Data model management method and device, electronic equipment and storage medium

Abstract

The invention discloses a data model management method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining target database information; according to the target database information, corresponding target data mapping and target data definition are determined, and the target data definition comprises data agreement and data elements; generating a corresponding target data model according to the target data mapping and the target data definition; and performing dynamic management on the target data model, wherein the dynamic management comprises dynamic updating of the target data mapping and the target data definition. Structured management can be carried out on the data model, the problems that the data model is unclear in structure, non-uniform in field, incapable of supporting multiple databases and the like are solved, efficient management of the data model is achieved, the management efficiency and dynamic adaptability of the data model are improved, and the method can be widely applied to the technical field of database systems.

Description

Technical Field

[0001] The present application relates to the technical field of database systems, and in particular to a data model management method, device, electronic device, and storage medium. Background Art

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

[0003] 1) Database adaptation limitations: The data model is only targeted at a single database type, making it impossible to achieve "one-time design, multi-database adaptation";

[0004] 2) Insufficient dynamic adaptability: It only supports basic single-table add, delete, modify, and query operations, and cannot meet complex business scenarios involving multi-level table management and transaction management.

[0005] 3) Lack of field standardization: The same business field in different tables faces the risk of inconsistent attribute definitions such as naming and length, and lacks a unified cross-table field management mechanism.

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

[0007] The main purpose of the embodiments of the present application is to propose a data model management method, device, electronic device and storage medium, which can realize structured management of data models and improve the efficiency and dynamic adaptability of data model management.

[0008] In one aspect, an embodiment of the present application provides a data model management method, the method comprising:

[0009] Get target database information;

[0010] Determining corresponding target data mapping and target data definition according to the target database information, wherein the target data definition includes data conventions and data elements;

[0011] generating a corresponding target data model according to the target data mapping and the target data definition;

[0012] The target data model is dynamically managed, and the dynamic management includes 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] Obtaining multiple preset data mappings and database types corresponding to the preset data mappings;

[0015] Determine the corresponding target database type and target database identification information according to the target database information;

[0016] Determining the target data mapping that matches the target database type from the plurality of preset data mappings according to the database type corresponding to each of the preset data mappings;

[0017] The target data definition is determined according to the target database identification information.

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

[0019] Parsing the target database identification information to determine a plurality of data items and data attributes corresponding to each of the data items;

[0020] According to the data attributes corresponding to the data items, establishing data element items corresponding to each of the data items, and data element attributes and data processing rule sets corresponding to each of the data element items;

[0021] Dividing the plurality of data element items according to the data processing rule sets corresponding to the respective data element items, and determining a plurality of data element sets and a shared data processing rule set corresponding to the respective data element sets;

[0022] Establishing data agreement items corresponding to each of the data element sets, and determining data agreement attributes corresponding to the data agreement items based on the shared data processing rule set corresponding to the data element set;

[0023] For each of the data element items, a target data element set corresponding to the data element item is determined from a plurality of the 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 according to the target data mapping and the target data definition specifically includes:

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

[0026] Associating the target data mapping with each of the data element items;

[0027] The target data model is generated according to the target data mapping, the data element items after associating the target data mapping with the data agreement items, the association relationship attributes, and the data agreement items.

[0028] In some embodiments, the dynamically managing the target data model specifically includes:

[0029] In response to a dynamic update operation on target data model information, determining updated target data model information, the target data model information including the target data mapping and the target data definition, the update operation including information modification, information deletion, and information addition;

[0030] The target data model is dynamically updated according to the updated target data model information.

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

[0032] Determine corresponding database table structure information according to the target data model;

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

[0034] In some embodiments, dividing the plurality of data element items according to the data processing rule sets corresponding to the respective data element items, and determining the plurality of data element sets and the shared data processing rule sets corresponding to the respective data element sets, specifically includes:

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

[0036] Acquire the data processing rule set corresponding to the current judgment item as the current rule set;

[0037] Constructing a corresponding data element set according to the current rule set, and using the current rule set as the shared data processing rule set corresponding to the data element set;

[0038] Performing consistency judgment based on the data processing rule sets corresponding to the remaining data element items, and determining a number of shared data element items from the plurality of data element items, wherein the shared data element items are the data element items for which the data processing rule set is consistent with the current rule set;

[0039] Marking each of the shared data element items and the current judgment item as being in a divided state and adding them to the data element set;

[0040] Determining whether there is an undivided data element item, the undivided data element item being the data element item in the undivided state;

[0041] When any of the undivided data element items exists, obtaining any of the undivided data element items as the current judgment item, and then returning to the step of obtaining the data processing rule set corresponding to the current judgment item as the current rule set, until any of the undivided data element items does not exist;

[0042] When there is no undivided data element item, the shared data processing rule set corresponding to each of the data element sets and the number of data element items included in each of the data element sets are determined.

[0043] On the other hand, an embodiment of the present application provides a data model management device, the device comprising:

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

[0045] A second module is configured to determine corresponding target data mapping and target data definition according to the target database information, wherein the target data definition includes data conventions and data elements;

[0046] A third module is configured to generate a corresponding target data model according to the target data mapping and the target data definition;

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

[0048] On the other hand, an embodiment of the present application proposes an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the data model management method described above when executing the computer program.

[0049] On the other hand, an embodiment of the present application proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the data model management method described above.

[0050] Embodiments of the present application include at least the following beneficial effects: The present application provides a data model management method, apparatus, electronic device, and storage medium, which obtain target database information, determine a corresponding target data mapping and target data definition based on the target database information, and generate a corresponding target data model based on the target data mapping and target data definition, thereby dynamically managing the target data model. The present application enables structured management of data models, avoiding issues such as unclear data model structure, inconsistent fields, and inability to support multiple databases, thereby achieving efficient management of data models and improving the efficiency and dynamic adaptability of data model management. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0053] Figure 1 This is a flow chart of a data model management method provided by an embodiment of the present application;

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

[0055] Figure 3 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the 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 the embodiments of the present application. They are merely examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0057] It will be understood that the terms "first", "second", etc. used in this application may be used herein to describe various concepts, but unless otherwise specified, 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 the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0058] The terms "at least one", "plurality", "each", "any", etc. used in this application include "at least one", "two" or more, "plurality" or "each", "any" or "any one", "each" or "any one" as used herein.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are 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 the present application. The method may include but is not limited to steps S101 to S104:

[0061] Step S101, obtaining target database information;

[0062] Step S102: determining the corresponding target data mapping and target data definition according to the target database information, where the target data definition includes data conventions and data elements;

[0063] Step S103, generating a corresponding target data model according to the target data mapping and target data definition;

[0064] Step S104 : Dynamically manage the target data model. The 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, among which the database identification information may include but is not limited to basic database identification (including database name and instance name, etc.), database object identification (including table name, view name, index name and trigger name, etc.), column-level identification (including field name, primary key identification and foreign key identification, etc.) and other identification (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, etc. 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] According to the target database information, a data structure consisting of data mapping, data conventions and data elements is constructed. Based on the data structure, a data model is generated. Optionally, the data mapping and the data convention are in a one-to-many relationship, that is, multiple data conventions are associated with one data mapping, and the data convention and the data element are also in 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, obtaining multiple preset data mappings and the database type corresponding to each preset data mapping;

[0069] Step S202: determining the corresponding target database type and target database identification information according to the target database information;

[0070] Step S203, determining a target data mapping that matches the target database type from a plurality of preset data mappings according to the database type corresponding to each preset data mapping;

[0071] Step S204: determining the target data definition according to the target database identification information.

[0072] In some embodiments, by maintaining data mapping compatible database types and program data types, conversion, migration and integration of the stored data of the target database are achieved through data mapping, 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 the mapping item name, database type and program data type. The program data type refers to the data type used in database program objects such as stored procedures, functions, triggers, etc., among which the mapping item name can be set by yourself, and the database type is determined according to the standard definition of the database type, and the program data type is determined according to the standard definition of the program data type.

[0074] In step S203 of some embodiments, multiple preset data mappings are stored in a mapping database. If there is no target data mapping that matches the target database type among the multiple preset data mappings, the target program data type and the target database type are determined based on the target database information, and a corresponding target data mapping is generated based on the target program data type and the target database type. The target data mapping is then added as a new preset data mapping and synchronously stored 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 data attributes corresponding to each data item;

[0077] Step S302: establishing data element items corresponding to each data item, as well as data element attributes and data processing rule sets corresponding to each data element item, based on data attributes corresponding to the data item;

[0078] Step S303: Divide the multiple data element items according to the data processing rule sets corresponding to the data element items, and determine multiple data element sets and the shared data processing rule sets corresponding to the data element sets;

[0079] Step S304: establishing data contract items corresponding to each data element set, and determining data contract attributes corresponding to the data contract items according to the shared data processing rule set corresponding to the data element set;

[0080] Step S305 : for each data element item, determine a 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 the usage rules and constraints of data, defining the rules and constraints of data, while a data element is a standardized definition of data, defining the structure and semantics of data. Different data elements can share the same data contract.

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

[0083] In some embodiments, the target database identification information is parsed to determine multiple data items of 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 sets of the corresponding data element items are determined. Optionally, the structural attributes (including field name, data type and field length, etc.), semantic attributes (including field description and foreign key association relationship, etc.) and value domain characteristics (such as enumeration 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 items. The data attributes contain data quality attributes (including null value rate, uniqueness and value distribution), business rule attributes (including format pattern and timeliness, etc.) and security and compliance attributes (including sensitive data labeling and data lineage, etc.) to determine the data processing rule set corresponding to the data element items.

[0084] In step S305 of some embodiments, illustratively, assuming that 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, data element items C and D belong to data element set 3, data convention item 1 corresponding to data element set 1 is obtained, data convention item 1 is the target data convention item of data element item A, and data convention item 1 is associated with data element item A. Similarly, data convention item 2 corresponding to data element set 2 is obtained, data convention item 2 is the target data convention item of data element item B, and 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 elements as unclassified, and take any data element as the current judgment item;

[0087] Step S402: obtaining a data processing rule set corresponding to the current judgment item as the current rule set;

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

[0089] Step S404: Perform consistency determination based on the data processing rule sets corresponding to the remaining data elements, and determine a number of shared data elements from the plurality of data elements, wherein the shared data elements are data elements for which the data processing rule sets are consistent with the current rule set.

[0090] Step S405: Mark each shared data element item and the current judgment item as being in a divided state and add them to the data element set;

[0091] Step S406, determining whether there is an undivided data element item, where the undivided data element item is a data element item 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 no undivided data element item exists;

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

[0094] In some embodiments, optionally, assuming that there are data element items A to E, data element item A is used 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 performs consistency judgment on the data processing rule sets corresponding to the remaining data element items, and determines that the data processing rule sets of data element items B and D are consistent with the data processing rule set GA. Then, the data element items A, B and D are marked as divided and added to the data element set 1, and the data processing rule set GA is used as the shared data processing rule set of the data element set 1. Then, it is determined that the undivided data element items include Data element item C and data element item E, obtain data element item C or data element item E as the current judgment item, repeat the above steps until there are no undivided data element items, and finally, determine the shared data processing rule set corresponding to each data element set, as well as the several data element items contained in each data element set. For example, the shared data processing rules corresponding to data element set 1 are data processing rule set GA, including: data element item A, data element item B and data element item D, the shared data processing rules corresponding to data element set 2 are data processing rule set GC, including: data element item C, and the shared data processing rules corresponding to data element set 3 are data processing rule set GE, including: 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 to determine the association relationship attributes between the data element items;

[0097] Step S502, associating the target data mapping with each data element item;

[0098] Step S503: Generate a target data model according to the target data mapping, the associated target data mapping and the data element items, the associated relationship attributes and the data agreed items.

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

[0100] Then, the target data mapping is associated with each data element item, and the target data model is generated by combining the data convention items associated with each data element item and the association relationship attributes between the data element items.

[0101] In step S104 of some embodiments, in response to a dynamic update operation on the target data model information, the updated target data model information is determined, and the target data model is dynamically updated based on the updated target data model information, wherein the target data model information includes target data mapping and target data definition, and the update operation includes information modification, information deletion, and information addition. For each update operation, a corresponding update record script is generated, and the update record script is added to the target data model information to achieve traceability of the model update.

[0102] Specifically, by dynamically updating the target data mapping, the mapping item information associated with each data element item in the target data model is synchronously updated; by dynamically updating the data convention item, the convention item information contained in each data element item associated with the data convention item in the target data model is synchronously updated; by dynamically updating the data element item, the data element attribute information of the data element item in the target data model is synchronously updated. Among them, 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, thereby 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, determining the corresponding database table structure information according to the target data model;

[0105] Step S602: Synchronously transmit the database table structure information to the corresponding target database through the data interface.

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

[0109] Step S702: Fill the code template with data according to the target data model information to generate 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, and the data model code is exported or stored to facilitate 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.

[0111] Reference Figure 2 , Figure 2 : is an optional structural diagram of a data model management device provided in an embodiment of the present application. The device is used to implement the above-mentioned data model management method. The device 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 according to the target database information, and the target data definition includes data conventions and data elements;

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

[0115] The fourth module is used to dynamically manage the target data model, including target data mapping and dynamic update of target data definition.

[0116] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically 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] The present application also provides an electronic device including a memory and a processor, wherein the memory stores a computer program, and the processor implements the above-mentioned data model management method when executing the computer program. The electronic device can be any smart terminal including a tablet computer.

[0118] It can be understood that the contents of the above method embodiments are applicable to the present device embodiments, the functions specifically 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.

[0119] See also Figure 3 , Figure 3 The hardware structure of an electronic device according to another embodiment is shown. The electronic device includes:

[0120] The processor 901 can be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an 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 the present application;

[0121] The memory 902 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an 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 by the processor 901 to execute the data model management method of the embodiments of this application;

[0122] Input / output interface 903, used to implement information input and output;

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

[0124] Bus 905 , which 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 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0126] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned data model management method.

[0127] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiment, the functions specifically implemented by the present storage medium 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.

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

[0129] The embodiments of the present application provide a data model management method, device, electronic device, and storage medium that can perform structured management of data models, avoid problems such as unclear data model structure, inconsistent fields, and inability to support multiple databases, thereby achieving efficient management of data models and improving the efficiency and dynamic adaptability of data model management.

[0130] The embodiments described in the embodiments of this application are intended to more clearly illustrate 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. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in 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 the present application, and may include more or fewer steps than shown in the figures, or a combination of 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, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

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

[0134] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0135] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0136] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0137] The units described above as separate components may or may not be physically separate, and 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 these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0138] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0139] It should be appreciated that embodiments of the present invention may be implemented or practiced by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The methods may 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 so configured causes the computer to operate in a specific and predefined manner according to the methods and drawings described in the specific embodiments. Each program may be implemented in a high-level procedural or object-oriented programming language to communicate with the computer system. However, if desired, the program may be implemented in assembly or machine language. In any case, the language may be a compiled or interpreted language. In addition, the program may be run on a programmed application-specific integrated circuit for this purpose.

[0140] If the integrated unit is implemented in the form of 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 the present application, 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, which is stored in a storage medium and includes multiple instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: various media that can store programs, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0141] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present invention should be within the scope of the present invention.

Claims

1. A data model management method, characterized in that: The method comprises: Get target database information; Determining corresponding target data mapping and target data definition according to the target database information, wherein the target data definition includes data conventions and data elements; generating a corresponding target data model according to the target data mapping and the target data definition; The target data model is dynamically managed, and the dynamic management includes dynamic updating of the target data mapping and the target data definition.

2. The data model management method according to claim 1, characterized in that: The determining of corresponding target data mapping and target data definition according to the target database information includes: Obtaining multiple preset data mappings and database types corresponding to the preset data mappings; Determine the corresponding target database type and target database identification information according to the target database information; Determining the target data mapping that matches the target database type from the plurality of preset data mappings according to the database type corresponding to each of the preset data mappings; The target data definition is determined according to the target database identification information.

3. The data model management method according to claim 2, characterized in that: The determining the target data definition according to the target database identification information specifically includes: Parsing the target database identification information to determine a plurality of data items and data attributes corresponding to each of the data items; According to the data attributes corresponding to the data items, establishing data element items corresponding to each of the data items, and data element attributes and data processing rule sets corresponding to each of the data element items; Dividing the plurality of data element items according to the data processing rule sets corresponding to the respective data element items, and determining a plurality of data element sets and a shared data processing rule set corresponding to the respective data element sets; Establishing data agreement items corresponding to each of the data element sets, and determining data agreement attributes corresponding to the data agreement items based on the shared data processing rule set corresponding to the data element set; For each of the data element items, a target data element set corresponding to the data element item is determined from a plurality of the data element sets, and the data convention item corresponding to the target data element set is associated with the data element item.

4. The data model management method according to claim 3, characterized in that: Generating a corresponding target data model according to the target data mapping and the target data definition specifically includes: Analyze the data element attributes corresponding to each of the data element items to determine the association relationship attributes between the data element items; Associating the target data mapping with each of the data element items; The target data model is generated according to the target data mapping, the data element items after associating the target data mapping with the data agreement items, the association relationship attributes, and the data agreement items.

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

6. The data model management method according to claim 1, characterized in that: The method further comprises: Determine corresponding database table structure information according to the target data model; The database table structure information is synchronously transmitted to the corresponding target database through the data interface.

7. The data model management method according to claim 3, characterized in that: The dividing the plurality of data element items according to the data processing rule sets corresponding to the respective data element items, and determining a plurality of data element sets and a shared data processing rule set corresponding to the respective data element sets, specifically includes: Mark all the data element items as unclassified, and obtain any data element item as the current judgment item; Acquire the data processing rule set corresponding to the current judgment item as the current rule set; Constructing a corresponding data element set according to the current rule set, and using the current rule set as the shared data processing rule set corresponding to the data element set; Performing consistency judgment based on the data processing rule sets corresponding to the remaining data element items, and determining a number of shared data element items from the plurality of data element items, wherein the shared data element items are the data element items for which the data processing rule set is consistent with the current rule set; Marking each of the shared data element items and the current judgment item as being in a divided state and adding them to the data element set; Determining whether there is an undivided data element item, the undivided data element item being the data element item in the undivided state; When any of the undivided data element items exists, obtaining any of the undivided data element items as the current judgment item, and then returning to the step of obtaining the data processing rule set corresponding to the current judgment item as the current rule set, until any of the undivided data element items does not exist; When there is no undivided data element item, the shared data processing rule set corresponding to each of the data element sets and the number of data element items included in each of the data element sets are determined.

8. A data model management device, characterized in that: The device comprises: The first module is used to obtain target database information; A second module is configured to determine corresponding target data mapping and target data definition according to the target database information, wherein the target data definition includes data conventions and data elements; A third module is configured to generate a corresponding target data model according to the target data mapping and the target data definition; The fourth module is used to dynamically manage the target data model, where the dynamic management includes dynamic updating of the target data mapping and the target data definition.

9. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the data model management method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the data model management method according to any one of claims 1 to 7 is implemented.

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