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

Abstract

The application provides a data model processing method and device, electronic equipment and a storage medium. The method comprises the following steps: obtaining business data of at least one business system; and constructing a data model by using target attribute information selected by a user, so that the established data model is more accurate. The data model is sent to a shopping guide system device, and the shopping guide system device can complete the update of the data model, so that the installation cost of the replacement model is lower.

Description

Technical Field

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

[0002] During the process of information technology construction, retail enterprises have encountered a surge in various online and offline retail channels, including physical stores, their own online stores, e-commerce platforms, and social media platforms, resulting in a large amount of fragmented data. The fragmentation of business systems and the dispersion of channels have gradually exposed their drawbacks. Specifically, it is impossible to build a data model of consumer profiles across all scenarios through unified membership data management, making it impossible for physical stores to achieve precise marketing. In addition, physical stores face high costs and untimely model updates. Summary of the Invention

[0003] To address the aforementioned issues, this application provides a data model processing method, apparatus, electronic device, and storage medium that can uniformly process dispersed business data and establish a data model based on user-selected target attribute information. This allows the data model to be deployed to a shopping guide system device, which can then update the data model. This enables more precise offline channel marketing and reduces the installation cost of replacing the model.

[0004] This application provides a method for processing a data model, including:

[0005] Obtain business data from at least one business system;

[0006] Determine the attribute information of each piece of data in each business data;

[0007] Obtain the target attribute information selected by the user, and determine the data corresponding to the target attribute information;

[0008] A data model is created based on the data corresponding to the target attribute information;

[0009] Send the data model to the store system device to deploy the data model to the store system device.

[0010] In some embodiments, determining the attribute information of each piece of data in each business data includes:

[0011] Obtain the dimension information selected by the user;

[0012] Based on the dimensional information, the business data is deduplicated to obtain the deduplicated business data.

[0013] By analyzing the deduplicated business data using big data, the attribute information of each piece of data in each business data is determined.

[0014] In some embodiments, acquiring business data from at least one business system includes:

[0015] Business data is synchronously retrieved from at least one business system at a preset time period.

[0016] In some embodiments, the business system includes: an online shopping platform and an offline store system; the attribute information includes at least one of product performance, product cost-effectiveness, and product appearance; the target attribute information includes at least one of the attribute information.

[0017] This application embodiment further provides a data model processing method applied to store system equipment, including:

[0018] Obtain a data model, wherein the data model is established based on target attribute information selected by the user;

[0019] The data model is parsed to determine whether it already exists in the store system equipment;

[0020] If the data model is not present in the store system equipment, the current model of the store system equipment is replaced based on the data model, and the data of the data model is loaded to complete the installation of the data model.

[0021] In some embodiments, the method further includes:

[0022] If the data model exists in the store system equipment, the data of the data model is loaded to update the data model in the business system.

[0023] This application provides a data model processing apparatus, including:

[0024] The first acquisition module is used to acquire business data from at least one business system.

[0025] The first determination module is used to determine the attribute information of each piece of data in each business data;

[0026] The second acquisition module is used to acquire the target attribute information selected by the user and determine the data corresponding to the target attribute information.

[0027] A creation module is used to create a data model based on the data corresponding to the target attribute information;

[0028] The sending module is used to send the data model to the store system equipment so as to deploy the data model to the store system equipment.

[0029] This application embodiment further provides a data model processing apparatus, including:

[0030] The second acquisition module is used to acquire a data model, wherein the data model is established based on the target attribute information selected by the user;

[0031] The second determining module is used to parse the data model and determine whether the data model already exists in the store system equipment;

[0032] The processing module is used to replace the current model of the store system equipment with the data model when the data model does not exist in the store system equipment, and to load the data of the data model to complete the installation of the data model.

[0033] This application provides an electronic device, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, performs the data model processing method described in any of the above-mentioned embodiments.

[0034] This application provides a computer-readable storage medium storing a computer program that can be executed by one or more processors and can be used to implement the data model processing method described above.

[0035] This application provides a data model processing method, apparatus, electronic device, and storage medium. By acquiring business data from at least one business system and then constructing a data model using target attribute information selected by the user, the established data model can be made more accurate. The data model is then sent to a shopping guide system device, which can update the data model, thus reducing the installation cost of replacing the model. Attached Figure Description

[0036] The present application will be described in more detail below based on embodiments and with reference to the accompanying drawings.

[0037] Figure 1 A schematic diagram illustrating the implementation flow of a data model processing method provided in an embodiment of this application;

[0038] Figure 2 A schematic diagram illustrating the implementation flow of another data model processing method provided in this application embodiment;

[0039] Figure 3 A schematic diagram illustrating the implementation flow of another data model processing method provided in this application embodiment;

[0040] Figure 4 A schematic diagram of the structure of a data model processing device provided in an embodiment of this application;

[0041] Figure 5This is a schematic diagram of the composition structure of the electronic device provided in the embodiments of this application.

[0042] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0044] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0045] If the application documents contain similar descriptions such as "first, second, third", the following explanation shall be added: In the following description, the terms "first, second, third" are used only to distinguish similar objects and do not represent a specific order of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0046] 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.

[0047] To address the problems existing in related technologies, this application provides a data model processing method. This method is applied to an electronic device, which can be a data platform. A data platform refers to the use of data technology to collect, calculate, store, and process massive amounts of data, while simultaneously unifying standards and definitions. After unifying the data, the data platform forms standardized data, which is then stored to form a big data asset layer, thereby providing efficient services to customers. The functions implemented by the data model processing method provided in this application can be achieved by the processor of the electronic device calling program code, which can be stored in a computer storage medium.

[0048] Example 1

[0049] This application provides a data model processing method. Figure 1This is a schematic diagram illustrating the implementation flow of a data model processing method provided in an embodiment of this application, as shown below. Figure 1 As shown, it includes:

[0050] Step S101: Obtain business data from at least one business system.

[0051] In this embodiment of the application, the business system can be an offline store system and an online shopping platform. The online shopping platform can include: a self-owned mall, an e-commerce platform, a social software platform, a questionnaire survey system, etc. The business data can include member data, user purchase data, product data, user evaluation data of products, questionnaire survey information, etc.

[0052] In this embodiment of the application, in order to obtain more comprehensive business data, business data from all business systems can be obtained through a data platform.

[0053] In this embodiment of the application, the data platform can synchronously obtain business data from at least one business system at a preset time period, which can be one month.

[0054] Step S102: Determine the attribute information of each data in each business data.

[0055] In this embodiment of the application, the attribute information can be a classification of various data, and the classification can include: product performance, product cost performance, and product appearance.

[0056] In this embodiment of the application, the attribute information of each data in each business data can be determined based on big data technology.

[0057] In this embodiment of the application, step S102 can be implemented through the following steps:

[0058] Step S1021: Obtain the dimension information selected by the user.

[0059] In this embodiment of the application, the user can select dimension information by inputting through an input device. The dimension information may be a name, phone number, etc.

[0060] Step S1022: Based on the dimensional information, the business data is deduplicated to obtain deduplicated business data.

[0061] In this embodiment of the application, since different business data may have a lot of duplicate data, in order to improve processing efficiency, it is necessary to remove duplicate data and keep only one identical data.

[0062] Following the example above, business data can be deduplicated using phone numbers. In this embodiment, after deduplication, the data can be stored in a database.

[0063] Step S1023: Analyze the deduplicated business data using big data to determine the attribute information of each piece of data in each business data set.

[0064] In this embodiment of the application, after big data analysis, various different attribute information can be created to match business data with attribute information.

[0065] In this embodiment, users can be associated with multiple attribute information. For example, if a user values ​​both product performance and product appearance, then this user will appear under both product performance and product appearance attributes. This classification creates a foundation for the subsequent construction of the data model.

[0066] Step S103: Obtain the target attribute information selected by the user and determine the data corresponding to the target attribute information.

[0067] In this embodiment, after obtaining the attribute information of each business data, options for the attribute information can be generated for the user to select. The user can select the target attribute information through an input device, such as a mouse.

[0068] In this embodiment of the application, the data corresponding to the target attribute information can be determined based on the correspondence between attribute information and each data.

[0069] Step S104: Create a data model based on the data corresponding to the target attribute information.

[0070] In this embodiment of the application, the data platform can analyze the various data corresponding to the target attribute information and create a data model.

[0071] For example, if many customers focus on product performance, then a data model can be built based on the company's product performance; if many customers focus on cost-effectiveness, then a data model can be built based on the company's product cost-effectiveness; or a data model can be created based on other attributes, either individually or in combination.

[0072] Step S105: Send the data model to the store system device to deploy the data model to the store system device.

[0073] In this embodiment of the application, after the store system obtains the data model, it can perform parsing and processing, and then deploy the data model in the store system equipment.

[0074] This application provides a data model processing method that obtains business data from at least one business system through a data middle platform, and then constructs a data model based on the target attribute information selected by the user. This method enables the data model to be more accurate. The data model is then sent to the shopping guide system device, which can update the data model, thus reducing the installation cost of replacing the model.

[0075] Example 2

[0076] Based on the foregoing embodiments, this application provides another data model processing method. The method is applied to an electronic device, which may be a store system device, a computer, or a mobile terminal, such as a mobile phone or a tablet computer. The functions implemented by the data model processing method provided in this application can be achieved by the processor of the electronic device calling program code, wherein the program code can be stored in a computer storage medium.

[0077] Figure 2 This is a schematic diagram illustrating the implementation flow of a data model processing method provided in an embodiment of this application, as shown below. Figure 2 As shown, it includes:

[0078] Step S201: Obtain the data model, wherein the data model is established based on the target attribute information selected by the user.

[0079] The data model in this application embodiment is the same as the data model in the above embodiment.

[0080] Step S202: parse the data model to determine whether the data model already exists in the store system equipment.

[0081] In this embodiment of the application, a standard data model parsing method can be established. The developed project is deployed to offline stores by the operation and maintenance engineer. When the data model is obtained, the data model can be parsed.

[0082] In this embodiment of the application, when the store system device recognizes the data model, it can compare it with the pre-stored data model to determine whether the data model already exists in the store system device.

[0083] Step S203: If the data model does not exist in the store system equipment, replace the current model of the store system equipment with the data model and load the data of the data model to complete the installation of the data model.

[0084] In this embodiment, after the data model is installed, the latest model can be displayed. In this embodiment, after displaying the new data model, the data of the original model can be cleared.

[0085] For example, if the data platform issues a product data model, the store system can then switch to a different display style for the product and shopping type by parsing the data model.

[0086] Step S204: If the data model exists in the store system equipment, load the data of the data model to update the data model in the business system.

[0087] In this embodiment of the application, when a customer evaluation model is issued by the data platform due to business adjustments, the store system obtains the new model, performs data parsing, and determines whether the new model is consistent with the previous data model. If they are consistent, it is only necessary to refresh the data display.

[0088] The data model processing method provided in this application embodiment can achieve multiple real-world effects in a single system and improve the deployment efficiency of the data model.

[0089] Example 3

[0090] Based on the foregoing embodiments, this application further provides a data model processing method, which is applied to a data model processing system, the data model processing system including: a data middle platform and store system equipment. Figure 3 A data model processing method provided in this application embodiment, such as Figure 3 As shown, the method includes:

[0091] Step S301: Information from all channels is aggregated and transmitted to the data platform.

[0092] In this embodiment of the application, channel data aggregation involves aggregating data from various platforms, collecting all user information through online and offline channels, and linking it to the data platform.

[0093] In step S302, the data platform performs data analysis, deduplication, and constructs a basic data model.

[0094] Data analysis and deduplication can be performed by selecting a dimension (usually phone number) for data deduplication, as some users may have left information on more than one channel. After data deduplication, a basic, shared database is created, and all data is added to this database as the raw data for creating various data models later. Simultaneously, because data from each channel will increase over time, data synchronization needs to be prepared, generally once a month is sufficient. After data deduplication, various attributes are created through big data analysis, and user information is then mapped to these attributes. For example, some users value both product performance and product appearance; thus, this user will appear under both product performance and product appearance attributes. This attribute classification lays the foundation for subsequent data model construction.

[0095] Step S303: Dynamically construct differentiated models based on different needs.

[0096] In this embodiment, appropriate attributes can be selected to construct a data model according to project requirements. For example, if many customers focus on the performance attributes of a product, a data model can be constructed based on the company's product performance; if many customers focus on the cost-effectiveness attribute, a data model can be constructed based on the company's product cost-effectiveness; or a data model can be created based on other attributes, either individually or in combination.

[0097] Step S304, Development and deployment of the store system.

[0098] In this embodiment, different page displays and event handling effects are achieved based on the pre-configured model. The same data model is loaded into the store system, and a standard data model parsing method is established. The developed project is then deployed to Gree's offline stores by the operation and maintenance engineers.

[0099] Step S305: The data platform sends model data.

[0100] Step S306: The store system obtains data from the data platform model, parses and displays it.

[0101] In this embodiment, after the system starts running, it receives a data model from the data platform, parses the data according to the built-in parsing method, adjusts the system display style according to the type of data model, and then loads and displays the data. For example, if the data platform sends a product data model, the store system parses the data model and switches to a product display and shopping type display style.

[0102] In step S307, the data platform sends another set of model data.

[0103] Step S308: The store system receives and parses the data model data.

[0104] Step S309: Determine whether the same data model already exists.

[0105] In this embodiment of the application, if yes, step S310 is executed; if no, step S311 is executed.

[0106] Step S310: The system interface display type and functions remain unchanged, and the data is refreshed.

[0107] The process ends here.

[0108] Step S311: Change the system interface display type and function, and load new model data.

[0109] The process ends here.

[0110] In some embodiments, when the store system is first deployed, the built-in system display style is set according to the standard data model. However, in future project requirements, there may be some unusual requirements, which requires the development of a special model for adaptation in later maintenance, and then timely updates to the store system.

[0111] This application provides a data model processing method that uses a data platform to analyze collected data and generate different data models based on different needs or focuses. The store system automatically parses and switches the display style interface corresponding to the data model according to the different data models sent by the data platform, and loads the corresponding data, thus achieving a system that can display multiple types of data with a single development.

[0112] By using the technology platform for data collection, storage, and development, not only is massive amounts of data centralized, facilitating future data use and display, but user data is also centralized, which is beneficial for data security and the company's future data collection and product development.

[0113] Meanwhile, the dynamic models built through the data platform can more easily display data to non-data analysis professionals, lowering the learning and understanding threshold.

[0114] The development of a store system allows for multiple effects with a single installation in the store, saving on future installation and development costs. It also enables quick switching between different system display effects using a single system.

[0115] Example 4

[0116] Based on the foregoing embodiments, this application provides a data model processing device. The modules and units included in the device can be implemented by a processor in a computer device; of course, they can also be implemented by specific logic circuits. In the implementation process, the processor can be a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.

[0117] This application provides a data model processing apparatus. Figure 4 This is a schematic diagram of the structure of a data model processing device provided in an embodiment of this application, as shown below. Figure 4 As shown, the data model processing device 400 includes:

[0118] The first acquisition module 401 is used to acquire business data from at least one business system.

[0119] The first determining module 402 is used to determine the attribute information of each data in each business data;

[0120] The second acquisition module 403 is used to acquire the target attribute information selected by the user and determine the data corresponding to the target attribute information.

[0121] A creation module 404 is used to create a data model based on the data corresponding to the target attribute information;

[0122] The sending module 405 is used to send the data model to the store system device so as to deploy the data model to the store system device.

[0123] In some embodiments, determining the attribute information of each piece of data in each business data includes:

[0124] Obtain the dimension information selected by the user;

[0125] Based on the dimensional information, the business data is deduplicated to obtain the deduplicated business data.

[0126] By analyzing the deduplicated business data using big data, the attribute information of each piece of data in each business data is determined.

[0127] In some embodiments, acquiring business data from at least one business system includes:

[0128] Business data is synchronously retrieved from at least one business system at a preset time period.

[0129] In some embodiments, the business system includes: an online shopping platform and an offline store system; the attribute information includes at least one of product performance, product cost-effectiveness, and product appearance; the target attribute information includes at least one of the attribute information.

[0130] This application embodiment further provides a data model processing apparatus, including:

[0131] The second acquisition module is used to acquire a data model, wherein the data model is established based on the target attribute information selected by the user;

[0132] The second determining module is used to parse the data model and determine whether the data model already exists in the store system equipment;

[0133] The processing module is used to replace the current model of the store system equipment with the data model when the data model does not exist in the store system equipment, and to load the data of the data model to complete the installation of the data model.

[0134] In some embodiments, the data model processing apparatus is further configured to, when the data model exists in the store system equipment, load the data of the data model to update the data model in the business system.

[0135] It should be noted that, in the embodiments of this application, if the above-described data model processing method is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this application are not limited to any specific hardware and software combination.

[0136] Accordingly, this application provides a computer-readable storage medium storing a computer program thereon, characterized in that the computer program, when executed by a processor, implements the steps in the data model processing method provided in the above embodiments.

[0137] Example 5

[0138] This application provides an electronic device; Figure 5 This is a schematic diagram of the composition structure of the electronic device provided in the embodiments of this application, such as... Figure 5 As shown, the electronic device 700 includes: a processor 701, at least one communication bus 702, a user interface 703, at least one external communication interface 704, and a memory 705. The communication bus 702 is configured to enable communication between these components. The user interface 703 may include a display screen, and the external communication interface 704 may include standard wired and wireless interfaces. The processor 701 is configured to execute a program for processing a data model stored in the memory, to implement the steps in the data model processing method provided in the above embodiment.

[0139] The descriptions of the above embodiments of the electronic devices and storage media are similar to those of the above method embodiments, and have similar beneficial effects. For technical details not disclosed in the embodiments of the computer devices and storage media of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0140] It should be noted that the descriptions of the storage medium and device embodiments above are similar to the descriptions of the method embodiments above, and have similar beneficial effects. For technical details not disclosed in the storage medium and device embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0141] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0142] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0143] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and 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. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0144] 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. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0145] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0146] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0147] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a controller to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0148] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for processing a data model, characterized in that, include: Obtain business data from at least one business system; Determine the attribute information of each piece of data in each business data; Obtain the target attribute information selected by the user, and determine the data corresponding to the target attribute information; A data model is created based on the data corresponding to the target attribute information; wherein, the data model is used to define the functions of the store system equipment and the display type of the system interface; The data model is sent to the store system device. The store system device determines whether the same data model already exists. If yes, the display type and function of the system interface of the store system device remain unchanged, and the data is refreshed. If no, the data model is deployed to the store system device, causing the store system device to change the display type and function of the system interface and load the new model data. This allows the store system device to automatically parse and switch the display style interface corresponding to the data model according to the different data models sent by the data platform, load the corresponding data, and realize the switching of system functions and the updating of interface display type.

2. The method according to claim 1, characterized in that, Determining the attribute information of each piece of data in each business data includes: Obtain the dimension information selected by the user; Based on the dimensional information, the business data is deduplicated to obtain the deduplicated business data. By analyzing the deduplicated business data using big data, the attribute information of each piece of data in each business data is determined.

3. The method according to claim 2, characterized in that, The acquisition of business data from at least one business system includes: Business data is synchronously retrieved from at least one business system at a preset time period.

4. The method according to claim 1, characterized in that, The business system includes an online shopping platform and an offline store system. The attribute information includes at least one of product performance, product cost-effectiveness, and product appearance. The target attribute information includes at least one of the attribute information.

5. A method for processing a data model, characterized in that, Applied to store system equipment, including: Obtain business data from at least one business system; Determine the attribute information of each piece of data in each business data; Obtain the target attribute information selected by the user, and determine the data corresponding to the target attribute information; Obtain a data model, wherein the data model is established based on target attribute information selected by the user; The data model is parsed to determine whether it already exists in the store system equipment; wherein, the data model is used to define the functions of the store system equipment and the display type of the system interface; If the data model is not present in the store system equipment, the current model of the store system equipment is replaced based on the data model, and the data of the data model is loaded to complete the installation of the data model. The system functions are switched and the interface display type is updated according to the data model.

6. The method according to claim 5, characterized in that, The method further includes: If the data model exists in the store system equipment, the data of the data model is loaded to update the data model in the business system.

7. A data model processing apparatus, characterized in that, include: The first acquisition module is used to acquire business data from at least one business system. The first determination module is used to determine the attribute information of each piece of data in each business data; The second acquisition module is used to acquire the target attribute information selected by the user and determine the data corresponding to the target attribute information. A creation module is used to create a data model based on the data corresponding to the target attribute information; A sending module is used to send the data model to the store system device to deploy the data model to the store system device; The second acquisition module is used to acquire a data model, wherein the data model is established based on the target attribute information selected by the user; The second determining module is used to parse the data model and determine whether the data model already exists in the store system equipment; wherein, the data model is used to define the functions of the store system equipment and the display type of the system interface; The processing module is used to replace the current model of the store system device with the data model when the data model does not exist in the store system device, and load the data of the data model to complete the installation of the data model, and switch system functions and update interface display type according to the data model; The store system equipment automatically parses and switches the display style interface corresponding to the different data models sent by the data platform, and loads the corresponding data.

8. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, performs the processing method of the data model as described in any one of claims 1 to 5.

9. A storage medium, characterized in that, The computer program stored in the storage medium can be executed by one or more processors and can be used to implement the processing method of the data model as described in any one of claims 1 to 5.

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