Business data query method and device, electronic equipment and storage medium

Abstract

The application provides a business data query method and device, electronic equipment and storage medium. The method comprises the following steps: obtaining an index definition table of to-be-collected data, wherein the index definition table at least comprises a data name, a data description, a collection scheme and a collection frequency of the to-be-collected data; collecting data in real time according to the index definition table to obtain an index value table matched with the index definition table; constructing a database according to the index definition table and the index value table; determining a target data name and a target data description matched with a business data query instruction in response to the business data query instruction; determining a target index definition table matched with the target data name and the target data description in the database, and a target index value table matched with the target index definition table; and generating a business data query report matched with the business data query instruction according to the target index value table. The application can realize fast and efficient query of business data and reduce the query cost of business data.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data query, in particular to a business data query method and device, electronic equipment and storage medium. BACKGROUND

[0002] In the implementation process of enterprise informatization system, the following problems are often encountered: in order to improve the management ability, the enterprise will put forward various data indicators for the informatization system. For example, the employee attendance rate this month, the equipment load rate this quarter, the contract signing amount this year, and the product qualified rate this day.

[0003] In related technologies, when a user puts forward a demand, the following steps need to be experienced: 1. Arrange the informatization system implementer to analyze the underlying data logic of the user demand; 2. Arrange the technical personnel to write complex relational data query statements to filter out the business data meeting the requirements from the complex database table, and then present the final index data on the UI interface through some logical operations; 3. Arrange the test personnel to verify; 4. Arrange the operation and maintenance personnel to update the system and release the function. It is not difficult to see that every time the user puts forward an index data demand, a complete software development cycle needs to be experienced, and the time and cost are unbearable for the enterprise.

[0004] Therefore, a new business data query method, device, electronic equipment and storage medium are needed to solve the above problems. SUMMARY

[0005] Therefore, the present application provides a business data query method, device, electronic equipment and storage medium, which can realize fast and efficient query of business data and reduce the query cost of business data.

[0006] The first aspect of the embodiment of the present application provides a business data query method, comprising: acquiring an index definition table of to-be-collected data, wherein the index definition table at least includes data name, data description, collection scheme and collection frequency of the to-be-collected data, and the to-be-collected data is the minimum unit collection data corresponding to a target business scenario; performing real-time data collection according to the index definition table to obtain an index value table matched with the index definition table, wherein the index value table at least includes a collection value of the to-be-collected data and a corresponding collection time; constructing a database according to the index definition table and the index value table; determining a target data name and a target data description matched with a business data query instruction in response to the business data query instruction; determining a target index definition table matched with the target data name and the target data description in the database, and a target index value table matched with the target index definition table; and generating a business data query report matched with the business data query instruction according to the target index value table.

[0007] In a possible implementation, the response to the business data query instruction, determining the target data name and the target data description matched with the business data query instruction, comprises: inputting the business data query instruction into a large language model, and the large language model parses the business data query instruction to obtain the target data name and the target data description.

[0008] In a possible implementation, after the large language model parses the business data query instruction, the large language model is further configured to obtain current time information, and generate a query data time period corresponding to the business data query instruction according to the current time information; and the determining, in the database, the target index definition table matched with the target data name and the target data description, and the target index value table matched with the target index definition table, comprises: the large language model extracts the target index definition table in the database according to the target data name and the target data description, and extracts the target index value table in the database according to the query data time period.

[0009] In a possible implementation, the database further comprises business scenario information matched with the to-be-collected data, and the business scenario information at least comprises a place, personnel and an organizational structure corresponding to the target business scenario; and the extracting the target index value table in the database according to the query data time period comprises: extracting the target index value table in the database according to the query data time period and the business scenario information.

[0010] In a possible implementation, after the generating the business data query report matched with the business data query instruction according to the target index value table, the method further comprises: obtaining an open source data query report matched with the target data name and the target data description in an open source database; and generating a final data query report according to the business data query report and the open source data query report.

[0011] In a possible implementation, the index value table further comprises an index definition, the index definition is used to describe a type of the to-be-collected data, and the index definition is matched with the data name and the data description.

[0012] In a possible implementation, the index definition table further comprises a maximum value, a minimum value and a value unit of the to-be-collected data; and the real-time data collection according to the index definition table to obtain the index value table matched with the index definition table comprises: performing real-time data collection according to the collection scheme and the collection frequency, and removing data smaller than the minimum value or larger than the maximum value to obtain the index value table.

[0013] In a second aspect, the embodiments of the present application further provide a service data query device, comprising an obtaining module, a collecting module, a constructing module, a first determining module, a second determining module and a generating module; the obtaining module is configured to obtain an index definition table of to-be-collected data, wherein the index definition table at least comprises data name, data description, collecting scheme and collecting frequency of the to-be-collected data, and the to-be-collected data is minimum unit collecting data corresponding to a target service scenario; the collecting module is configured to collect data in real time according to the index definition table, and obtain an index value table matched with the index definition table, wherein the index value table at least comprises collecting value and corresponding collecting time of the to-be-collected data; the constructing module is configured to construct a database according to the index definition table and the index value table; the first determining module is configured to determine target data name and target data description matched with a service data query instruction in response to the service data query instruction; the second determining module is configured to determine, in the database, a target index definition table matched with the target data name and the target data description, and a target index value table matched with the target index definition table; and the generating module is configured to generate a service data query report matched with the service data query instruction according to the target index value table.

[0014] In a third aspect, the embodiments of the present application further provide an electronic device, comprising a processor and a memory, wherein the memory is configured to store instructions, and the processor is configured to invoke the instructions in the memory, so that the electronic device performs the service data query method as described in the first aspect.

[0015] In a fourth aspect, the embodiments of the present application further provide a computer readable storage medium, which stores computer instructions, and when the computer instructions run on an electronic device, the electronic device performs the service data query method as described in the first aspect.

[0016] Compared with the related art, the embodiments of the present application have at least the following advantages: by acquiring the index definition table of the to-be-collected data, on the one hand, since the index definition table includes the data name, data description, collection scheme and collection frequency of the to-be-collected data, the automatic data collection of the to-be-collected data can be realized through the index definition table; on the other hand, since the to-be-collected data is the minimum unit collection data corresponding to the target business scenario, that is, the target business scenario can be comprehensively understood through the to-be-collected data, after the target data name and the target data description matched with the business data query instruction are determined, the target index definition table and the target index value table matched with the target index definition table can be found in the database according to the target data name and the target data description, and the accurate business data query report can be obtained through the target index value table, realizing the fast and efficient query of the business data. The entire query process does not need human participation and verification, greatly reducing the query cost of the business data.

[0017] The technical effects obtained by the above-mentioned second aspect, third aspect and fourth aspect are similar to the technical effects obtained by the corresponding technical means in the first aspect, and will not be described here again. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 A step flowchart of a business data query method provided by an embodiment of the present application;

[0019] Figure 2 A design type schematic diagram of an index definition table and an index value table provided by an embodiment of the present application;

[0020] Figure 3 An application scenario schematic diagram of an index definition table provided by an embodiment of the present application;

[0021] Figure 4 An application scenario schematic diagram of an index value table provided by an embodiment of the present application;

[0022] Figure 5 Another step flowchart of a business data query method provided by an embodiment of the present application;

[0023] Figure 6 An application scenario schematic diagram of a business data query provided by an embodiment of the present application;

[0024] Figure 7 A function module diagram of a business data query apparatus provided by an embodiment of the present application;

[0025] Figure 8 A structure schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to enable a clearer understanding of the above-mentioned objects, features and advantages of the present application, the present application will now be described in detail with the following description and specific embodiments. It should be noted that the embodiments and the features in the embodiments of the present application can be combined with each other without conflict, if possible.

[0027] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. The described embodiments are merely some embodiments of the present application, but not all embodiments of the present application.

[0028] 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 in the description herein is for describing some embodiments of the present application only and is not intended to be limiting of the present application.

[0029] It should be further noted that the terms "comprise", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element preceded by "comprises a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0030] In the present application, "at least one" means one or more, and "multiple" means two or more than two. The association relationship of "and / or" between the associated objects indicates that there can be three relationships, for example, A and / or B can represent the following three cases: A exists alone, A and B exist together, and B exists alone, where A and B can be singular or plural. The terms "first", "second", "third", "fourth" and the like (if any) in the specification and claims of the present application and the drawings are used to distinguish similar objects, and are not used to describe a specific order or sequence.

[0031] In the embodiments of the present application, the words "exemplary" or "for example" are used to mean serving as an example, instance, or illustration. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the use of the term "exemplary" or "for example" is intended to present concepts in a concrete manner.

[0032] For the sake of understanding, some explanations of concepts related to the embodiments of the present application are given by way of example for reference.

[0033] Large Language Model (LLM): A deep learning-based artificial intelligence system that learns the grammar, semantics, and patterns of language by training on vast amounts of text data, enabling it to understand and generate natural language text. Its core features include a large parameter size (often reaching tens of billions or even hundreds of billions), reliance on the Transformer architecture for efficient text sequence processing, and a three-stage training process involving pre-training, fine-tuning, and reinforcement learning based on human feedback.

[0034] Key Performance Indicator (KPI): A target-oriented quantitative management indicator that measures the performance of internal processes by setting, sampling, calculating, and analyzing key parameters at the input and output ends. It is a tool for breaking down strategic goals into actionable work objectives and serves as the foundation for performance management. KPIs can help department managers clearly define their primary responsibilities and, based on that, establish performance measurement indicators for their staff. Establishing a clear and practical KPI system is crucial for effective performance management. Key performance indicators are quantitative indicators used to measure the performance of employees and are an important part of performance planning.

[0035] Please refer to Figure 1 , Figure 1 is the step flowchart of the business data query method according to an embodiment of the present application. The order of the steps in the flowchart can be changed according to different needs, and some steps can be omitted.

[0036] It should be noted that the business data query method according to the embodiments of the present application can be applied to a data query scenario, and the execution subject thereof can be a business data query device, for example, when an employee has a business data query requirement, the data query can be realized through the business data query device. Of course, the business data query method according to the embodiments of the present application can also be applied to other scenarios requiring business data query, which is not limited in the present application.

[0037] The specific process of the present embodiment is shown in Figure 1 , including the following steps:

[0038] S101, obtaining an index definition table of the data to be collected.

[0039] Specifically, the index definition table at least includes the data name, data description, collection scheme and collection frequency of the data to be collected, and the data to be collected is the minimum unit of data corresponding to the target business scenario.

[0040] More specifically, the data name is a specific name of the data to be collected, such as the equipment load rate, the product qualification rate, etc.; the data description is a specific content description of the data to be collected, for example, the data name of the data to be collected is the plan completion rate, and the corresponding data description is “indicating the proportion of the completed plan”; the collection frequency is the collection frequency of the data to be collected, for example, the daily load rate of device A is collected every day at 11 pm.

[0041] It is worth noting that the minimum unit collection data is the smallest unit of data that can be collected under the target business scenario. For example, the target business scenario is the department attendance rate, and the minimum unit collection data corresponding to the target business scenario is the attendance rate of each person in the department.

[0042] In some embodiments, the index definition table further includes the maximum value, the minimum value, and the value unit of the data to be collected. It can be understood that in the process of data collection, data less than the minimum value or greater than the maximum value will be removed, that is, abnormal noise data will be removed, to ensure the accuracy of the subsequent index value table.

[0043] S102, real-time data collection is performed according to the index definition table, and an index value table matching the index definition table is obtained.

[0044] Specifically, the index value table at least includes the collection value of the data to be collected and the corresponding collection time. More specifically, the collection time contains time information such as year, month, and day.

[0045] In some embodiments, the index value table further includes an index definition, the index definition is used to describe the type of the data to be collected, and the index definition matches the data name and the data description.

[0046] For ease of understanding, the following will be described in combination with Figures 2 to 4 The index definition table and the index value table of the present embodiment will be specifically described:

[0047] Please refer to Figure 2 The design type diagram of the index definition table and the index value table provided by the embodiment of the present application. Figure 2 The left side of the diagram is the index definition table, Figure 2 The right side of the diagram is the index value table.

[0048] Please refer to Figure 3 The application scenario diagram of the index definition table provided by the embodiment of the present application.

[0049] Figure 3 The index definition table shown includes KPI code (used for identification of large language models), KPI name (i.e. data name), minimum value, maximum value, measurement unit (i.e. value unit), trend, and data description.

[0050] Please refer toFigure 4 The application scenario diagram of the index value table provided by the embodiment of the present application is shown.

[0051] Figure 4 The index value table shown includes KPI definition (i.e., index definition), value (i.e., collected value), unit, year, quarter, month, day, etc.

[0052] S103, constructing a database according to the index definition table and the index value table.

[0053] In some embodiments, after the database is constructed, the system automatically collects data according to the index definition table and generates the corresponding index value table.

[0054] S104, in response to a business data query instruction, determining a target data name and a target data description matched with the business data query instruction.

[0055] In some embodiments, the business data query instruction is input into a large language model, and the large language model analyzes the business data query instruction to obtain the target data name and the target data description.

[0056] S105, determining in the database a target index definition table matched with the target data name and the target data description, and a target index value table matched with the target index definition table.

[0057] In some embodiments, the large language model is also used to obtain current time information and generate a query data time period corresponding to the business data query instruction according to the current time information; and determining in the database a target index definition table matched with the target data name and the target data description, and a target index value table matched with the target index definition table includes: the large language model extracts the target index definition table in the database according to the target data name and the target data description, and extracts the target index value table in the database according to the query data time period.

[0058] In some embodiments, the database also includes business scenario information matched with the data to be collected, and the business scenario information at least includes a place, personnel and organizational structure corresponding to the target business scenario; and extracting the target index value table in the database according to the query data time period includes: extracting the target index value table in the database according to the query data time period and the business scenario information.

[0059] S106, generating a business data query report matched with the business data query instruction according to the target index value table.

[0060] In order to facilitate understanding, the following takes the target business scenario of A department plan completion rate as an example to specifically explain how the embodiment performs business data query:

[0061] 1, input a business data query instruction such as "query the plan completion rate of department A in the past half year" into the large language model. After receiving the business data query instruction, the large language model obtains current time information and generates a query data time period based on the analysis of the business data query instruction.

[0062] 2, the large language model also obtains the target data name and the target data description after analyzing the business data query instruction, that is, the target data name "plan completion rate" and the target data description "representing the proportion of completed plans".

[0063] 3, the large language model extracts a target index definition table in the database according to the target data name and the target data description, and determines a target index value table in all index value tables corresponding to the target index definition table according to the query data time period.

[0064] 4, the large language model outputs a business data query report according to the target index value table.

[0065] Compared with related technologies, the embodiments of the present application have at least the following advantages: by obtaining the index definition table of the to-be-collected data, on the one hand, since the index definition table includes the data name, data description, collection scheme and collection frequency of the to-be-collected data, the automatic data collection of the to-be-collected data can be realized through the index definition table; on the other hand, since the to-be-collected data is the minimum unit of collection data corresponding to the target business scenario, that is, the target business scenario can be fully understood through the to-be-collected data, after determining the target data name and the target data description matched with the business data query instruction, the target index definition table in the database can be found according to the target data name and the target data description, and the target index value table matched with the target index definition table, and an accurate business data query report can be obtained through the target index value table, realizing fast and efficient query of business data. The entire query process does not require human participation and verification, greatly reducing the query cost of business data.

[0066] Please refer to Figure 5 , Figure 5 is a step flowchart of an embodiment of the business data query method of the present application. The order of the steps in the flowchart can be changed according to different needs, and some steps can be omitted. The data query method can be applied to the business data query device described above, but is not limited thereto, and the embodiments of the present application do not limit this.

[0067] The embodiment is a further improvement of the foregoing embodiment, and the specific improvement lies in that in the embodiment, the large language model also obtains an open source data query report matched with the target data name and the target data description from an open source database, and generates a final data query report based on the business data query report and the open source data query report. In this way, the global analysis capability of the query result can be improved while the business data is efficiently and quickly queried, and a more superior query experience is provided for the user.

[0068] The specific process of the embodiment is shown in Figure 5 and includes the following steps:

[0069] S501, an index definition table of to-be-collected data is obtained.

[0070] S502, real-time data collection is performed according to the index definition table, and an index value table matched with the index definition table is obtained.

[0071] S503, a database is constructed according to the index definition table and the index value table.

[0072] S504, a target data name and a target data description matched with a business data query instruction are determined in response to the business data query instruction.

[0073] S505, a target index definition table matched with the target data name and the target data description is determined in the database, and a target index value table matched with the target index definition table is determined.

[0074] S506, a business data query report matched with the business data query instruction is generated according to the target index value table.

[0075] S501 to S506 of the embodiment are similar to S101 to S106 of the foregoing embodiment, and details are not repeated here to avoid repetition.

[0076] S507, an open source data query report matched with the target data name and the target data description is obtained in an open source database.

[0077] S508, a final data query report is generated according to the business data query report and the open source data query report.

[0078] For ease of understanding, the following Figure 6 how the embodiment generates the final data query report is specifically explained:

[0079] Please refer to Figure 6 for a business data query application scenario provided by the embodiment of the application.

[0080] 1. Input a business data query instruction, such as "generate a production comprehensive report for the second half of last year", into the large language model. After receiving the business data query instruction, the large language model obtains current time information and generates a query data time period based on the analysis of the business data query instruction.

[0081] 2. The large language model also obtains the target data name and target data description after analyzing the business data query instruction, that is, determines the KPI definition. Figure 6

[0082] 3. The large language model extracts a target indicator value table from the database according to the query data time period and business scenario information. The large language model analyzes the target indicator value table and obtains a business data query report. Specifically, the database includes business scenario information, such as organization, personnel, factory, warehouse, storage location, etc. Figure 6

[0083] 4. The large language model obtains an open source data query report matching the target data name and target data description from an open source database, and generates a final data query report based on the business data query report and the open source data query report. The open source database includes a security management knowledge base, a supply chain and material receiving management knowledge base, etc. Figure 6

[0084] Compared with related technologies, the embodiments of the present application have at least the following advantages: by obtaining an indicator definition table of the data to be collected, on the one hand, since the indicator definition table includes the data name, data description, collection scheme and collection frequency of the data to be collected, the automatic data collection of the data to be collected can be realized through the indicator definition table; on the other hand, since the data to be collected is the minimum unit of data corresponding to the target business scenario, that is, the target business scenario can be fully understood through the data to be collected, after determining the target data name and target data description matching the business data query instruction, the target indicator definition table can be found in the database according to the target data name and target data description, and the target indicator value table matching the target indicator definition table can be found, and an accurate business data query report can be obtained through the target indicator value table, realizing fast and efficient query of business data. The entire query process does not require human intervention and verification, greatly reducing the query cost of business data.

[0085] ​​​Based on the same idea as the business data query method in the above embodiment, the application further provides a business data query device which can be used to execute the above business data query method. For the convenience of description, only the parts related to the embodiments of the application are shown in the structural schematic diagram of the business data query device, and those skilled in the art can understand that the diagrammed structure does not constitute a limitation on the device, and the device can include more or less components than the diagrammed, or combine some components, or have different component arrangement.

[0086] As shown in Figure 7 The business data query device 70 includes an acquisition module 701, a collection module 702, a construction module 703, a first determination module 704, a second determination module 705, and a generation module 706. In some embodiments, the above modules can be programmable software instructions stored in a memory and executable by a processor. It can be understood that in other embodiments, the above modules can also be program instructions or firmware fixed in the processor.

[0087] The acquisition module 701 is configured to acquire an index definition table of to-be-collected data, wherein the index definition table at least includes data name, data description, collection scheme, and collection frequency of the to-be-collected data, and the to-be-collected data is minimum unit collection data corresponding to a target business scenario.

[0088] The collection module 702 is configured to perform real-time data collection according to the index definition table to obtain an index value table matched with the index definition table, wherein the index value table at least includes collection values of the to-be-collected data and corresponding collection times.

[0089] The construction module 703 is configured to construct a database according to the index definition table and the index value table.

[0090] The first determination module 704 is configured to determine target data name and target data description matched with a business data query instruction in response to the business data query instruction.

[0091] The second determination module 705 is configured to determine, in the database, a target index definition table matched with the target data name and the target data description, and a target index value table matched with the target index definition table.

[0092] The generation module 706 is configured to generate a business data query report matched with the business data query instruction according to the target index value table.

[0093] The service data query apparatus 70 provided by the above embodiments can implement the technical solutions described in the above service data query method embodiments, and the principles of the implementation of the above modules or units can be referred to the corresponding content in the above service data query method embodiments, which will not be described here.

[0094] Please refer to Figure 8 , Figure 8 FIG. 8 is a schematic diagram of an embodiment of an electronic device. In the embodiment of the present application, the electronic device 800 includes a processor 801, a memory 802, and a display 803. Figure 8 Only some components of the electronic device 800 are shown, but it should be understood that all the components shown are not required, and more or less components can be alternatively implemented.

[0095] The processor 801 can be a central processing unit (CPU), a microprocessor, or other data processing chip in some embodiments, used to run the program code or process data stored in the memory 802, such as the service data query method in the present application.

[0096] In some embodiments, the processor 801 can be a single server or a group of servers. The group of servers can be centralized or distributed. In some embodiments, the processor 801 can be local or remote. In some embodiments, the processor 801 can be implemented in a cloud platform. In an embodiment, the cloud platform can include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-internal cloud, a multi-cloud, etc., or any combination thereof.

[0097] The memory 802 can be an internal storage unit of the electronic device 800 in some embodiments, such as a hard disk or a memory of the electronic device 800. The memory 802 can also be an external storage device of the electronic device 800 in other embodiments, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 800.

[0098] Further, the memory 802 can include both the internal storage unit and the external storage device of the electronic device 800. The memory 802 is used to store application software and various data installed on the electronic device 800.

[0099] The display 803 can be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, etc. in some embodiments. The display 803 is used to display information of the electronic device 800 and to display visualized user applications. The components 801-803 of the electronic device 800 communicate with each other through a system bus.

[0100] In an embodiment, when the processor 801 executes the service data query program in the memory 802, the following steps can be implemented:

[0101] An index definition table of to-be-collected data is acquired, wherein the index definition table at least includes data names, data descriptions, collection schemes and collection frequencies of the to-be-collected data, and the to-be-collected data is minimum unit collection data corresponding to a target service scenario;

[0102] Real-time data collection is performed according to the index definition table, to obtain an index value table matched with the index definition table, wherein the index value table at least includes collection values of the to-be-collected data and corresponding collection times;

[0103] A database is constructed according to the index definition table and the index value table;

[0104] A target data name and a target data description matched with a service data query instruction are determined in response to the service data query instruction;

[0105] A target index definition table matched with the target data name and the target data description and a target index value table matched with the target index definition table are determined in the database;

[0106] A service data query report matched with the service data query instruction is generated according to the target index value table.

[0107] It should be understood that, in addition to the above functions, the processor 801 can also implement other functions when executing the service data query program in the memory 802, which can be specifically understood by referring to the description of the corresponding method embodiments.

[0108] Further, the embodiments of the present application do not make specific limitation on the type of the electronic device 800 mentioned above, and the electronic device 800 can be a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop computer, or the like. Exemplary embodiments of the portable electronic device include, but are not limited to, a portable electronic device running an IOS, an android, a microsoft, or other operating system. The portable electronic device can also be other portable electronic devices, such as a laptop computer having a touch-sensitive surface (e.g., a touch panel), and the like. It should also be understood that in some other embodiments of the present application, the electronic device 800 can also not be a portable electronic device, but a desktop computer having a touch-sensitive surface (e.g., a touch panel).

[0109] Correspondingly, the embodiments of the present application also provide a computer readable storage medium for storing computer readable programs or instructions, which, when executed by a processor, can implement the steps or functions of the service data query method provided by the above method embodiments.

[0110] Those skilled in the art can understand that all or part of the processes of the above-mentioned embodiments can be completed by a computer program instructing related hardware (such as a processor, a controller, etc.) to complete, and the computer program can be stored in a computer readable storage medium. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory, or a random access memory, etc.

[0111] The service data query method, device, electronic device and computer readable storage medium provided by the present application are described in detail above, and the principle and implementation mode of the present application are described by applying specific examples. The above description of the embodiments is only used to help understand the method of the present application and its core idea; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range will be changed; in conclusion, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A business data query method, characterized in that, include: Obtain the indicator definition table of the data to be collected, wherein the indicator definition table includes at least the data name, data description, collection scheme and collection frequency of the data to be collected, and the data to be collected is the smallest unit of data collected corresponding to the target business scenario; Real-time data collection is performed based on the indicator definition table to obtain an indicator value table that matches the indicator definition table. The indicator value table includes at least the collected value of the data to be collected and the corresponding collection time. The indicator value table also includes an indicator definition, which describes the type of the data to be collected, and the indicator definition matches the data name and the data description. Construct a database based on the indicator definition table and the indicator value table; In response to a business data query command, determine the target data name and target data description that match the business data query command; In the database, determine a target indicator definition table that matches the target data name and the target data description, and a target indicator value table that matches the target indicator definition table; A business data query report matching the business data query instruction is generated based on the target indicator value table.

2. The business data query method according to claim 1, characterized in that, The response to the business data query instruction includes determining the target data name and target data description that match the business data query instruction, including: The business data query instruction is input into the large language model, which parses the business data query instruction to obtain the target data name and the target data description.

3. The business data query method according to claim 2, characterized in that, After the large language model parses the business data query instruction, the method further includes: The large language model is also used to obtain current time information and generate a query data time period corresponding to the business data query instruction based on the current time information; The step of determining a target indicator definition table that matches the target data name and the target data description in the database, and a target indicator value table that matches the target indicator definition table, includes: The large language model extracts the target indicator definition table from the database according to the target data name and the target data description, and extracts the target indicator value table from the database according to the query data time period.

4. The business data query method according to claim 3, characterized in that, The database also includes business scenario information that matches the data to be collected. The business scenario information includes at least the location, personnel, and organizational structure corresponding to the target business scenario. The step of extracting the target indicator value table from the database according to the time period of the query data includes: The target indicator value table is extracted from the database based on the query data time period and the business scenario information.

5. The business data query method according to claim 1, characterized in that, After generating a business data query report matching the business data query instruction based on the target indicator value table, the process further includes: Retrieve an open-source data query report from the open-source database that matches the target data name and the target data description; The final data query report is generated based on the business data query report and the open-source data query report.

6. The business data query method according to any one of claims 1 to 5, characterized in that, The indicator definition table also includes the maximum value, minimum value, and unit of the data to be collected; The step of collecting data in real time according to the indicator definition table to obtain an indicator value table matching the indicator definition table includes: Real-time data acquisition is performed according to the acquisition scheme and the acquisition frequency, and data smaller than the minimum value or larger than the maximum value are removed to obtain the index value table.

7. A business data query device, characterized in that, include: The module includes an acquisition module, a data collection module, a construction module, a first determination module, a second determination module, and a generation module. The acquisition module is used to acquire the indicator definition table of the data to be collected. The indicator definition table includes at least the data name, data description, collection scheme and collection frequency of the data to be collected. The data to be collected is the smallest unit of data collected corresponding to the target business scenario. The acquisition module is used to acquire data in real time according to the indicator definition table to obtain an indicator value table that matches the indicator definition table. The indicator value table includes at least the acquisition value of the data to be acquired and the corresponding acquisition time. The indicator value table also includes an indicator definition, which is used to describe the type of the data to be acquired, and the indicator definition matches the data name and the data description. The construction module is used to construct a database based on the indicator definition table and the indicator value table; The first determining module is used to respond to a business data query instruction and determine the target data name and target data description that match the business data query instruction; The second determining module is used to determine in the database a target indicator definition table that matches the target data name and the target data description, and a target indicator value table that matches the target indicator definition table; The generation module is used to generate a business data query report that matches the business data query instruction based on the target indicator value table.

8. An electronic device, the electronic device comprising a processor and a memory, characterized in that, The memory is used to store instructions, and the processor is used to call the instructions in the memory to cause the electronic device to execute the business data query method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed on an electronic device, cause the electronic device to perform the business data query method as described in any one of claims 1 to 6.

Images