Data query method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a data query method and device, electronic equipment and a storage medium. The data query method comprises the steps that a data query request is received, and the data query request carries querier information; based on the data query request, determining a query dimension and target data; and determining a return result based on the querier information, the query dimension and the target data. According to the data query method provided by the embodiment of the invention, the return result can be determined based on the query dimension, and the reliability of data query is improved.

Description

Technical Field

[0001] This specification relates to the field of computer technology, and more particularly to a data query method, apparatus, electronic device, and storage medium. Background Art

[0002] Data query is one of the indispensable capabilities of modern enterprises and organizations. With the development of big data technology, the methods and tools for data query are constantly evolving, making it more efficient, convenient, and intelligent. In related technologies, data queries can be performed through specific data query statements, such as SQL statements. Summary of the Invention

[0003] Embodiments of the present application provide a data query method, apparatus, electronic device, and storage medium, which can determine the return result based on the query dimension, improving the reliability of data query.

[0004] In a first aspect, embodiments of the present application provide a data query method, including: receiving a data query request, where the data query request carries information about the querying person; determining a query dimension and target data based on the data query request; and determining a return result based on the information about the querying person, the query dimension, and the target data.

[0005] In some implementations, determining the return result based on the information about the querying person, the query dimension, and the target data includes: determining the permissions of the querying person based on the information about the querying person; and determining the return result based on the permissions of the querying person, the query dimension, and the target data.

[0006] In some implementations, determining the return result based on the permissions of the querying person, the query dimension, and the target data includes: adding a dimension field to the target data and using the query dimension as the content of the dimension field to obtain data to be verified; and verifying the data to be verified based on the permissions of the querying person to determine the return result.

[0007] In some implementations, verifying the data to be verified based on the permissions of the querying person to determine the return result includes: when the permissions of the querying person include the query permission for the data to be verified, determining to return the target data; or when the permissions of the querying person do not include the query permission for the data to be verified, determining to return a message indicating that the query request exceeds the permissions.

[0008] In some implementations, the query dimension includes at least one of person, department, or project.

[0009] In some implementations, determining the query dimension and target data based on the data query request includes: determining the query dimension and query statement based on a data analysis model; and determining the target data based on the query statement.

[0010] In some implementations, the data analysis model includes a natural language processing model, and the form of the data query request is natural language.

[0011] In a second aspect, an embodiment of the present application provides a data query device, including: a request receiving module, configured to receive a data query request, where the data query request carries queryer information; a first determination module, configured to determine a query dimension and target data based on the data query request; and a second determination module, configured to determine a return result based on the queryer information, the query dimension, and the target data.

[0012] In a third aspect, an embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the operations in the method described in the first aspect are implemented.

[0013] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the operations in the method described in the first aspect are implemented.

[0014] In summary, an embodiment of the present application discloses a data query method, device, electronic device, and storage medium. The data query method includes receiving a data query request, where the data query request carries queryer information; determining a query dimension and target data based on the data query request; and determining a return result based on the queryer information, the query dimension, and the target data. The data query method provided by the embodiment of the present application can determine a return result based on a query dimension, improving the reliability of data query. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] To more clearly illustrate the technical solutions in the embodiments of this specification, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of this specification. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 A schematic diagram of an application scenario of the data query method provided by some embodiments of the present application is shown;

[0017] Figure 2 A schematic flowchart of the data query method provided by some embodiments of the present application is shown;

[0018] Figure 3 A schematic flowchart of the method for determining a return result provided by some embodiments of the present application is shown;

[0019] Figure 4 The flowchart of the data query method provided by some embodiments of the present application is shown;

[0020] Figure 5 The structural schematic diagram of the data query device provided by some embodiments of the present application is shown;

[0021] Figure 6 The structural schematic diagram of the electronic device provided by some embodiments of the present application is shown. Detailed implementation manners

[0022] Next, the technical solutions in the present application will be clearly and completely described in conjunction with the accompanying drawings in the present application. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present invention.

[0023] Figure 1 The application scenario schematic diagram of the data query method provided by some embodiments of the present application is shown. The data query method provided by the present application can be applied to an application scenario as Figure 1 shown. As Figure 1 shown, the application scenario may include a user 101, a terminal 102, and a data query system 103.

[0024] Among them, the user 101 can be any user who queries data through the terminal 102. The user 101 can initiate a data query request through the terminal 102. For example, the user 101 can input the question to be queried and obtain the query result. For example, the data query request of the user 101 can be "How many working hours does Xiao Wang have each month this year?", "What is the profit situation of Department A this year?", and so on.

[0025] Among them, the terminal 102 can be a device that interacts with the user 101. The user 101 can input various data or instructions to the terminal 102 through the input / output device of the terminal 102 and receive data or results from the terminal 102. In some embodiments, the terminal 102 may include a hardware device with data information processing capabilities and the necessary application programs required to drive the hardware device to work. The application program can provide the user 101 with the ability to interact with the outside world through the network and an interface.

[0026] In some embodiments, the terminal 102 may include a mobile device, a tablet computer, a laptop computer, a built-in device of a motor vehicle, or the like, or any combination thereof. In some embodiments, the mobile device may include a smart home device, a smart mobile device, a virtual reality device, an augmented reality device, or the like, or any combination thereof. In some embodiments, the smart home device may include a smart TV, a desktop computer, etc., or any combination. In some embodiments, the smart mobile device may include a smart phone, a personal digital assistant, a gaming device, a navigation device, etc., or any combination thereof. In some embodiments, the built-in device in the motor vehicle may include an in-vehicle computer, an in-vehicle TV, etc.

[0027] Among them, the data query system 103 may be a back-end server that provides services to the terminal 102. For example, the data query system 103 may receive a data query request sent by the terminal 102, determine the query dimension and the target data based on the data query request, and determine the return result based on the queryer information, the query dimension, and the target data. The data query system 103 returns the result to the terminal 102 and can be displayed through the interaction program of the terminal 102.

[0028] The data query system 103 may include one or more databases to store the data required by the user 101. In the database, the data may be organized according to a certain structure (such as a table, a set, or a document, etc.) and can be managed by a database management system. The data query system 103 may receive a data query request from the terminal 120 and perform operations such as data access on the database based on the data query request.

[0029] In some embodiments, the data query system 103 may further include a data analysis model, which can be used to determine the query dimension and query statement of the data query, and can determine the target data based on the query statement.

[0030] The data query system 103 may be a single computing device or a cluster system composed of multiple computing devices. The data query system 103 may adopt various architectures to meet different requirements, performance requirements, and scalability goals. For example, the data query system 103 may be a centralized architecture, a distributed architecture, an architecture that combines batch processing and real-time processing, a stream computing architecture, a data warehouse architecture, a cloud-native architecture, or one or more of the data warehouse architectures. It should be noted that Figure 1 the number of computing devices in the terminal 102 and the data query system 103 shown are all exemplary, and according to the implementation needs, it may have any number.

[0031] It should also be noted that Figure 1The schematic diagram of the application scenario of the data query shown is only an example. This application scenario example is to more clearly illustrate the technical solution of the embodiments of the present application and does not constitute a limitation on the technical solution of the present application. For example, in some embodiments, the data query system 103 may also include a terminal 102.

[0032] Figure 2 The flowchart of the data query method provided by some embodiments of the present application is shown. Although the logical order is shown in the flowchart, in some cases, the operations shown or described may be executed in a different order than that shown in the drawings. The specific process of the data query method may be as follows:

[0033] S201. Receive a data query request.

[0034] Among them, the data query request can be used to indicate the data that the querier expects to obtain. For example, the data query request can be a query request for working hour data, salary data, operation data, query request for content in a professional knowledge base, or a similar query request. The present application does not limit the type and content of the data query request.

[0035] In some embodiments, the data query request can be made by selecting different fields in the data query interface. For example, in the data query interface, there is a tab for the application scenario. After clicking on the application scenario, sub-tabs for specific application scenarios such as working hour query, salary query, operation data query, etc. can be selected. According to the specific application scenario, further selection can be made to query the data of a certain employee or department. It can be understood that the foregoing example is only one possible implementation manner of the data query interface, and other implementation manners are also within the protection scope of the present application.

[0036] In some other embodiments, the data query request can be described using natural language. The querier can describe the data query request through an input box, and the description method can be text or voice input. For example, the querier can input "What is the salary of Xiao Li in July this year?", "How about the performance of the company's sales department this year?", or "What are the budgets of the top ten projects next year? Who are the person in charge of each project?" or similar data query requests described using natural language.

[0037] The data query request can carry querier information. The querier information can be used to reflect the position, rank or authority of the querier. For example, the querier information included in the data query request can be the querier's work number, the querier's device number or other specific identity identifiers. The querier information carried by the data query request can be adding the querier information to the content of the data request, or attaching the querier information when transmitting the signal of the data query request.

[0038] S202. Determine the query dimension and the target data based on the data query request.

[0039] Among them, the query dimension can be used to distinguish data types. For example, the query dimension can be one or more of personnel, department, or project.

[0040] For example, the content of the data query request is "What is Xiao Li's salary in July this year?" The query dimension in this data query request is personnel, that is, the data query for "Xiao Li". Another example, the content of the data query request is "How about the performance of the company's sales department this year?" The query dimension in this data query request is department, that is, the data query for "sales department". Another example, the content of the data query request is "What are the budgets of the top ten projects for next year? Who are the person in charge of each project?" The query dimension in this data query request is project, that is, the data query for "the top ten projects in terms of budget".

[0041] It can be understood that the query dimension can be set according to actual usage needs. For example, the query dimension can be working hours, salary, profit. Another example, the query dimension can be private data, non-private data. Another example, the query dimension can be internal data, external data.

[0042] Among them, the target data can be the data obtained according to the data query request. For example, it can be the data obtained by querying according to the query information included in the data query request or the query information generated according to the data query request.

[0043] In some embodiments, the data query request may include the query dimension and the query information for the target data. By parsing the data query request to obtain the query dimension and the query information related to using the target data, the target data is obtained. For example, for the data query request obtained by selecting different fields in the data query interface, its data format may include a query dimension field and a query object-related field. By parsing the data query request, the information of each field can be obtained, and a query statement can be automatically generated based on the query object-related field, and then the target data is queried from the corresponding database.

[0044] In some other embodiments, the query dimension and the target data can be determined through a data analysis model. The process can be as follows:

[0045] (1) Based on the data analysis model, determine the query dimension and the query statement.

[0046] (2) Based on the query statement, determine the target data.

[0047] The data analysis model can be a natural language processing model that can receive a data query request described in natural language. The form of the data query request can be text or speech, and the input text or speech is analyzed to generate query dimensions and a query statement for obtaining target data. Further, the target data can be obtained based on the query statement.

[0048] Among them, the data analysis model can be a series of models based on Transformer (a language model using the attention mechanism) technology, a series of models based on the Bidirectional Encoder Representation from Transformers (BERT) technology using multiple Transformers, or other similar models, or any combination thereof. In some embodiments, the network configuration model can be a series of models based on the Generative Pre-Trained Transformer (GPT) technology, a series of models based on the ChatGLM (a general language model based on the bidirectional attention mechanism) technology, a series of models based on the LLaMa (a general language model using more tokens and a smaller parameter scale) technology, or other similar models, or any combination thereof. In some embodiments, the large model based on the GPT technology can be ChatGPT3.5, ChatGPT4.0, or a similar model.

[0049] For example, the content of the data query request is "What is Xiao Li's salary in July this year?" Entering this data query request into the data analysis model can obtain the query dimension of "personnel" and a specific database query statement. For example, the query statement can be an SQL statement. Based on the output SQL statement, a query can be made in the salary database of all employees in the company to obtain the target data, that is, the specific value of Xiao Li's salary in July this year.

[0050] S203. Determine the return result based on the querier information, query dimension, and target data.

[0051] As mentioned above, the querier information can be used to reflect the querier's position, rank, or authority. The query dimension can be used to distinguish data types. The target data can be the data obtained according to the data query request. In some application scenarios, the target data is open to specific queriers. Therefore, it is necessary to determine whether the querier has the qualification or authority to obtain the target data to prevent the leakage of sensitive or private data.

[0052] Among them, the return result can be to determine to return the target data or not to return the target data.

[0053] Specifically, how to determine the return result based on the querier information, query dimension, and target data will be described in detail later.

[0054] Some embodiments of the present application provide a data query method, which includes receiving a data query request, where the data query request carries querier information; determining a query dimension and target data based on the data query request; and determining a return result based on the querier information, query dimension, and target data. The data query method provided by the embodiments of the present application can determine the return result based on the query dimension, improving the reliability of data query.

[0055] In some embodiments, the process of operation S203 can be as follows:

[0056] (1) Determine the querier's permission based on the querier information.

[0057] As mentioned above, the querier information can be used to reflect the querier's position, rank, or permission. For example, the querier information included in the data query request can be the querier's employee number, the querier's device number, or other specific identity identifiers. Therefore, the querier's permission can be determined based on the querier information.

[0058] Among them, the querier's permission can include the data that can be queried by the querier in each query dimension. For example, querier 1 can query the data of Xiaowang, Xiaoli, and Xiaozhang in the query dimension of personnel. Querier 1 can query the data of Project A, Project C, and Project F in the query dimension of projects. For other query dimensions, and so on.

[0059] In some embodiments, the querier's permission also includes the queryable time corresponding to the queryable data. For example, querier 1 can query the data of Xiaowang, Xiaoli, and Xiaozhang in the query dimension of personnel, but for these three people, querier 1's query permission is only to query the data of the three people in 2024, or there are different time permissions for the three people respectively.

[0060] (2) Determine the return result based on the querier's permission, query dimension, and target data.

[0061] The querier's permission obtained based on the querier information may include permissions in each query dimension. Therefore, it is necessary to combine the query dimension corresponding to the data query request to determine whether the target data can be returned, or whether it can be fully returned.

[0062] In some embodiments, based on the querier's permission, query dimension, and target data, the process of determining the return result can be as follows:

[0063] Add dimension fields to the target data, and use the query dimension as the content of the dimension fields to obtain the data to be verified.

[0064] Verify the data to be verified based on the queryer's permissions and determine the return result.

[0065] To facilitate data verification, that is, to determine whether the queryer has the permission to obtain the target data, dimension fields can be added to the target data. Among them, the content of the dimension fields is the query dimension corresponding to the data query request. For example, if the content of the data query request is "What is Xiaoli's salary in July this year?", the target data obtained can be a data entry including name - date - salary such as "Xiaoli, July 2024, 15000 yuan". After adding the dimension fields, the data to be verified can be "Xiaoli, July 2024, 15000 yuan, personnel".

[0066] Based on the queryer's permissions, determine whether the queryer has the permission to obtain the data to be verified, or partial permission to obtain it, and determine the return result according to the judgment result.

[0067] The data query method provided by some embodiments of the present application can, based on the queryer's permissions, determine whether the queryer has the permission to obtain the target data. Further, by adding dimension fields to the target data to obtain the data to be verified, and combining the queryer's permissions to perform permission verification on the data to be verified, the return result is determined. The data query method provided by some embodiments of the present application can improve the security of data query and prevent the queryer from obtaining data beyond the query permission.

[0068] Figure 3 The flow chart shows the method for determining the return result provided by some embodiments of the present application. Although the logical order is shown in the flow chart, in some cases, the operations shown or described can be executed in a different order from that shown in the drawings. The specific process of the method for determining the return result can be as follows:

[0069] S301. Determine the queryer's permissions based on the queryer's information.

[0070] S302. Add dimension fields to the target data, and use the query dimension as the content of the dimension fields to obtain the data to be verified.

[0071] S303. Determine whether the queryer's permissions include the query permission for the data to be verified. If so, perform operation S304; otherwise, perform operation S305.

[0072] S304. When the queryer's permissions include the query permission for the data to be verified, determine to return the target data.

[0073] For example, the content of the data query request is "What is Xiao Li's salary in July this year?", and the target data obtained can be a data entry including name - date - salary, such as "Xiao Li, July 2024, 15,000 yuan". After adding the dimension field, the data to be verified can be "Xiao Li, July 2024, 15,000 yuan, personnel". If Queryer 1's permission in the query dimension of "personnel" is to query the salary data of Xiao Wang, Xiao Li, and Xiao Zhang in 2024, then Queryer 1 can obtain the target data, that is, "Xiao Li, July 2024, 15,000 yuan".

[0074] In some embodiments, the data received by the queryer can be presented in other forms. For example, in the data query dialog box, the queryer may receive a natural - language - described reply such as "Xiao Li's salary in July 2024 is 15,000 yuan". Another example is that in the display control for returning the data query result, "15,000 yuan" may be displayed. This application does not limit the form in which the target data is presented.

[0075] When the queryer's permission does not include the query permission for the data to be verified, operation S305 is executed.

[0076] S305. Determine to return a message indicating that the query request exceeds the permission.

[0077] For example, the content of the data query request is "What is Xiao Li's salary in July last year?", and the target data obtained can be a data entry including name - date - salary, such as "Xiao Li, July 2023, 15,000 yuan". After adding the dimension field, the data to be verified can be "Xiao Li, July 2023, 15,000 yuan, personnel". If Queryer 1's permission in the query dimension of "personnel" is to query the salary data of Xiao Wang, Xiao Li, and Xiao Zhang in 2024, then Queryer 1 cannot obtain the target data. If Queryer 2's permission in the query dimension of "personnel" is to query the salary data of Xiao Wang, Xiao Zhao, and Xiao Zhang from 2022 to 2024, then Queryer 2 also cannot obtain the target data.

[0078] When the queryer has no query permission, the returned result is a message indicating that the query request exceeds the permission. For example, this message can be an error code or a message prompt indicating no query permission.

[0079] Figure 4 The flowchart of the data query method provided by some embodiments of this application is shown. As Figure 4The data query method shown above can be applied to a data query system that includes multiple services. The data query system can provide data analysis services, user permission services, data annotation services, and data verification services. The data query system can be a microservices system or a system with other architectures, and this application does not limit it.

[0080] The querier can input a data query request through the data query interface of the terminal device, and the terminal device will transmit the data query request to the data analysis service. For example, Figure 4 the data query request shown in is "How much was Xiao Li's salary last month?".

[0081] The data analysis service can obtain the query dimension and the query statement through the data analysis model. The data analysis service can transmit the query statement to the database query service and the query dimension to the data annotation service.

[0082] The permission query service can obtain the querier information based on the data query request, or receive the parsed querier information provided by other data services. Then, it can obtain the querier permission based on the querier information. The permission query service can transmit the querier permission to the data verification service.

[0083] The data annotation service can perform data annotation based on the target data and the query dimension. In some implementation manners, the data annotation method can be to add a dimension field to the target data to obtain the data to be verified. In other implementation manners, the data annotation method can be to add a label representing the query dimension to the target data to obtain the data to be verified. The data annotation service can transmit the data to be verified to the data verification service.

[0084] The data verification service determines the return result based on the querier permission and the data to be verified. If the querier permission includes the query permission for the data to be verified, the target data can be returned. For example, Figure 4 the display manner of the target data shown in is "Xiao Li's salary last month was 15,000 yuan". It can be understood that Figure 4 the example in is for returning the target result. When the data verification result fails, the return result can be an error code or a message prompt indicating no query permission.

[0085] Figure 5 The structure diagram of the data query device provided by some embodiments of this application is shown. Among them, the data query device 500 can include:

[0086] The request receiving module 501 is used to receive the data query request. Among them, the data query request carries the querier information.

[0087] The first determination module 502 is used to determine the query dimension and the target data based on the data query request.

[0088] The second determination module 503 is configured to determine a return result based on the querier information, the query dimension, and the target data.

[0089] In some embodiments of the present application, the data query device 500 may receive a data query request by the request receiving module 501. Among them, the data query request carries the querier information. The data query device 500 may determine the query dimension and the target data by the first determination module 502 based on the data query request. The data query device 500 may determine the return result by the second determination module 503 based on the querier information, the query dimension, and the target data. The data query device 500 provided by the embodiments of the present application can determine the return result based on the query dimension, improving the reliability of data query.

[0090] In some embodiments, the second determination module 503 may include a first determination unit and a second determination unit. Among them, the first determination unit may be configured to determine the querier permission based on the querier information. The second determination unit may be configured to determine the return result based on the querier permission, the query dimension, and the target data.

[0091] In some embodiments, the second determination unit may include an annotation subunit and a result return subunit. Among them, the annotation subunit may be configured to add a dimension field to the target data and use the query dimension as the content of the dimension field to obtain the data to be verified. The result return subunit may be configured to verify the data to be verified based on the querier permission and determine the return result.

[0092] In some embodiments, the result return subunit may include a permission judgment subunit. The permission judgment subunit may be configured to determine to return the target data when the querier permission includes the query permission for the data to be verified; or determine to return a message that the query request exceeds the permission when the querier permission does not include the query permission for the data to be verified.

[0093] In some embodiments, the query dimension includes at least one of personnel, department, or project.

[0094] In some embodiments, the first determination module 502 may include a third determination unit and a fourth determination unit. The third determination unit may be configured to determine the query dimension and the query statement based on the data analysis model. The fourth determination unit may be configured to determine the target data based on the query statement.

[0095] In some embodiments, the data analysis model includes a natural language processing model, and the form of the data query request is natural language.

[0096] In addition, the present application further provides an electronic device, Figure 6The schematic structural diagram of an electronic device provided by some embodiments of the present application is shown. Specifically:

[0097] The electronic device 600 may include components such as a processor 601 with one or more processing cores and a memory 602 with one or more computer-readable storage media. Those skilled in the art can understand that Figure 6 the structure of the electronic device 600 shown in does not limit the electronic device, and it may include more or fewer components than shown in the figure, or combine some components, or have different component arrangements. Among them:

[0098] The processor 601 is the control center of the electronic device 600, connecting various parts of the entire electronic device 600 through various interfaces and lines. By running or executing software programs and / or modules stored in the memory 602, and calling the data stored in the memory 602, it executes various functions of the electronic device 600 and processes data, thereby monitoring the entire electronic device 600. Optionally, the processor 601 may include one or more processing cores; preferably, the processor 601 may integrate an application processor and a modem processor. Among them, the application processor mainly processes the operating system, user interface, application programs, etc., and the modem processor mainly processes wireless communication. It can be understood that the above-mentioned modem processor may not be integrated into the processor 601 either.

[0099] The memory 602 can be used to store software programs and modules. The processor 601 executes various functional applications and data processing by running the software programs and modules stored in the memory 602. The memory 602 may mainly include a program storage area and a data storage area. Among them, the program storage area can store the operating system, application programs required for at least one function, etc.; the data storage area can store the data created according to the use of the electronic device 600, etc. In addition, the memory 602 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices. Correspondingly, the memory 602 may also include a memory controller to provide the processor 601 with access to the memory 602.

[0100] Specifically in this embodiment, the processor 601 in the electronic device 600 will load the executable files corresponding to the processes of one or more application programs into the memory 602 according to the following instructions, and the processor 601 will run the application programs stored in the memory 602, thereby implementing the operations in any data query method provided by the embodiments of the present application.

[0101] The specific process of the electronic device 600 executing the data query method can refer to Figures 1 to 4 the description in, and details are not repeated here in the present application.

[0102] Those of ordinary skill in the art can understand that all or part of the operations in the various methods of the above embodiments can be completed by instructions, or by controlling related hardware through instructions. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0103] Therefore, the present application provides a computer-readable storage medium, on which a computer program is stored. The computer program can be loaded by a processor to execute the operations in any of the data query methods provided by the present application.

[0104] For the specific implementation of each of the above operations, reference can be made to the previous embodiments, which will not be elaborated here.

[0105] Among them, the computer-readable storage medium may include: read-only memory (ROM, Read Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disc, etc.

[0106] Since the instructions stored in the computer-readable storage medium can execute the operations in any of the data query methods provided by the present application, the beneficial effects that can be achieved by any of the data query methods provided by the present application can be realized. For details, refer to the previous embodiments, which will not be elaborated here.

[0107] The above has introduced in detail a data query method, device, electronic device and storage medium provided by the present application. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those skilled in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A data query method, characterized in that, Including: Receiving a data query request, where the data query request carries information of the querier; Based on the data query request, determining a query dimension and target data; and Based on the information of the querier, the query dimension, and the target data, determining a return result.

2. The method according to claim 1, wherein The determining the return result based on the information of the querier, the query dimension, and the target data includes: Determining the querier's permission based on the information of the querier; and Based on the querier's permission, the query dimension, and the target data, determining the return result.

3. The method according to claim 2, characterized in that The determining the return result based on the querier's permission, the query dimension, and the target data includes: Adding a dimension field to the target data and using the query dimension as the content of the dimension field to obtain data to be verified; and Verifying the data to be verified based on the querier's permission and determining the return result.

4. The method according to claim 3, characterized in that, The verifying the data to be verified based on the querier's permission and determining the return result includes: When the querier's permission includes the query permission for the data to be verified, determining to return the target data; or When the querier's permission does not include the query permission for the data to be verified, determining to return a message that the query request exceeds the permission.

5. The method according to claim 2, wherein The query dimension includes at least one of personnel, department, or project.

6. The method according to claim 1, wherein, The determining the query dimension and target data based on the data query request includes: Based on a data analysis model, determining the query dimension and a query statement; and Based on the query statement, determining the target data.

7. The method according to claim 6, characterized in that, The data analysis model includes a natural language processing model, and the form of the data query request is natural language.

8. A data query device, characterized in that, Including: A request receiving module for receiving a data query request, where the data query request carries information of the querier; A first determining module for determining a query dimension and target data based on the data query request; and A second determining module for determining a return result based on the information of the querier, the query dimension, and the target data.

9. An electronic device, characterized in that, Including a memory, a processor, and a computer program stored on the memory and executable on the processor, where when the processor executes the computer program, it implements the operations in the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, A computer program is stored on a computer-readable storage medium, and when the computer program is executed by a processor, it implements the operations in the method according to any one of claims 1-7.

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