Data generation method and device, computer equipment and storage medium

Abstract

The invention belongs to the technical field of artificial intelligence, and relates to a data generation method, which comprises the following steps: acquiring a to-be-processed business scene; performing demand decomposition on the business scene to obtain a corresponding demand decomposition result; based on the demand decomposition result, selecting a corresponding target function from a preset function library; sorting and combining the target functions to obtain a corresponding function logic diagram; executing processing on the function logic diagram to obtain corresponding target processing data; and outputting the target processing data. The invention further provides a data generation device, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and the target processing data can be stored in a block chain. The method can be applied to the financial science and technology field and the digital medical field, result calculation processing of the business scene can be automatically completed, the processing efficiency of result calculation of the business scene is effectively improved, and the accuracy of the obtained business scene is ensured.

Description

Technical Field

[0001] This application relates to the field of data processing technologies, and can be applied to fields such as fintech and digital healthcare. In particular, it relates to a data generation method, apparatus, computer device, and storage medium. Background Art

[0002] In some highly specialized fields, the complexity of business scenarios is increasing day by day. These scenarios often require highly refined data processing and logical operations. To address these challenges, the industry usually decomposes complex business logics into a series of independent minimum unit functions, and each function undertakes specific data processing or logical judgment tasks. Through a carefully designed function combination and execution process, these minimum units can work together to jointly calculate the results required by the business scenario.

[0003] In the financial field, complex business scenarios such as risk assessment, investment decision-making, and credit approval all involve comprehensive analysis and processing of multi-dimensional data such as a large amount of market data, user information, and transaction records. The functions in these scenarios may cover multiple links such as data cleaning, feature extraction, model prediction, and rule judgment, and each function is an indispensable part of the data processing process. Similarly, in the medical field, business scenarios such as disease diagnosis, patient management, and drug research and development also require highly specialized data processing and analysis. The functions in these scenarios may involve multiple aspects such as medical image analysis, gene sequence alignment, and physiological index monitoring, and each function carries specific medical knowledge and algorithm logic.

[0004] However, although these minimum unit functions play a crucial role in business scenarios, there is currently a lack of a unified and efficient function combination execution and management method in the industry. Existing solutions often rely on specific programming frameworks or toolchains, but these frameworks or toolchains have many limitations in function combination, execution scheduling, result aggregation, etc., resulting in problems of low processing efficiency and low accuracy in the process of calculating the results required by business scenarios, and it is difficult to meet the diverse needs in complex business scenarios. Summary of the Invention

[0005] The purpose of the embodiments of this application is to propose a data generation method, apparatus, computer device, and storage medium to solve the technical problems of low processing efficiency and low accuracy in the existing processing methods for calculating the results required by business scenarios.

[0006] In a first aspect, a data generation method is provided, including:

[0007] Obtain a business scenario to be processed;

[0008] Perform requirement decomposition on the business scenario to obtain a corresponding requirement decomposition result;

[0009] Based on the requirement decomposition result, select the corresponding target function from a preset function library;

[0010] Perform sorting and combination processing on the target function to obtain the corresponding function logic diagram;

[0011] Perform execution processing on the function logic diagram to obtain the corresponding target processing data;

[0012] Output the target processing data.

[0013] In a second aspect, a data generation device is provided, including:

[0014] An acquisition module, configured to acquire a business scenario to be processed;

[0015] A decomposition module, configured to perform requirement decomposition on the business scenario to obtain the corresponding requirement decomposition result;

[0016] A selection module, configured to select the corresponding target function from a preset function library based on the requirement decomposition result;

[0017] A processing module, configured to perform sorting and combination processing on the target function to obtain the corresponding function logic diagram;

[0018] An execution module, configured to perform execution processing on the function logic diagram to obtain the corresponding target processing data;

[0019] An output module, configured to output the target processing data.

[0020] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above data generation method are implemented.

[0021] In a fourth aspect, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above data generation method are implemented.

[0022] In the solution implemented by the above data generation method, apparatus, computer device, and storage medium, a business scenario to be processed can be obtained; then, the requirements of the business scenario are decomposed to obtain a corresponding requirements decomposition result; thereafter, based on the requirements decomposition result, a corresponding target function is selected from a preset function library; subsequently, sorting and combination processing are performed on the target function to obtain a corresponding function logic diagram; further, execution processing is performed on the function logic diagram to obtain a corresponding target processing data; and finally, the target processing data is output. In this application, by decomposing the requirements of the obtained business scenario to be processed to obtain a corresponding requirements decomposition result, selecting a corresponding target function from the preset function library based on the requirements decomposition result, then performing sorting and combination processing on the target function to obtain a corresponding function logic diagram, further performing execution processing on the function logic diagram to obtain a corresponding target processing data, and subsequently outputting the target processing data, through the data processing method for business scenarios adopted in this application, it is possible to automatically, quickly, and accurately complete the result calculation processing for business scenarios, effectively improving the processing efficiency of the result calculation for business scenarios and ensuring the accuracy of the obtained business scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] To more clearly illustrate the solutions in this application, the following will briefly introduce the drawings required for the description of the embodiments of this application. Obviously, the following-described drawings are some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0024] Figure 1 is an exemplary system architecture diagram to which this application can be applied;

[0025] Figure 2 is a flowchart according to an embodiment of the data generation method of this application;

[0026] Figure 3 is a schematic structural diagram according to an embodiment of the data generation apparatus of this application;

[0027] Figure 4 is a schematic structural diagram according to an embodiment of the computer device of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[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 terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above drawings are intended to cover non-exclusive inclusion. The terms "first", "second", etc. in the specification and claims of this application or the above drawings are used to distinguish different objects and not to describe a specific order.

[0029] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in connection with the embodiments can be included in at least one embodiment of the application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive of other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0030] To enable those skilled in the art to better understand the solution of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0031] As Figure 1 shown, the system architecture 100 may include a terminal device 101, a network 102, and a server 103. The terminal device 101 may be a laptop computer 1011, a tablet computer 1012, or a mobile phone 1013. The network 102 is a medium for providing a communication link between the terminal device 101 and the server 103. The network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0032] Users can use the terminal device 101 to interact with the server 103 through the network 102 to receive or send messages, etc. Various communication client applications may be installed on the terminal device 101, such as a web browser application, a shopping application, a search application, an instant messaging tool, an email client, a social platform software, etc.

[0033] The terminal device 101 can be various electronic devices with a display screen and supporting web browsing. In addition to the laptop 1011, tablet computer 1012, or mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop computer, a desktop computer, and so on.

[0034] The server 103 can be a server that provides various services, such as a background server that supports the pages displayed on the terminal device 101.

[0035] It should be noted that the data generation method provided in the embodiments of the present application is generally executed by the server / terminal device. Correspondingly, the data generation device is generally set in the server / terminal device.

[0036] It should be understood that Figure 1 the numbers of the terminal devices, networks, and servers in

[0037] Continue to refer to Figure 2 , which shows a flowchart of an embodiment of the data generation method according to the present application. According to different requirements, the order of the steps in this flowchart can be changed, and some steps can be omitted. The data generation method provided in the embodiments of the present application can be applied to any scenario that requires product recommendation. Then, this data generation method can be applied to the products in these scenarios. For example, product recommendation in the financial insurance field. The said data generation method includes the following steps:

[0038] Step S201, obtain the business scenario to be processed.

[0039] In this embodiment, the electronic device on which the data generation method runs (such as Figure 1The server / terminal device shown can obtain the business scenarios to be processed through wired connection or wireless connection. It should be noted that the above wireless connection methods can include, but are not limited to, 3G / 4G / 5G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other currently known or future-developed wireless connection methods. The execution subject of this application can specifically be a data generation system, which can be simply referred to as a system. This application can be applied to the data generation and processing process of business scenarios in the financial field or the medical field. Specifically, in the financial field, the above business scenarios to be processed can include personal financial report generation scenarios, loan approval process automation scenarios, credit card bill settlement scenarios, portfolio optimization recommendation scenarios, financial market trend prediction scenarios, and so on. Among them, the requirements of the personal financial report generation scenario include: obtaining user account information, calculating account balances, and summarizing investment returns, etc. The function combinations required for the personal financial report generation scenario include: getAccountInfo (obtain account information), calculateBalance (calculate balance), summarizeInvestmentReturns (summarize investment returns), etc. The requirements of the loan approval process automation scenario include: verifying user identity information, evaluating user credit ratings, calculating loan amounts, etc. The function combinations required for the loan approval process automation scenario include: verifyIdentity (verify identity information), evaluateCreditRating (evaluate credit rating), calculateLoanAmount (calculate loan amount), etc. The requirements of the credit card bill settlement scenario include: obtaining user consumption records, calculating the amount due, generating bill details, etc. The function combinations required for the credit card bill settlement scenario include: getTransactionHistory (obtain consumption records), calculateDueAmount (calculate the amount due), generateBillDetails (generate bill details), etc. The requirements of the portfolio optimization recommendation scenario are: analyzing user investment preferences, evaluating portfolio risks, recommending optimization plans, etc. The function combinations required for the portfolio optimization recommendation scenario include: analyzeInvestmentPreferences (analyze investment preferences), evaluatePortfolioRisk (evaluate portfolio risks), recommendOptimizationStrategy (recommend optimization strategies), etc. The requirements of the financial market trend prediction scenario include: collecting market data, analyzing historical trends, predicting future trends, etc.The function combinations required for the financial market trend prediction scenario include: collectMarketData (collect market data), analyzeHistoricalTrends (analyze historical trends), predictFutureMovements (predict future movements), etc.

[0040] In addition, in the medical field, the above-mentioned business scenarios to be processed may include patient medical record management scenarios, drug side effect monitoring scenarios, telemedicine consultation scenarios, chronic disease management plan formulation scenarios, and medical data visualization analysis scenarios. Among them, the requirements of the patient medical record management scenario include: collecting basic patient information, recording medical history, generating medical record reports, etc. The function combinations required for the patient medical record management scenario include: collectPatientInfo (collect patient information), recordVisitHistory (record medical history), generateMedicalRecord (generate medical record reports), etc. The requirements of the drug side effect monitoring scenario include: collecting patient medication information, monitoring drug side effects, generating monitoring reports, etc. The function combinations required for the drug side effect monitoring scenario include: collectMedicationInfo (collect medication information), monitorSideEffects (monitor drug side effects), generateMonitoringReport (generate monitoring reports), etc. The requirements of the telemedicine consultation scenario include: receiving patient consultation requests, matching professional doctors, recording consultation content, etc. The function combinations required for the telemedicine consultation scenario include: receiveConsultationRequest (receive consultation requests), matchDoctor (match professional doctors), recordConsultationContent (record consultation content), etc. The requirements of the chronic disease management plan formulation scenario include: analyzing the patient's health status, formulating management plans, tracking implementation progress, etc. The function combinations required for the chronic disease management plan formulation scenario include: analyzeHealthStatus (analyze health status), developManagementPlan (formulate management plans), trackProgress (track implementation progress), etc. The requirements of the medical data visualization analysis scenario include: collecting medical data, performing data cleaning, generating visualization charts, etc. The function combinations required for the medical data visualization analysis scenario include: collectMedicalData (collect medical data), cleanData (perform data cleaning), generateVisualizations (generate visualization charts), etc.

[0041] In addition, the business scenario information corresponding to the business scenario to be processed may include personnel information, budget information, project information, process information, etc.

[0042] Step S202: Decompose the requirements of the business scenario to obtain a corresponding requirements decomposition result.

[0043] In this embodiment, the specific implementation process of decomposing the requirements of the business scenario to obtain a corresponding requirements decomposition result will be further described in detail in the subsequent specific embodiments of this application, and will not be elaborated here too much.

[0044] Step S203: Based on the requirements decomposition result, select a corresponding target function from a preset function library.

[0045] In this embodiment, the specific implementation process of selecting a corresponding target function from a preset function library based on the requirements decomposition result will be further described in detail in the subsequent specific embodiments of this application, and will not be elaborated here too much.

[0046] Step S204: Sort and combine the target functions to obtain a corresponding function logic diagram.

[0047] In this embodiment, the specific implementation process of sorting and combining the target functions to obtain a corresponding function logic diagram will be further described in detail in the subsequent specific embodiments of this application, and will not be elaborated here too much.

[0048] Step S205: Execute the function logic diagram to obtain corresponding target processed data.

[0049] In this embodiment, the specific implementation process of executing the function logic diagram to obtain corresponding target processed data will be further described in detail in the subsequent specific embodiments of this application, and will not be elaborated here too much.

[0050] Step S206: Output the target processed data.

[0051] In this embodiment, the specific implementation process of outputting the target processed data will be further described in detail in the subsequent specific embodiments of this application, and will not be elaborated here too much.

[0052] This application first obtains the business scenario to be processed; then decomposes the requirements of the business scenario to obtain the corresponding requirement decomposition result; then selects the corresponding target function from a preset function library based on the requirement decomposition result; subsequently, performs sorting and combination processing on the target function to obtain the corresponding function logic diagram; further performs execution processing on the function logic diagram to obtain the corresponding target processing data; and finally outputs the target processing data. By decomposing the requirements of the obtained business scenario to be processed to obtain the corresponding requirement decomposition result, selecting the corresponding target function from the preset function library based on the requirement decomposition result, then performing sorting and combination processing on the target function to obtain the corresponding function logic diagram, further performing execution processing on the function logic diagram to obtain the corresponding target processing data, and subsequently outputting the target processing data, through the data processing method for the business scenario adopted in this application, it is possible to automatically, quickly, and accurately complete the result calculation processing for the business scenario, effectively improving the processing efficiency of the result calculation for the business scenario and ensuring the accuracy of the obtained business scenario.

[0053] In some alternative implementation manners, step S202 includes the following steps:

[0054] Decompose the requirements of the business scenario to obtain the corresponding data source and processing rule.

[0055] In this embodiment, by decomposing the requirements of the above-mentioned business scenario to be processed, the specific requirement points related to this business scenario can be determined, and the data source and corresponding processing rule matching the requirement points can be determined. The data source and corresponding processing rule matching the above-mentioned requirement points can be used to determine which functions need to be selected to combine and implement the business logic of this business scenario. The above-mentioned data source may refer to the data source used to complete this business scenario. The above-mentioned processing rule refers to the processing rules corresponding to multiple different source data.

[0056] Exemplarily, if the business scenario is "generating a monthly insurance consumption report for a user", the requirement points may include: obtaining user information, calculating the total monthly insurance consumption of the user, and counting the insurance categories consumed by the user, etc. Then the data sources matching the requirement points may include the data source of user information, the data source required for calculating the total monthly insurance consumption of the user, and the data source for counting the insurance categories consumed by the user. The processing rules matching the requirement points may include: the rule for obtaining user information, the calculation rule for calculating the total monthly insurance consumption of the user, and the statistical rule for counting the insurance categories consumed by the user.

[0057] Integrate and process the data source and the processing rule to obtain the corresponding integrated data.

[0058] In this embodiment, the above integrated data is data including the above data sources and processing rules.

[0059] Use the integrated data as the result of the requirement decomposition.

[0060] In this embodiment, the obtained result of the requirement decomposition can be further stored to ensure the data security of the result of the requirement decomposition and facilitate subsequent analysis and processing.

[0061] This application decomposes the requirements for the business scenario to obtain corresponding data sources and processing rules; then integrates and processes the data sources and the processing rules to obtain corresponding integrated data; subsequently, uses the integrated data as the result of the requirement decomposition. This application decomposes the requirements for the business scenario to obtain corresponding data sources and processing rules, and then integrates and processes the obtained data sources and processing rules, thereby enabling efficient and accurate completion of the requirement decomposition processing for the business scenario, improving the processing efficiency of the requirement decomposition for the business scenario, ensuring the accuracy of the obtained result of the requirement decomposition, and facilitating subsequent rapid and accurate selection of the required target function from the function library through the use of the result of the requirement decomposition.

[0062] In some alternative implementation manners of this embodiment, step S203 includes the following steps:

[0063] Obtain a preset retrieval strategy.

[0064] In this embodiment, there is no specific limitation on the selection of the above retrieval strategy, which can be determined according to actual business requirements. For example, it may include strategies corresponding to retrieval methods such as keyword search and classification screening.

[0065] Invoke the function library.

[0066] In this embodiment, for the construction process of the above function library, this application will further describe the details in subsequent specific embodiments and will not elaborate too much here.

[0067] Based on the retrieval strategy, retrieve a specified function that matches the result of the requirement analysis from the function library.

[0068] In this embodiment, according to the retrieval method corresponding to the above retrieval strategy, the function library can be retrieved for functions according to the result of the requirement analysis, so as to obtain a specified function that matches the result of the requirement analysis. Exemplarily, searching for "obtain user information" may find a function named "getUserInfoByUserId"; searching for "calculate total consumption" may find a function named "calculateTotalConsumption".

[0069] Take the specified function as the target function.

[0070] In this embodiment, the retrieved target functions are all function metadata related to the above business scenario, and the target functions meet the functional requirements and data source requirements of the above business scenario.

[0071] This application obtains a preset retrieval strategy; then calls the function library; then based on the retrieval strategy, retrieves the specified function that matches the result of requirement analysis from the function library; subsequently, takes the specified function as the target function. By obtaining a preset retrieval strategy and calling the function library, and then based on the use of the retrieval strategy, retrieving the specified function that matches the result of requirement analysis from the function library and taking it as the corresponding target function, this application can efficiently and accurately select the corresponding target function from the above function library, improve the retrieval efficiency of the target function, ensure the accuracy of the obtained target function, and is conducive to quickly and accurately constructing the corresponding function logic diagram based on the use of the target function in the subsequent process.

[0072] In some optional implementation manners, step S204 includes the following steps:

[0073] Obtain the processing rule corresponding to the business scenario.

[0074] In this embodiment, after decomposing the requirements of the above business scenario to obtain the corresponding requirement decomposition result, the corresponding processing rule can be further extracted from the requirement decomposition result.

[0075] Perform a sorting process on the target function based on the processing rule to obtain the sorted target function.

[0076] In this embodiment, the business logic corresponding to the above target function can be obtained according to the above processing rule, and then the execution order of all target functions and the data dependency relationship between them can be determined according to the business logic. For example, first call "getUserInfoByUserId" to obtain user information, then pass the user information as a parameter to "calculateTotalConsumption" to calculate the total consumption amount, and finally count the consumption categories. Subsequently, perform a sorting operation on the selected target functions according to the above execution order to obtain the corresponding sorting result, that is, the sorted target function. Among them, the sorting result determines the execution order of the target function and the data processing flow.

[0077] Perform a concatenation process on the sorted target function to obtain the corresponding initial function logic diagram.

[0078] In this embodiment, the sorted objective functions and their execution order can be presented graphically to form the corresponding function combination logic diagram, that is, the above-mentioned initial function logic diagram. Exemplarily, the initial function logic diagram can be displayed as a flowchart, which includes three main steps: user information acquisition, total consumption calculation, and consumption category statistics.

[0079] Perform a verification process on the initial function logic diagram.

[0080] In this embodiment, after the series connection is completed and the initial function logic diagram is obtained, the initial function logic diagram can be further audited, which specifically includes ensuring that the logic of the initial function logic diagram is correct and meets the business requirements. Exemplarily, it can be checked whether all necessary functions are included in the initial function logic diagram, whether the execution order of the functions is correct, and whether the data transfer between the functions is error-free. In addition, the above-mentioned initial function logic diagram can be adjusted and optimized as needed.

[0081] If the initial function logic diagram passes the verification, use the initial function logic diagram as the function logic diagram.

[0082] In this embodiment, if the logic of the above-mentioned initial function logic diagram is correct and meets the business requirements, it is determined that the initial function logic diagram passes the verification, and then the initial function logic diagram is used as the function logic diagram.

[0083] In addition, the generated function logic diagram can be displayed through the system page or other visualization tools to facilitate developers' understanding and use. Exemplarily, developers can see the real-time display of the logic diagram on the system page and adjust or optimize the function combination through operations such as clicking or dragging.

[0084] This application obtains the processing rules corresponding to the business scenario; then sorts the objective function based on the processing rules to obtain the sorted objective function; then concatenates the sorted objective function to obtain the corresponding initial function logic diagram; subsequently, performs a verification process on the initial function logic diagram; if the initial function logic diagram passes the verification, the initial function logic diagram is used as the function logic diagram. This application obtains the processing rules corresponding to the business scenario, then sorts the objective function based on the use of the processing rules to obtain the sorted objective function, and further concatenates the sorted objective function to obtain the corresponding initial function logic diagram. When it is detected that the initial function logic diagram passes the verification, the initial function logic diagram is used as the function logic diagram, so that the sorting and combination processing of the objective function can be automatically and intelligently completed, and the accuracy of the generated function logic diagram can be ensured, and it is beneficial to subsequently perform an execution process on the function logic diagram, so that the required target processing data can be automatically and accurately obtained.

[0085] In some alternative implementation manners, step S205 includes the following steps:

[0086] Call a preset processing environment.

[0087] In this embodiment, the above-mentioned processing environment may specifically be an online environment.

[0088] Deploy the function logic diagram to the processing environment.

[0089] In this embodiment, the generated function logic diagram can be deployed to the above-mentioned processing environment, and can be further executed by triggering events (such as scheduled tasks, user requests, etc.). Exemplarily, a scheduled task can be set to automatically trigger the execution of the logic diagram at the beginning of each month to generate a user consumption report for the previous month.

[0090] Based on a preset trigger event, trigger the execution process of the function logic diagram in the processing environment and obtain the execution result after the execution is completed.

[0091] In this embodiment, during the execution process of the above-mentioned function logic diagram, the system will perform data processing and calculation according to the function order and data flow defined in the above-mentioned function logic diagram, and after the execution is completed, the corresponding execution result will be obtained, that is, the specific data required for the above-mentioned business scenario, that is, the above-mentioned target processing data. Among them, the function logic diagram can be executed in an online environment, and the functions are executed sequentially from left to right.

[0092] Use the execution result as the target processing data.

[0093] This application calls a preset processing environment; then deploys the function logic diagram to the processing environment; then triggers the execution processing of the function logic diagram in the processing environment based on a preset trigger event, and obtains the execution result after the execution is completed; subsequently, uses the execution result as the target processing data. By calling a preset processing environment and deploying the function logic diagram to the processing environment, and then triggering the execution processing of the function logic diagram in the processing environment based on the trigger event, this application can quickly and accurately generate the corresponding target processing data, effectively improving the generation efficiency of the target processing data and ensuring the data accuracy of the obtained target processing data.

[0094] In some optional implementation manners of this embodiment, step S206 includes the following steps:

[0095] Obtain a preset adjustment strategy.

[0096] In this embodiment, the content of the adjustment strategy includes: ensuring that the output data meets the requirements and format requirements of the business scenario.

[0097] Perform adjustment processing on the target processing data based on the adjustment strategy to obtain the corresponding output data.

[0098] In this embodiment, the above target data can be subjected to matching adjustment processing according to the content of the above adjustment strategy, so as to obtain output data that meets the requirements and format requirements of the above business scenario.

[0099] Obtain a preset target output method.

[0100] In this embodiment, there is no specific limitation on the selection of the above target output method, and it can be selected according to actual business needs. For example, it can include various forms of data output methods such as email sending and Excel file downloading.

[0101] Send the output data to relevant personnel based on the target output method.

[0102] In this embodiment, the above relevant personnel can be a designated user or a designated team corresponding to the above business scenario. The output data can be sent to relevant personnel by adopting the above target output method.

[0103] This application obtains a preset adjustment strategy; then adjusts and processes the target processing data based on the adjustment strategy to obtain corresponding output data; then obtains a preset target output method; subsequently, based on the target output method, sends the output data to relevant personnel. After the function logic diagram is executed to obtain the corresponding target processing data, this application will intelligently adjust and process the target data based on the use of the adjustment strategy to obtain the corresponding output data, improving the compliance and accuracy of the obtained output data. Furthermore, based on the obtained target output method, the output data is sent to relevant personnel, thereby improving the output intelligence of the output data and facilitating the improvement of the usage experience of relevant personnel.

[0104] In some alternative implementation manners of this embodiment, before step S203, the above electronic device may further execute the following steps:

[0105] Call a preset function collector.

[0106] In this embodiment, the above function collector is a pre-constructed scanning tool for scanning source code files in a code library. This tool has the ability to parse source code files and can identify the locations and relevant information of function definitions. Among them, in the source code, specific tags are added to the functions to be collected in advance according to actual business requirements, such as annotation tags.

[0107] Among them, complex business logics can be split into the smallest, independent, and reusable smallest function units. Ensure that each function is as fine-grained as possible, provide dynamic parameters to improve reusability and scalability, and the function names are clear and the functions have single and clear functions. Among them, the use of basic functions is very frequent. If the function splitting is fine enough, in the most ideal scenario where the function already exists, all the logics required for the business can be obtained only by using the combination of functions. Exemplarily, for the function of calculating the length of service of an employee, the input parameters can calculate the data of employees in dimensions such as internal establishment, external establishment, and architecture according to the entry and exit times, whether it is an internal establishment or an external establishment, and the architecture information, etc.

[0108] Specifically, the process of function definition includes: 1. Requirement analysis: First, it is necessary to conduct an in-depth analysis of the business logic to identify the smallest functional units that can be isolated. These functional units should have clear inputs and outputs and a single function, making them convenient for reuse. 2. Function design: Based on the results of the requirement analysis, design each minimum unit function. The design of the function should consider the dynamics and scalability of the parameters to enable flexible use in different business scenarios. 3. Naming convention: Establish a clear naming convention for the functions to ensure that the function names can accurately reflect their functions. At the same time, the naming should also follow certain rules for subsequent function management and retrieval. 4. Documentation writing: Write detailed documentation for each function, including function descriptions, parameter explanations, return values, and usage examples. These documents will serve as important references for subsequent development and use.

[0109] Based on the function collector, function scanning is performed on the source code files in the preset code library to obtain corresponding function metadata.

[0110] In this embodiment, the function collector can identify specific tags in the above-mentioned code library and extract function metadata corresponding to the specific tags.

[0111] Classify the function metadata to obtain classified function metadata.

[0112] In this embodiment, the process of classifying the function metadata may include: formulating standards and rules for function classification in advance. These standards and rules can be formulated according to business requirements and function functions to ensure the rationality and accuracy of classification. Then, classify the functions according to the formulated classification standards and rules. The classification results will serve as important bases for subsequent function retrieval and use. In addition, after classification, further review and adjustment work are carried out on the classified function metadata. This includes checking the accuracy and rationality of the classification results and making necessary adjustments and optimizations as needed.

[0113] In addition, the process of classifying the function metadata may also include: the function writer proposes function classification and others review it. Among them, the classification includes but is not limited to data operation classes, data conversion classes, data aggregation classes, business source data classes, printing classes, Excel export classes, email classes, etc.

[0114] Enter the classified function metadata into the preset database to obtain the function library.

[0115] In this embodiment, the above database is a library with efficient data storage and retrieval capabilities, which can facilitate subsequent function management and use. Among them, the classified function metadata can be entered into the above database by manual entry or automated import, thereby completing the construction of the function library.

[0116] This application calls a preset function collector; then based on the function collector, it scans the source code files in the preset code library to obtain corresponding function metadata; then classifies the function metadata to obtain classified function metadata; subsequently, the classified function metadata is entered into a preset database to obtain the function library. This application calls a preset function collector, scans the source code files in the preset code library based on the use of the function collector to obtain corresponding function metadata, then classifies the function metadata to obtain classified function metadata, and further enters the classified function metadata into a preset database to obtain the function library, thereby enabling the efficient and accurate completion of the construction of the function library and effectively improving the construction efficiency and accuracy of the function library.

[0117] In some alternative implementation manners, the obtained user information has obtained the consent of the user and complies with the provisions of relevant laws and relevant policies.

[0118] In addition, the non-company software tools or components that appear in the embodiments of this application are only introduced by way of example and do not represent actual use.

[0119] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0120] It should be emphasized that to further ensure the privacy and security of the above target processing data, the above target processing data can also be stored in a node of a blockchain.

[0121] The blockchain referred to in this application is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, and encryption algorithms. Blockchain, in essence, is a decentralized database, a string of data blocks generated by using cryptographic methods. Each data block contains information about a batch of network transactions, which is used to verify the validity (anti-counterfeiting) of the information and generate the next block. The blockchain can include a blockchain underlying platform, a platform product service layer, and an application service layer, etc.

[0122] Embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to obtain the best results.

[0123] Artificial intelligence basic technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, and mechatronics. Artificial intelligence software technologies mainly include several major directions such as computer vision technology, robotics, biometric technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0124] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through computer-readable instructions. These computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, Read-Only Memory (ROM), or a Random Access Memory (RAM), etc.

[0125] It should be understood that although the steps in the flowchart of the accompanying drawings are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same moment, but can be executed at different moments, and their execution order is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

[0126] Further reference Figure 3 to Figure 2 As an implementation of the method shown above, an embodiment of a data generation device is provided in the present application. This device embodiment corresponds to the method embodiment shown in Figure 2 and this device can be specifically applied to various electronic devices.

[0127] Such as Figure 3As shown in the figure, the data generation device 300 in this embodiment includes: an acquisition module 301, a decomposition module 302, a selection module 303, a processing module 304, an execution module 305, and an output module 306. Among them:

[0128] The acquisition module 301 is used to acquire the business scenario to be processed;

[0129] The decomposition module 302 is used to decompose the requirements of the business scenario to obtain the corresponding requirement decomposition result;

[0130] The selection module 303 is used to select the corresponding target function from the preset function library based on the requirement decomposition result;

[0131] The processing module 304 is used to perform sorting and combination processing on the target function to obtain the corresponding function logic diagram;

[0132] The execution module 305 is used to perform execution processing on the function logic diagram to obtain the corresponding target processing data;

[0133] The output module 306 is used to output the target processing data.

[0134] In this embodiment, the operations respectively performed by the above modules or units correspond one by one to the steps of the data generation method in the foregoing embodiment, and will not be elaborated herein.

[0135] In some optional implementation manners of this embodiment, the decomposition module 302 includes:

[0136] The decomposition sub-module is used to decompose the requirements of the business scenario to obtain the corresponding data source and processing rule;

[0137] The integration sub-module is used to perform integration processing on the data source and the processing rule to obtain the corresponding integration data;

[0138] The first determination sub-module is used to use the integration data as the requirement decomposition result.

[0139] In this embodiment, the operations respectively performed by the above modules or units correspond one by one to the steps of the data generation method in the foregoing embodiment, and will not be elaborated herein.

[0140] In some optional implementation manners of this embodiment, the selection module 303 includes:

[0141] The first acquisition sub-module is used to acquire the preset retrieval strategy;

[0142] The first call sub-module is used to call the function library;

[0143] A retrieval sub-module, configured to retrieve a specified function that matches the result of requirement analysis from the function library based on the retrieval strategy;

[0144] A second determination sub-module, configured to use the specified function as the target function.

[0145] In this embodiment, the operations respectively performed by the above-mentioned modules or units correspond one by one to the steps of the data generation method in the foregoing embodiment, and will not be elaborated herein.

[0146] In some alternative implementation manners of this embodiment, the processing module 304 includes:

[0147] A second acquisition sub-module, configured to acquire the processing rule corresponding to the service scenario;

[0148] A sorting sub-module, configured to perform a sorting process on the target function based on the processing rule to obtain a sorted target function;

[0149] A concatenation sub-module, configured to perform a concatenation process on the sorted target function to obtain a corresponding initial function logic diagram;

[0150] A verification sub-module, configured to perform a verification process on the initial function logic diagram;

[0151] A third determination sub-module, configured to use the initial function logic diagram as the function logic diagram if the initial function logic diagram passes the verification.

[0152] In this embodiment, the operations respectively performed by the above-mentioned modules or units correspond one by one to the steps of the data generation method in the foregoing embodiment, and will not be elaborated herein.

[0153] In some alternative implementation manners of this embodiment, the execution module 305 includes:

[0154] A second call sub-module, configured to call a preset processing environment;

[0155] A deployment sub-module, configured to deploy the function logic diagram to the processing environment;

[0156] A processing sub-module, configured to trigger an execution process on the function logic diagram in the processing environment based on a preset trigger event and obtain an execution result after the execution is completed;

[0157] A fourth determination sub-module, configured to use the execution result as the target processing data.

[0158] In this embodiment, the operations respectively performed by the above-mentioned modules or units correspond one by one to the steps of the data generation method in the foregoing embodiment, and will not be elaborated herein.

[0159] In some alternative implementation manners of this embodiment, the output module 306 includes:

[0160] A third acquisition sub-module, configured to acquire a preset adjustment policy;

[0161] An adjustment sub-module, configured to perform adjustment processing on the target processed data based on the adjustment policy to obtain corresponding output data;

[0162] A fourth acquisition sub-module, configured to acquire a preset target output manner;

[0163] A sending sub-module, configured to send the output data to relevant personnel based on the target output manner.

[0164] In this embodiment, the operations respectively performed by the foregoing modules or units correspond one by one to the steps of the data generation method in the foregoing embodiment, and will not be elaborated herein.

[0165] In some alternative implementation manners of this embodiment, the data generation device further includes:

[0166] A calling module, configured to call a preset function collector;

[0167] A scanning module, configured to perform function scanning on source code files in a preset code library based on the function collector to obtain corresponding function metadata;

[0168] A classification module, configured to perform classification processing on the function metadata to obtain classified function metadata;

[0169] An input module, configured to input the classified function metadata into a preset database to obtain the function library.

[0170] In this embodiment, the operations respectively performed by the foregoing modules or units correspond one by one to the steps of the data generation method in the foregoing embodiment, and will not be elaborated herein.

[0171] To solve the above technical problems, an embodiment of the present application further provides a computer device. For details, please refer to Figure 4 , Figure 4 which is the basic structural block diagram of the computer device in this embodiment.

[0172] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are communicatively connected to each other via a system bus. It should be noted that only the computer device 4 with components 41-43 is shown in the figure, but it should be understood that it is not required to implement all the shown components, and more or fewer components can be alternatively implemented. Among them, those skilled in the art of this technology can understand that a computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0173] The computer device can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The computer device can perform human-computer interaction with the user through means such as a keyboard, a mouse, a remote control, a touchpad, or a voice control device.

[0174] The memory 41 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, a hard disk, a multimedia card, a card-type memory (such as an SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device 4. Of course, the memory 41 may also include both the internal storage unit and the external storage device of the computer device 4. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions of the data generation method. In addition, the memory 41 can also be used to temporarily store various data that have been output or will be output.

[0175] In some embodiments, the processor 42 may be a Central Processing Unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run the computer-readable instructions stored in the memory 41 or process data, such as running the computer-readable instructions of the data generation method.

[0176] The network interface 43 may include a wireless network interface or a wired network interface, and this network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0177] Compared with the prior art, the embodiments of the present application mainly have the following beneficial effects:

[0178] In the embodiments of the present application, the present application first obtains the service scenario to be processed; then decomposes the requirements of the service scenario to obtain the corresponding requirement decomposition result; then based on the requirement decomposition result, selects the corresponding target function from the preset function library; subsequently performs sorting and combination processing on the target function to obtain the corresponding function logic diagram; further performs execution processing on the function logic diagram to obtain the corresponding target processing data; and finally outputs the target processing data. By decomposing the requirements of the obtained service scenario to be processed to obtain the corresponding requirement decomposition result, selecting the corresponding target function from the preset function library based on the requirement decomposition result, then performing sorting and combination processing on the target function to obtain the corresponding function logic diagram, and then performing execution processing on the function logic diagram to obtain the corresponding target processing data, and subsequently outputting the target processing data, through the data processing method for the service scenario adopted by the present application, it is possible to automatically, quickly, and accurately complete the result calculation processing for the service scenario, effectively improving the processing efficiency of the result calculation of the service scenario and ensuring the accuracy of the obtained service scenario.

[0179] The present application also provides another implementation manner, that is, to provide a computer-readable storage medium storing computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to execute the steps of the data generation method as described above.

[0180] Compared with the prior art, the embodiments of the present application mainly have the following beneficial effects:

[0181] In the embodiments of the present application, the present application first obtains a business scenario to be processed; then decomposes the requirements of the business scenario to obtain a corresponding requirement decomposition result; then selects a corresponding target function from a preset function library based on the requirement decomposition result; subsequently performs sorting and combination processing on the target function to obtain a corresponding function logic diagram; further performs execution processing on the function logic diagram to obtain a corresponding target processing data; and finally outputs the target processing data. By decomposing the requirements of the obtained business scenario to be processed to obtain a corresponding requirement decomposition result, selecting a corresponding target function from a preset function library based on the requirement decomposition result, then performing sorting and combination processing on the target function to obtain a corresponding function logic diagram, further performing execution processing on the function logic diagram to obtain a corresponding target processing data, and subsequently outputting the target processing data, through the data processing method for the business scenario adopted by the present application, it is possible to automatically, quickly and accurately complete the result calculation processing for the business scenario, effectively improving the processing efficiency of the result calculation of the business scenario and ensuring the accuracy of the obtained business scenario.

[0182] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions for causing a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in the various embodiments of the present application.

[0183] Obviously, the above-described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The accompanying drawings show the preferred embodiments of the present application, but do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosed content of the present application more thorough and comprehensive. Although the present application has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions described in the foregoing specific embodiments, or perform equivalent replacements on some of the technical features. Any equivalent structure directly or indirectly using the content of the specification and drawings of the present application in other related technical fields shall be within the scope of the patent protection of the present application by the same token.

Claims

1. A data generation method, characterized in that: The steps include: Get the business scenarios to be processed; Decomposing the business scenario to obtain the corresponding demand decomposition result; Based on the requirement decomposition result, a corresponding objective function is selected from a preset function library; Sorting and combining the objective functions to obtain a corresponding function logic diagram; Execute the function logic diagram to obtain corresponding target processing data; The target processed data is outputted.

2. The data generation method according to claim 1, characterized in that: The step of performing requirement decomposition on the business scenario to obtain a corresponding requirement decomposition result specifically includes: Decompose the business scenarios to obtain corresponding data sources and processing rules; Integrate the data source and the processing rules to obtain corresponding integrated data; The integrated data is used as the demand decomposition result.

3. The data generation method according to claim 1, characterized in that: The step of selecting a corresponding objective function from a preset function library based on the demand decomposition result specifically includes: Get the preset search strategy; Calling the function library; Based on the search strategy, a specified function matching the requirement analysis result is retrieved from the function library; The specified function is used as the target function.

4. The data generation method according to claim 2, characterized in that: The step of sorting and combining the target functions to obtain a corresponding function logic diagram specifically includes: Obtaining the processing rule corresponding to the business scenario; Sorting the objective function based on the processing rule to obtain a sorted objective function; The sorted objective functions are serially processed to obtain a corresponding initial function logic diagram; Performing verification processing on the initial function logic diagram; If the initial function logic diagram passes the verification, the initial function logic diagram is used as the function logic diagram.

5. The data generation method according to claim 1, characterized in that: The step of executing the function logic diagram to obtain corresponding target processing data specifically includes: Call the preset processing environment; deploying the function logic graph into the processing environment; Triggering the execution of the function logic graph in the processing environment based on a preset trigger event, and obtaining an execution result after the execution is completed; The execution result is used as the target processing data.

6. The data generation method according to claim 1, characterized in that: The step of outputting the target processed data specifically includes: Get the preset adjustment strategy; Based on the adjustment strategy, the target processing data is adjusted to obtain corresponding output data; Get the preset target output mode; Based on the target output mode, the output data is sent to relevant personnel.

7. The data generation method according to claim 1, characterized in that: Before the step of selecting a corresponding objective function from a preset function library based on the demand decomposition result, the method further includes: Call the preset function collector; Based on the function collector, a function scan is performed on the source code files in the preset code library to obtain corresponding function metadata; Classifying the function metadata to obtain classified function metadata; The classified function metadata is entered into a preset database to obtain the function library.

8. A data generating device, characterized in that: include: The acquisition module is used to obtain the business scenarios to be processed; A decomposition module, used to perform demand decomposition on the business scenario to obtain corresponding demand decomposition results; A selection module, used to select a corresponding objective function from a preset function library based on the demand decomposition result; A processing module, used for sorting and combining the target functions to obtain a corresponding function logic diagram; An execution module, used to execute the function logic diagram to obtain corresponding target processing data; An output module is used to output the target processed data.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the data generating method according to any one of claims 1 to 7 when executing the computer-readable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the data generation method according to any one of claims 1 to 7 are implemented.

Images