[0081] In some embodiments, a data contract is a set of rules and constraints for the use of data, defining the rules and constraints of the data, while a data element is a standardized definition of data, defining the structure and semantics of the data. Different data elements can share the same data contract.

[0082] Specifically, a data convention library is constructed to correspond to the data conventions, and all data convention items are stored in the data convention library. A data element library is constructed to correspond to the data elements, and all data elements are stored in the data element library. Data convention items are used to constrain several related data element items and maintain the common fields of data element items. Data convention items may include, but are not limited to, data convention attribute information such as data quality rules, business logic constraints, security policies, timeliness rules, convention item names, data types, data lengths, data decimal places, and data descriptions. Data element items may include, but are not limited to, data element attribute information such as field names, field descriptions, related convention item names, field descriptions, field types, field lengths, field decimal places, data element types, business types, default control types, mapping item names, and association relationship attributes (including related data elements and association relationship definitions).

[0083] In some embodiments, the target database identification information is parsed to determine multiple data items in the target database and the data attributes corresponding to each data item. Based on the data attributes of the data items, the data element attributes and data processing rule set of the corresponding data element item are determined. Optionally, structural attributes (including field name, data type, and field length, etc.), semantic attributes (including field description and foreign key relationships, etc.) and value domain features (such as enumerated value list, etc.) contained in the data attributes of the data items are extracted to determine the data element attribute information of the data element item. Data quality attributes (including null value rate, uniqueness, and value distribution), business rule attributes (including format mode and timeliness, etc.) and security and compliance attributes (including sensitive data marking and data lineage, etc.) contained in the data attributes are extracted to determine the data processing rule set corresponding to the data element item.

[0084] In step S305 of some embodiments, for example, assuming there are data element items A to D and data element sets 1 to 3, data element item A belongs to data element set 1, data element item B belongs to data element set 2, and data element items C and D belong to data element set 3, the data convention item 1 corresponding to data element set 1 is obtained, and data convention item 1 is the target data convention item of data element item A. Data convention item 1 is associated with data element item A. Similarly, the data convention item 2 corresponding to data element set 2 is obtained, and data convention item 2 is the target data convention item of data element item B. Data convention item 2 is associated with data element item B, and so on.

[0085] In some embodiments, step S303 may include, but is not limited to, steps S401 to S408:

[0086] Step S401: Mark all data element items as undivided and obtain any data element item as the current judgment item;

[0087] Step S402: Obtain the set of data processing rules corresponding to the current judgment item as the current rule set;

[0088] Step S403: Based on the current rule set, construct the corresponding data element set, and use the current rule set as the shared data processing rule set corresponding to the data element set;

[0089] Step S404: Based on the data processing rule set corresponding to each of the remaining data element items, perform a consistency judgment and determine several shared data element items from multiple data element items. The shared data element items are data element items whose data processing rule set is consistent with the current rule set.

[0090] Step S405: Mark each shared data element item and the current judgment item as having been divided and add them to the data element set;

[0091] Step S406: Determine whether there are any undivided data element items. Undivided data element items are data element items that are in an undivided state.

[0092] Step S407: When any undivided data element item exists, obtain any undivided data element item as the current judgment item, and then return to step S402 until there is no undivided data element item.

[0093] Step S408: When there is no undivided data element item, determine the set of shared data processing rules corresponding to each data element set, and the number of data element items contained in each data element set.

[0094] In some embodiments, optionally, assuming there are data element items A to E, data element item A is taken as the current judgment item, and the data processing rule set GA of data element item A is obtained as the current rule set. The data element set 1 corresponding to the data processing rule set GA is then used. For the data processing rule sets corresponding to the remaining data element items, a consistency judgment is performed. It is determined that the data processing rule sets of data element items B and D are consistent with the data processing rule set GA. Therefore, data element items A, B, and D are marked as partitioned and added to data element set 1. The data processing rule set GA is used as the shared data processing rule set of data element set 1. Then, it is determined that the unpartitioned data element items include... For data element item C and data element item E, either data element item C or data element item E is selected as the current judgment item. The above steps are repeated until there are no undivided data element items. Finally, the shared data processing rule set corresponding to each data element set is determined, as well as the number of data element items contained in each data element set. For example, the shared data processing rule set GA corresponds to data element set 1, which includes data element item A, data element item B, and data element item D. The shared data processing rule set GC corresponds to data element set 2, which includes data element item C. The shared data processing rule set GE corresponds to data element set 3, which includes data element item E.

[0095] In some embodiments, step S103 may include, but is not limited to, steps S501 to S503:

[0096] Step S501: parse the data element attributes corresponding to each data element item and determine the association attributes between data element items;

[0097] Step S502: Map the target data and associate it with each data element item;

[0098] Step S503: Generate the target data model based on the target data mapping, the associated target data mapping and the data convention items, the associated relationship attributes and the data convention items.

[0099] In some embodiments, the data element attributes corresponding to each data element item are parsed to determine the association between data element items, and the association relationship attributes between data element items are determined based on the association between data element items, wherein the association relationship is defined through foreign key references or business logic dependencies.

[0100] Then, the target data is mapped and associated with each data element item. Combining the data conventions associated with each data element item and the association attributes between data element items, the target data model is generated.

[0101] In step S104 of some embodiments, in response to the dynamic update operation of the target data model information, the updated target data model information is determined, and the target data model is dynamically updated according to the updated target data model information. The target data model information includes target data mapping and target data definition. The update operation includes information modification, information deletion and information addition. Each update operation generates a corresponding update record script, which is added to the target data model information to achieve traceability of model updates.

[0102] Specifically, by dynamically updating the target data mapping, the mapping information associated with each data element item in the target data model is updated synchronously. By dynamically updating the data convention items, the convention item information contained in each data element item associated with the data convention item in the target data model is updated synchronously. By dynamically updating the data element items, the data element attribute information of the data element item in the target data model is updated synchronously. The dynamic update of the target data mapping enables the target data model to be compatible with multiple different databases, rather than just adapting to a single database, thus improving the dynamic adaptability of data model management.

[0103] In some embodiments, the above method may further include steps S601 to S602:

[0104] Step S601: Determine the corresponding database table structure information based on the target data model;

[0105] In step S602, the database table structure information is synchronously transmitted to the corresponding target database through the data interface.

[0106] In some embodiments, based on the target data model, corresponding database table structure information is generated; based on the target database information, target database connection information is determined; based on the target database connection information, the target database is connected; the database table structure information is transmitted to the target database; and then, the target database generates multiple corresponding database tables based on the database table structure information.

[0107] In some embodiments, the above method may further include steps S701 to S702:

[0108] Step S701: Obtain the preset code template;

[0109] Step S702: Based on the target data model information, populate the code template with data to generate the corresponding data model code.

[0110] In some embodiments, a code generation tool is used to generate data model code corresponding to the target data model information based on a pre-configured code template. The data model code is then exported or stored to facilitate the synchronization of the target data model to other environments besides the model development environment, including isolated technical environments such as testing, pre-production, production, and disaster recovery environments.

[0111] Reference Figure 2 , Figure 2 This is an optional structural diagram of a data model management device provided in an embodiment of this application. The device is used to implement the aforementioned data model management method and may include:

[0112] The first module is used to obtain target database information;

[0113] The second module is used to determine the corresponding target data mapping and target data definition based on the target database information. The target data definition includes data conventions and data elements.

[0114] The third module is used to generate the corresponding target data model based on the target data mapping and target data definition;

[0115] The fourth module is used for dynamic management of the target data model, which includes dynamic updates of target data mapping and target data definition.

[0116] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0117] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the aforementioned data model management method. This electronic device can be any smart terminal, including a tablet computer.

[0118] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0119] Please see Figure 3 , Figure 3 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes:

[0120] The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0121] The memory 902 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901 using the data model management method of the embodiments of this application.

[0122] The input / output interface 903 is used to implement information input and output;

[0123] The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0124] Bus 905 transmits information between various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904);

[0125] The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0126] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described data model management method.

[0127] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0128] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0129] The data model management method, apparatus, electronic device, and storage medium provided in this application embodiment can perform structured management of data models, avoid problems such as unclear data model structure, inconsistent fields, and inability to support multiple databases, achieve efficient management of data models, and improve the efficiency and dynamic adaptability of data model management.

[0130] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0131] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0132] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0133] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0134] 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 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.

[0135] 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.

[0136] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above 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 through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0137] The units described above 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.

[0138] 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.

[0139] It should be recognized that embodiments of the present invention can be implemented or carried out by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable storage medium. The method can be implemented in a computer program using standard programming techniques, including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium is configured such that the computer operates in a specific and predefined manner—according to the methods and drawings described in the specific embodiments. Each program can be implemented in a high-level procedural or object-oriented programming language to communicate with the computer system. However, if desired, the program can be implemented in assembly or machine language. In any case, the language can be a compiled or interpreted language. Furthermore, for this purpose, the program can run on a programmed application-specific integrated circuit (ASIC).

[0140] 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 multiple 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 of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0141] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A data model management method, characterized in that, The method includes: Obtain target database information; Based on the target database information, the corresponding target data mapping and target data definition are determined, wherein the target data definition includes data conventions and data elements; Based on the target data mapping and the target data definition, a corresponding target data model is generated; The target data model is dynamically managed, and the dynamic management includes the dynamic updating of the target data mapping and the target data definition. The step of determining the corresponding target data mapping and target data definition based on the target database information includes: Obtain multiple preset data mappings and the database types corresponding to each preset data mapping; Based on the target database information, determine the corresponding target database type and target database identification information; Based on the database type corresponding to each of the preset data mappings, determine the target data mapping that matches the target database type from among the multiple preset data mappings; The target data definition is determined based on the target database identification information; The step of determining the target data definition based on the target database identifier information specifically includes: Parse the target database identification information to determine multiple data items and the data attributes corresponding to each data item; Based on the data attributes corresponding to the data items, establish data element items corresponding to each data item, as well as a set of data element attributes and data processing rules corresponding to each data element item; Based on the set of data processing rules corresponding to each data element item, the multiple data element items are divided to determine multiple data element sets and a shared set of data processing rules corresponding to each data element set; Establish data convention items corresponding to each of the data element sets, and determine the data convention attributes corresponding to the data convention items based on the shared data processing rule set corresponding to the data element sets. For each data element item, a target data element set corresponding to the data element item is determined from multiple data element sets, and the data convention item corresponding to the target data element set is associated with the data element item.

2. The data model management method according to claim 1, characterized in that, The step of generating a corresponding target data model based on the target data mapping and the target data definition specifically includes: Analyze the data element attributes corresponding to each data element item to determine the association attributes between data element items; The target data is mapped and associated with each of the data element items; The target data model is generated based on the target data mapping, the data element items associated with the target data mapping and the data convention items, the association attribute, and the data convention items.

3. The data model management method according to claim 1, characterized in that, The dynamic management of the target data model specifically includes: In response to a dynamic update operation on the target data model information, the updated target data model information is determined, wherein the target data model information includes the target data mapping and the target data definition, and the update operation includes information modification, information deletion and information addition. The target data model is dynamically updated based on the updated target data model information.

4. The data model management method according to claim 1, characterized in that, The method further includes: Based on the target data model, determine the corresponding database table structure information; The database table structure information is synchronously transmitted to the corresponding target database through the data interface.

5. The data model management method according to claim 1, characterized in that, The step of dividing multiple data element items according to the data processing rule set corresponding to each data element item, and determining multiple data element sets and a shared data processing rule set corresponding to each data element set, specifically includes: Mark all the data element items as undivided, and obtain any data element item as the current judgment item; The set of data processing rules corresponding to the current judgment item is obtained as the current rule set; Based on the current set of rules, construct a corresponding set of data elements, and use the current set of rules as the set of shared data processing rules corresponding to the set of data elements. Based on the data processing rule set corresponding to each of the remaining data element items, a consistency judgment is made, and several shared data element items are determined from the multiple data element items, wherein the shared data element items are the data element items whose data processing rule set is consistent with the current rule set; Mark each of the shared data element items and the current judgment item as having been divided and add them to the data element set; Determine whether there are any undivided data element items, wherein the undivided data element items are the data element items in the undivided state; When any of the undivided data element items exists, obtain any of the undivided data element items as the current judgment item, and then return to the step of obtaining the data processing rule set corresponding to the current judgment item as the current rule set, until there are no more undivided data element items. When there is no undivided data element item, determine the set of shared data processing rules corresponding to each set of data elements, and the several data element items contained in each set of data elements.

6. A data model management device, characterized in that, The device includes: The first module is used to obtain target database information; The second module is used to determine the corresponding target data mapping and target data definition based on the target database information, wherein the target data definition includes data conventions and data elements; The third module is used to generate a corresponding target data model based on the target data mapping and the target data definition; The fourth module is used to dynamically manage the target data model, and the dynamic management includes the dynamic updating of the target data mapping and the target data definition; The step of determining the corresponding target data mapping and target data definition based on the target database information includes: Obtain multiple preset data mappings and the database types corresponding to each preset data mapping; Based on the target database information, determine the corresponding target database type and target database identification information; Based on the database type corresponding to each of the preset data mappings, determine the target data mapping that matches the target database type from among the multiple preset data mappings; The target data definition is determined based on the target database identification information; The step of determining the target data definition based on the target database identifier information specifically includes: Parse the target database identification information to determine multiple data items and the data attributes corresponding to each data item; Based on the data attributes corresponding to the data items, establish data element items corresponding to each data item, as well as a set of data element attributes and data processing rules corresponding to each data element item; Based on the set of data processing rules corresponding to each data element item, the multiple data element items are divided to determine multiple data element sets and a shared set of data processing rules corresponding to each data element set; Establish data convention items corresponding to each of the data element sets, and determine the data convention attributes corresponding to the data convention items based on the shared data processing rule set corresponding to the data element sets. For each data element item, a target data element set corresponding to the data element item is determined from multiple data element sets, and the data convention item corresponding to the target data element set is associated with the data element item.

7. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the data model management method according to any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the data model management method according to any one of claims 1 to 5.

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