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

Abstract

The embodiment of the invention discloses a business data development method and device, electronic equipment and a storage medium. The method comprises the following steps: for to-be-developed business data, obtaining a description text of a business demand which needs to be met by the business data; obtaining a natural language processing tool obtained through pre-learning; and inputting the description text into a natural language processing tool, and obtaining a technical aperture corresponding to the business demand according to an output result of the natural language processing tool, so as to develop business data based on the technical aperture. According to the technical scheme provided by the embodiment of the invention, the natural language processing tool is utilized, the service demand is automatically converted into the technical aperture, and the service data development is realized based on the technical aperture, so that the development process does not need to involve multiple parties, and the whole development link is short, thereby improving the development efficiency of the service data.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of computers, and in particular, to a method, apparatus, electronic device, and storage medium for business data development. Background Art

[0002] To effectively carry out business and achieve business data development is crucial.

[0003] In the process of implementing the present invention, the inventors found the following technical problems in the prior art: The currently adopted business data development solutions usually involve multiple handlers, which results in a long development link and thus low development efficiency, and there is room for improvement. Summary of the Invention

[0004] Embodiments of the present invention provide a method, apparatus, electronic device, and storage medium for business data development to achieve efficient development of business data.

[0005] According to one aspect of the present invention, a method for business data development is provided, which may include:

[0006] For the business data to be developed, obtain the description text of the business requirements that the business data needs to meet;

[0007] Obtain the pre-learned natural language processing tool;

[0008] Input the description text into the natural language processing tool, and based on the output result of the natural language processing tool, obtain the technical specifications corresponding to the business requirements, so as to develop business data based on the technical specifications.

[0009] According to another aspect of the present invention, a device for business data development is provided, which may include:

[0010] A description text acquisition module, configured to obtain the description text of the business requirements that the business data needs to meet for the business data to be developed;

[0011] A natural language processing tool acquisition module, configured to obtain the pre-learned natural language processing tool;

[0012] A business data development module, configured to input the description text into the natural language processing tool, and based on the output result of the natural language processing tool, obtain the technical specifications corresponding to the business requirements, so as to develop business data based on the technical specifications.

[0013] According to another aspect of the present invention, an electronic device is provided, which may include:

[0014] At least one processor; and

[0015] A memory communicatively connected to at least one processor; wherein,

[0016] The memory stores a computer program executable by at least one processor. When the computer program is executed by at least one processor, at least one processor is caused to implement the service data development method provided in any embodiment of the present invention.

[0017] According to another aspect of the present invention, there is provided a computer-readable storage medium having computer instructions stored thereon, and the computer instructions are used to cause a processor to implement the service data development method provided in any embodiment of the present invention when executed.

[0018] In the technical solution of the embodiment of the present invention, for the service data to be developed, by obtaining the description text of the service requirements that the service data needs to meet, and obtaining the pre-learned natural language processing tool; then, inputting the description text into the natural language processing tool, and according to the output result of the natural language processing tool, obtaining the technical caliber corresponding to the service requirements, so as to develop the service data based on the technical caliber. The above technical solution automatically transforms the service requirements into the technical caliber by using the natural language processing tool, and realizes the development of service data based on the technical caliber. This development process does not need to involve multiple handling personnel, and the entire development link is short, thereby improving the development efficiency of service data.

[0019] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0021] Figure 1 is a flowchart of a service data development method provided according to an embodiment of the present invention;

[0022] Figure 2 is a comparative schematic diagram of a development link in a service data development method provided according to an embodiment of the present invention;

[0023] Figure 3 is a flowchart of another service data development method provided according to an embodiment of the present invention;

[0024] Figure 4It is a schematic diagram of an optional example in another business data development method provided by an embodiment of the present invention;

[0025] Figure 5 It is a flowchart of yet another business data development method provided by an embodiment of the present invention;

[0026] Figure 6 It is a comparative schematic diagram of the development process in yet another business data development method provided by an embodiment of the present invention;

[0027] Figure 7 It is a structural block diagram of a business data development device provided by an embodiment of the present invention;

[0028] Figure 8 It is a schematic diagram of the structure of an electronic device for implementing the business data development method of an embodiment of the present invention. Detailed implementation manners

[0029] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. The situations of "target", "original", etc. are similar and will not be repeated here. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily need to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0031] Figure 1The figure is a flowchart of a business data development method provided in an embodiment of the present invention. This embodiment is applicable to the situation where business requirements are automatically transformed into technical specifications by using natural language processing tools, and business data development is realized based on this. This method can be executed by a business data development device provided in an embodiment of the present invention. The device can be implemented in software and / or hardware, and can be integrated on an electronic device, which can be various user terminals or servers.

[0032] See Figure 1 , the method of the embodiment of the present invention specifically includes the following steps:

[0033] S110. For the business data to be developed, obtain the description text of the business requirements that the business data needs to meet.

[0034] Among them, business data can be understood as the data to be developed in the target business. Combining the application scenarios that the embodiment of the present invention may involve, the target business can be, for example, a warehousing business, a logistics business, or an e-commerce business, etc. The business data can be, for example, business metrics or business models (i.e., data tables), etc. It should be noted that the above business data can be offline data or real-time data, which is related to the actual situation and is not specifically limited here. Exemplarily, when the business data represents the quantity of goods shipped on the (T - 1)th day counted on the Tth day, the business data is offline data; correspondingly, when the business data represents the stock change trend analyzed based on real-time transaction data, the business data is real-time data.

[0035] Business requirements can be understood as the requirements that business data needs to meet. That is, in actual applications, business requirements can be proposed first, and then business data can be developed according to the business requirements. The description text can be understood as the text used to describe business requirements. To obtain the description text, in actual applications, optionally, the description text can be obtained through input by relevant personnel, and the relevant personnel can be business personnel or technical R & D personnel.

[0036] S120. Obtain the natural language processing tool pre-learned in advance.

[0037] Among them, the natural language processing (NLP) tool can be understood as a tool for implementing natural language processing. Combining the application scenarios that the embodiment of the present invention may involve, the natural language processing tool is pre-learned and specifically used to identify the description text, so as to transform the description text into technical specifications. On this basis, optionally, the natural language processing tool can also be used to implement interactive question and answer.

[0038] S130. Input the description text into a natural language processing tool, and based on the output result of the natural language processing tool, obtain the technical specifications corresponding to the business requirements, so as to develop business data based on the technical specifications.

[0039] Among them, the technical specifications correspond to the business requirements, and can be understood as the specifications used to guide machines or personnel to develop business data that meets the business requirements. Exemplarily, here taking the business data as the on-time delivery backlog rate of the pharmaceutical private network as an example, the following examples of technical specifications are given:

[0040] Data source: Routing system (for reference: XX)

[0041] Data range: The fleet type is the cold chain pharmaceutical fleet (for reference: YY)

[0042] Statistical date: The on-time delivery date of the routing dynamic plan (Note: The dynamic time is variable, and business personnel can be reminded whether to confirm the use of this date)

[0043] Statistical area: The planned on-time delivery area

[0044] Statistical dimension: The number of orders

[0045] Numerator:

[0046] Statistical logic: AA

[0047] Denominator:

[0048] Statistical logic: BB.

[0049] Input the description text into the natural language processing tool, so that the description text can be recognized by the natural language processing tool to obtain the technical specifications. Further, after obtaining the technical specifications based on the output result of the natural language processing tool, business data can be developed based on the technical specifications. Combining with the application scenarios that the embodiments of the present invention may involve, specifically, it can be the implementation logic (such as processing logic, etc.) of developing business data. In practical applications, optionally, the above process of developing business data based on technical specifications can be automatically implemented by machines, manually implemented by personnel, or implemented in cooperation between machines and personnel, etc., which is not specifically limited herein.

[0050] It should be noted that, see Figure 2, the currently adopted business data development solution involves multiple handling personnel, which leads to a relatively long development chain and thus low development efficiency. Exemplarily, the multiple handling personnel may include business personnel - business BP - technical BP - technical R & D personnel. Here, BP is short for business partner. On this basis, the overall development chain is as follows: First, the business personnel describe their business requirements to the business BP; then, the business BP converts the business requirements into business terms and submits them to the technical BP; then, the technical BP converts the business terms into technical terms and submits them to the technical R & D personnel. Finally, the technical R & D personnel conduct business data development based on the technical terms.

[0051] In contrast, the business data development solution described in the embodiments of the present invention only involves business personnel and technical R & D personnel. The business personnel put forward their business requirements, then use natural language processing tools to obtain the technical terms corresponding to the business requirements, and finally the technical R & D personnel conduct business data development based on the technical terms. It can be seen that the above business data development solution significantly improves the development efficiency of business data by shortening the entire development chain; moreover, it can avoid the situation of omission or error of business requirements caused by multiple retellings of business requirements, thus ensuring the accurate development of business data.

[0052] The technical solution of the embodiments of the present invention, for the business data to be developed, obtains the description text of the business requirements that the business data needs to meet, and obtains the pre-learned natural language processing tool; then, inputs the description text into the natural language processing tool, and according to the output result of the natural language processing tool, obtains the technical terms corresponding to the business requirements, so as to develop business data based on the technical terms. The above technical solution automatically transforms business requirements into technical terms by using natural language processing tools and realizes business data development based on the technical terms. This development process does not need to involve multiple handling personnel, and the entire development chain is relatively short, thereby improving the development efficiency of business data.

[0053] An optional technical solution is that the natural language processing tool is pre-learned based on the business information of the target business to which the business data belongs. Then, inputting the description text into the natural language processing tool and obtaining the technical terms corresponding to the business requirements according to the output result of the natural language processing tool includes:

[0054] Identifying the business information through the natural language processing tool to obtain the description text;

[0055] Inputting the description text into the natural language processing tool to generate and output the technical terms corresponding to the business requirements;

[0056] Obtaining the technical terms according to the output result of the natural language processing tool.

[0057] Among them, the target business can be understood as the business to which the business data belongs, that is, the business data is the data in the target business. The business information can be understood as the information used to describe the target business. Combining the application scenarios that may be involved in the embodiments of the present invention, the business information can be the information indicating the model situation of the existing business models in the data warehouse, such as metadata, model fields, partitions, model descriptions, and data volume, etc.; it can be the information used to connect with the target business, such as the source business system and the system person in charge, etc.; it can be the information that facilitates the users of the business model to quickly learn how to use the business model, such as model granularity, applicable scenarios, and granularity confirmation methods, etc.; it can also be the information used to explain some business terms in the target business, such as the waybill has been closed-loop, which means that the waybill has been completed in the business process. In addition to normal delivery, operations such as scrapping, order cancellation, interception success, and rejection also indicate that the waybill has been completed in the business process, mainly referring to that there will be no further operations for this waybill. For details, please refer to the waybill status information list; of course, it can also be the rest of the information used to describe the target business, which is not specifically limited here.

[0058] Since the natural language processing tool is pre-learned based on the business information, and the business information can be used to describe the target business to which the business data belongs, the business information can be identified through the natural language processing tool to obtain the description text for describing the business requirements that the business data needs to meet; then, the description text is input into the natural language processing tool, so that the natural language processing tool can identify the description text, generate the technical caliber corresponding to the business requirements, and output the technical caliber. On this basis, the corresponding technical caliber can be obtained according to the output result of the natural language processing tool.

[0059] For the above technical solution, the natural language processing tool can be pre-learned based on the business information, that is, the natural language processing tool is pre-trained by using the business information. Since the business information is used to describe the target business and the business data belongs to the target business, by using the natural language processing tool based on the business information, the accurate transformation from business requirements to technical caliber can be realized, thus ensuring the accuracy of business data development.

[0060] Another alternative technical solution is to input the description text into the natural language processing tool and obtain the technical caliber corresponding to the business requirements according to the output result of the natural language processing tool, including:

[0061] Input the description text into the natural language processing tool to identify the description text through the natural language processing tool, obtain the business model that matches the business requirements, check the usability of the business model, and generate and output the technical caliber corresponding to the business requirements according to the usability;

[0062] Based on the output result of the natural language processing tool, the technical scope is obtained.

[0063] Among them, the business model matches the business requirements, which can be understood as the data sources involved in the process of business data development. Input the description text into the natural language processing tool, so that through the natural language processing tool, the description text can be recognized to obtain the business model, and the usability of the business model can be verified, that is, to verify whether the business model is available in the process of business data development, and then generate the technical scope according to the usability, for example, generate the technical scope according to the available business model, so as to successfully develop business data based on the technical scope.

[0064] The above technical solution can automatically verify the usability of the business model through the natural language processing tool without manual verification by the technical BP, thereby avoiding the situation that different technical BPs repeatedly verify the usability of the same business model, and further improving the development efficiency of business data.

[0065] On this basis, optionally, verifying the usability of the business model includes:

[0066] Verifying whether the business model contains application data applied in the process of business data development, and / or whether the application data conforms to the business logic of the target business to which the business data belongs;

[0067] Obtain the verification result. When the verification result indicates that the business model contains application data, or the business model contains application data and the application data conforms to the business logic, determine that the usability of the business model is available; and / or,

[0068] When the verification result indicates that the business model does not contain application data, or the business model contains application data and the application data does not conform to the business logic, determine that the usability of the business model is unavailable.

[0069] Among them, the application data can be understood as the data applied in the process of business data development, and the business logic can be understood as the operation logic of the target business. By judging whether the business model contains application data, and / or whether the application data conforms to the business logic, the usability of the business model is obtained.

[0070] On this basis, several examples are given here to facilitate a better understanding of how to judge the usability of the business model. Exemplarily, 1. When the business model contains application data, it can be determined that the business model is available, that is, as long as the business model contains application data, regardless of whether the application data conforms to the business logic, the usability of the business model is considered to be available.

[0071] 2. When the business model contains application data and the application data conforms to the business logic, it is determined that the business model is available. Compared with Example 1, Example 2 gives more stringent conditions for the availability of the business model, which is to better ensure the effective development of business data.

[0072] 3. When the business model does not contain application data, it is determined that the business model is unavailable.

[0073] 4. When the business model contains application data and the application data does not conform to the business logic, it can be determined that the business model is unavailable.

[0074] Of course, it is also possible to determine whether the business model is available in other ways based on whether the business model contains application data and / or whether the application data conforms to the business logic, which is not specifically limited here.

[0075] Based on the above availability verification process, the effective development of business data can be guaranteed.

[0076] Figure 3 It is a flowchart of another business data development method provided in an embodiment of the present invention. This embodiment is optimized based on the above technical solutions. In this embodiment, optionally, to develop business data based on a technical caliber may include: outputting the technical caliber; when receiving a query instruction input for the technical caliber, determining the business terms in the technical caliber corresponding to the query instruction; inputting the business terms into a natural language processing tool, and obtaining the term explanations of the business terms according to the output result of the natural language processing tool, so as to develop business data based on the technical caliber and the term explanations. Among them, the explanations of the same or corresponding terms as those in the above embodiments will not be elaborated here.

[0077] See Figure 3 , the method of this embodiment may specifically include the following steps:

[0078] S210. For the business data to be developed, obtain the description text of the business requirements that the business data needs to meet.

[0079] S220. Obtain the pre-learned natural language processing tool.

[0080] S230. Input the description text into the natural language processing tool, and obtain and output the technical caliber corresponding to the business requirements according to the output result of the natural language processing tool.

[0081] Among them, output the technical caliber so that relevant personnel can know the technical caliber.

[0082] S240. When receiving a query instruction input for the technical caliber, determine the business terms in the technical caliber corresponding to the query instruction.

[0083] Among them, after relevant personnel learn about the technical caliber, there may be a situation where they are not clear about some business terms in the technical caliber, which will affect the accuracy of relevant personnel developing business data based on the technical caliber. Exemplarily, continuing with the technical caliber in the above example, relevant personnel may wonder what business model the business model referred to by the routing system is, how to determine that the fleet type is a cold chain pharmaceutical fleet, and so on. Therefore, in order to ensure the accurate development of business data, relevant personnel can input a query instruction for the business terms with doubts in the technical caliber to query the term explanations of these business terms.

[0084] On this basis, when receiving the query instruction, the business term corresponding to the query instruction in the technical caliber can be determined, that is, the business term for which the term explanation is to be queried in the technical caliber.

[0085] S250. Input the business term into a natural language processing tool, and based on the output result of the natural language processing tool, obtain the term explanation of the business term, so as to develop business data based on the technical caliber and the term explanation.

[0086] Among them, input the business term into the natural language processing tool, so that the term explanation of the business term can be obtained according to the output result of the natural language processing tool. Furthermore, relevant personnel can develop business data based on the technical caliber and the term explanation.

[0087] The technical solution of the embodiment of the present invention provides an interactive question-and-answer function through a natural language processing tool. In this way, relevant personnel do not need to communicate and confirm business terms with other personnel, thereby reducing the communication cost in the process of developing business data and further improving the development efficiency; moreover, it can assist relevant personnel to better understand the technical caliber, thus ensuring the accuracy of developing business data.

[0088] An optional technical solution is that the natural language processing tool is pre-learned based on the business information of the target business to which the business data belongs. Then, input the business term into the natural language processing tool, and based on the output result of the natural language processing tool, obtain the term explanation of the business term, including:

[0089] Input the business term into the natural language processing tool to determine and output the term explanation of the business term based on the business information through the natural language processing tool;

[0090] Obtain the term explanation according to the output result of the natural language processing tool.

[0091] Among them, according to the above description, business information can be information used to explain some business terms in the target business. Therefore, when the natural language processing tool is pre-learned based on the business information, the natural language processing tool can be used to determine the term explanations of the business terms based on the business information, thereby achieving the effect of accurately determining the term explanations.

[0092] To better understand the above technical solutions as a whole, the following will be described by way of specific examples. Exemplarily, refer to Figure 4 , use an Operational Data Store (ODS) to integrate data from different data sources and then store it in a data warehouse. Further, use the data related to the target business in the data warehouse (i.e., business information) to train a natural language processing tool, that is, the natural language processing tool is learned based on the business information. Thus, functions such as technical caliber sorting, interactive Q&A, and public information supplementation can be realized using the natural language processing tool, where the interactive Q&A is convenient for new employees to learn and become more familiar with the target business.

[0093] Figure 5 The flowchart of another business data development method provided in the embodiments of the present invention. This embodiment is optimized based on the above technical solutions. In this embodiment, optionally, to develop business data based on the technical caliber may include: obtaining common fields, where the common fields are obtained by analyzing the technical caliber, and the common implementation logic of the common fields is common in the target business to which the business data belongs; inputting the common fields into the natural language processing tool, and obtaining the common implementation logic according to the output result of the natural language processing tool, so as to develop business data according to the common implementation logic and the core implementation logic of the core fields, where the core fields are obtained by analyzing the technical caliber, and the core implementation logic matches the business requirements. Among them, the explanations of the same or corresponding terms as those in the above embodiments will not be elaborated here.

[0094] Refer to Figure 5 , the method of this embodiment may specifically include the following steps:

[0095] S310. For the business data to be developed, obtain the description text of the business requirements that the business data needs to meet.

[0096] S320. Obtain the pre-learned natural language processing tool.

[0097] S330. Input the description text into the natural language processing tool, and obtain the technical caliber corresponding to the business requirements according to the output result of the natural language processing tool.

[0098] S340. Obtain common fields, where the common fields are obtained by analyzing technical specifications, and the common implementation logic of the common fields is common in the target business to which the business data belongs.

[0099] Among them, the common fields are obtained by analyzing technical specifications. This analysis process can be automatically implemented by a machine or manually implemented by relevant personnel, and no specific limitation is made here. Considering the application scenarios that the embodiments of the present invention may involve, the common fields can be understood as fields that are common in the target business and involved in the business data. For example, they can be dates, organizations, merchants, and partitions, etc. The number of common fields can be one, two, or more, which is related to the actual situation and no specific limitation is made here.

[0100] The common implementation logic can be understood as the implementation logic of the common fields. The common implementation logic is common in the target business, that is, for any business data in the target business that involves common fields, the common fields can be implemented based on the common implementation logic, and then business data can be developed based on this.

[0101] On this basis, optionally, in addition to being common in the target business, the common fields can also be common in other businesses, then in addition to being common in the target business, the common implementation logic can also be common in other businesses.

[0102] After obtaining the technical specifications, the common fields can be obtained by analyzing the technical specifications, so as to obtain the common fields.

[0103] S350. Input the common fields into a natural language processing tool, and obtain the common implementation logic according to the output result of the natural language processing tool, so as to develop business data according to the common implementation logic and the core implementation logic of the core fields, where the core fields are obtained by analyzing technical specifications, and the core implementation logic matches the business requirements.

[0104] Among them, the core fields are obtained by analyzing technical specifications. This analysis process can be automatically implemented by a machine or manually implemented by relevant personnel, and no specific limitation is made here. Considering the application scenarios that the embodiments of the present invention may involve, the core fields can be understood as fields involved in the business data. For example, they can be waybill numbers, actual receiving times, scheduled receiving times, and whether the receiving is timely, etc. The number of core fields can be one, two, or more, which is related to the actual situation and no specific limitation is made here.

[0105] Here, taking the data table of the cold chain pharmaceutical warehouse link as an example of business data, it may involve the following fields shown in the following table. Among them, date, organization, merchant, and partition are common fields, and waybill number, actual receiving time, scheduled receiving time, and whether the receiving is timely are core fields:

[0106]

[0107]

[0108] The core implementation logic can be understood as the implementation logic of the core fields. The core implementation logic matches the business requirements, that is, for the remaining data in the target business that involves the core fields, the core implementation logic of the core fields under the business data is likely to be different from that under the remaining data. Therefore, relevant personnel can manually write the core implementation logic of the core fields under the business data according to the business requirements.

[0109] Since the common implementation logic is common in the target business, the common fields can be input into the natural language processing tool, and the common implementation logic can be obtained according to the output result of the natural language processing tool. Further, business data can be developed based on the common implementation logic and the core implementation logic. For example, the common implementation logic and the core implementation logic can be combined to develop business data.

[0110] Exemplarily, see Figure 6 , taking the business data as warehouse distribution indicators, express delivery indicators, and pharmaceutical indicators as an example. Previously, technical R & D personnel needed to pay attention to the field implementation logic of each field under these indicators. Now, they only need to pay attention to the core implementation logic of the core fields under these indicators, and the common implementation logic can be obtained through the natural language processing tool, thereby reducing the development cost of business data. In addition, the unachieved indicators in the figure can be understood as the indicators that have not been developed yet, which need to be focused on by technical R & D personnel; correspondingly, the developed indicators can be stored in the corresponding indicator library.

[0111] For the technical solution of the embodiment of the present invention, for the common fields and core fields obtained by analyzing the technical caliber, the natural language processing tool can be used to obtain the common implementation logic of the common fields. On this basis, combined with the core implementation logic manually written by relevant personnel for the core fields, business data is developed, which enables relevant personnel to only pay attention to the core implementation logic and does not need to pay attention to the common implementation logic, thereby reducing the development cost of business data and further improving the development efficiency of business data.

[0112] An alternative technical solution is that the natural language processing tool is at least pre-learned based on a general template, and the general template is pre-generated according to the general implementation logic of general fields, and the general fields include common fields;

[0113] Inputting the common fields into the natural language processing tool and obtaining the common implementation logic according to the output result of the natural language processing tool includes:

[0114] Inputting the common fields into the natural language processing tool to generate and output the common implementation logic through the natural language processing tool according to the general template;

[0115] Based on the output result of the natural language processing tool, obtain the common implementation logic.

[0116] Among them, the general fields can be understood as the fields that are common in the target business. The number of general fields can be one, two, or multiple, which is related to the actual situation and is not specifically limited here. The general fields include common fields. Specifically, the common fields are some of the fields in the general fields that are associated with business data.

[0117] The general implementation logic can be understood as the implementation logic of the general fields. The general implementation logic is common in the target business and can be obtained by analyzing the business information of the target business. This analysis process can be automatically implemented by a machine or manually implemented by relevant personnel, and is not specifically limited here. On this basis, optionally, in addition to being common in the target business, the general fields can also be common in other businesses, so the general implementation logic can also be common in other businesses in addition to being common in the target business.

[0118] In practical applications, a general template can be pre-generated according to the general implementation logic. This generation process can be automatically implemented by a machine or manually implemented by relevant personnel, and is not specifically limited here. Then, a natural language processing tool can be pre-trained according to the general template. In other words, the natural language processing tool can be pre-learned according to the business information and the general template. Then, the common fields can be input into the natural language processing tool, so that through the natural language processing tool, according to the general template, the common implementation logic can be generated.

[0119] For the above technical solution, the natural language processing tool can be pre-learned based on the general template. Since the common implementation logic to be generated is a part of the general implementation logic represented by the general template, by using the natural language processing tool and based on the general template, the automatic generation of the common implementation logic can be realized.

[0120] Another alternative technical solution is that the number of core fields is at least one. Then, the common fields are input into the natural language processing tool, and according to the output result of the natural language processing tool, the common implementation logic is obtained, including:

[0121] For the target fields associated with the common fields among the at least one core field, the common fields and the target fields are input into the natural language processing tool, so that through the natural language processing tool, according to the dimension table associated with the target fields, the common implementation logic is generated and output;

[0122] According to the output result of the natural language processing tool, obtain the common implementation logic.

[0123] Among them, the number of core fields is at least one, and the target field can be understood as the core field associated with the common field among at least one core field. In practical applications, the common implementation logic can be generated according to the dimension table associated with the target field. This dimension table can be obtained from the data warehouse. Therefore, the common field and the target field can be jointly input into the natural language processing tool, so that the common implementation logic can be generated according to the dimension table through the natural language processing tool, thus realizing the rapid generation of the common implementation logic.

[0124] Figure 7 It is a structural block diagram of the service data development device provided by the embodiment of the present invention. This device is used to execute the service data development method provided by any of the above embodiments. This device and the service data development methods of the above embodiments belong to the same inventive concept. For the details not described in detail in the embodiment of the service data development device, reference can be made to the embodiments of the above service data development methods. See Figure 7 Specifically, this device may include: a description text acquisition module 410, a natural language processing tool acquisition module 420, and a service data development module 430. Among them,

[0125] The description text acquisition module 410 is used to acquire the description text of the service requirements that the service data needs to meet for the service data to be developed;

[0126] The natural language processing tool acquisition module 420 is used to acquire the pre-learned natural language processing tool;

[0127] The service data development module 430 is used to input the description text into the natural language processing tool, and obtain the technical caliber corresponding to the service requirements according to the output result of the natural language processing tool, so as to develop service data based on the technical caliber.

[0128] Optionally, the natural language processing tool is pre-learned based on the service information of the target service to which the service data belongs; the service data development module 430 includes:

[0129] The description text obtaining unit is used to identify service information through the natural language processing tool to obtain the description text;

[0130] The technical caliber output unit is used to input the description text into the natural language processing tool to generate and output the technical caliber corresponding to the service requirements;

[0131] The technical caliber obtaining unit is used to obtain the technical caliber according to the output result of the natural language processing tool.

[0132] Optionally, the service data development module 430 includes:

[0133] The first technical specification output sub-module is used to input the description text into a natural language processing tool, so as to identify the description text through the natural language processing tool, obtain a business model that matches the business requirements, verify the usability of the business model, and generate and output the technical specification corresponding to the business requirements according to the usability;

[0134] The technical specification obtaining sub-module is used to obtain the technical specification according to the output result of the natural language processing tool.

[0135] On this basis, optionally, the first technical specification output sub-module includes:

[0136] The business model verification unit is used to verify whether the business model contains application data applied in the development of business data, and / or whether the application data conforms to the business logic of the target business to which the business data belongs;

[0137] The first availability determination unit is used to obtain the verification result, and determine that the usability of the business model is available when the verification result indicates that the business model contains application data, or the business model contains application data and the application data conforms to the business logic; and / or,

[0138] The second availability determination unit is used to determine that the usability of the business model is unavailable when the verification result indicates that the business model does not contain application data, or the business model contains application data and the application data does not conform to the business logic.

[0139] Optionally, the business data development module 430 includes:

[0140] The second technical specification output sub-module is used to output the technical specification;

[0141] The business term determination sub-module is used to determine the business term corresponding to the query instruction in the technical specification when receiving a query instruction input for the technical specification;

[0142] The first business data development sub-module is used to input the business term into the natural language processing tool, and obtain the term explanation of the business term according to the output result of the natural language processing tool, so as to develop business data based on the technical specification and the term explanation.

[0143] On this basis, optionally, the natural language processing tool is pre-learned based on the business information of the target business to which the business data belongs; the first business data development sub-module includes:

[0144] The term explanation output unit is used to input the business term into the natural language processing tool, so as to determine and output the term explanation of the business term through the natural language processing tool based on the business information;

[0145] A term explanation obtaining unit is configured to obtain a term explanation based on the output result of a natural language processing tool.

[0146] Optionally, the business data development module 430 includes:

[0147] A common field obtaining sub-module is configured to obtain common fields, where the common fields are obtained by analyzing technical calibers, and the common implementation logic of the common fields is common in the target business to which the business data belongs;

[0148] A second business data development sub-module is configured to input the common fields into a natural language processing tool, and based on the output result of the natural language processing tool, obtain the common implementation logic, so as to develop business data according to the common implementation logic and the core implementation logic of the core fields, where the core fields are obtained by analyzing technical calibers, and the core implementation logic matches the business requirements.

[0149] On this basis, optionally, the natural language processing tool is at least pre-learned based on a general template, and the general template is pre-generated according to the common implementation logic of general fields, and the general fields include common fields;

[0150] The second business data development sub-module includes:

[0151] A first common implementation logic output unit is configured to input the common fields into a natural language processing tool, so as to generate and output the common implementation logic through the natural language processing tool according to the general template;

[0152] A first common implementation logic obtaining unit is configured to obtain the common implementation logic based on the output result of the natural language processing tool.

[0153] Another option is that the number of core fields is at least one, and the second business data development sub-module includes:

[0154] A second common implementation logic output unit is configured to input the common fields and the target fields associated with the common fields among at least one core field into a natural language processing tool, so as to generate and output the common implementation logic through the natural language processing tool according to the dimension table associated with the target field;

[0155] A second common implementation logic obtaining unit is configured to obtain the common implementation logic based on the output result of the natural language processing tool.

[0156] The business data development device provided by the embodiment of the present invention, for the business data to be developed, through the cooperation of the description text acquisition module and the natural language processing tool acquisition module, obtains the description text of the business requirements that the business data needs to meet, and obtains the pre-learned natural language processing tool; then, through the business data development module, inputs the description text into the natural language processing tool, and according to the output result of the natural language processing tool, obtains the technical caliber corresponding to the business requirements, so as to develop business data based on the technical caliber. The above device, by using the natural language processing tool, can automatically transform business requirements into technical calibers, and realize business data development based on the technical calibers. This development process does not need to involve multiple handling personnel, and the entire development link is relatively short, thereby improving the development efficiency of business data.

[0157] The business data development device provided by the embodiment of the present invention can execute the business data development method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0158] It should be noted that in the embodiments of the above business data development device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the present invention.

[0159] Figure 8 FIG. shows a schematic structural diagram of an electronic device 10 that can be used to implement the embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only for illustration and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0160] As Figure 8As shown, the electronic device 10 includes at least one processor 11 and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. The memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0161] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0162] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the business data development method.

[0163] In some embodiments, the business data development method can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the business data development method described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute the business data development method by any other appropriate means (e.g., by means of firmware).

[0164] The various embodiments of the systems and techniques described above in this specification can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems-on-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which may be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0165] A computer program for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

[0166] In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium may be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0167] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0168] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0169] The computing system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0170] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0171] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for developing business data, characterized in that, it includes: For the business data to be developed, obtain the description text of the business requirements that the business data needs to meet; Obtain a pre-learned natural language processing tool; Input the description text into the natural language processing tool, and based on the output result of the natural language processing tool, obtain the technical caliber corresponding to the business requirements, so as to develop the business data based on the technical caliber.

2. The method according to claim 1, characterized in that, The natural language processing tool is pre-learned based on the business information of the target business to which the business data belongs; The step of inputting the description text into the natural language processing tool and obtaining the technical caliber corresponding to the business requirements according to the output result of the natural language processing tool includes: Identify the business information through the natural language processing tool to obtain the description text; Input the description text into the natural language processing tool to generate and output the technical caliber corresponding to the business requirements; Obtain the technical caliber according to the output result of the natural language processing tool.

3. The method according to claim 1, characterized in that, The step of inputting the description text into the natural language processing tool and obtaining the technical caliber corresponding to the business requirements according to the output result of the natural language processing tool includes: Input the description text into the natural language processing tool, so as to identify the description text through the natural language processing tool, obtain a business model matching the business requirements, verify the usability of the business model, and generate and output the technical caliber corresponding to the business requirements according to the usability; Obtain the technical caliber according to the output result of the natural language processing tool.

4. The method according to claim 3, characterized in that, The step of verifying the usability of the business model includes: Verify whether the business model contains application data applied in the development process of the business data, and / or whether the application data conforms to the business logic of the target business to which the business data belongs; Obtain a verification result, and determine that the usability of the business model is available when the verification result indicates that the business model contains the application data, or the business model contains the application data and the application data conforms to the business logic; and / or, When the verification result indicates that the business model does not contain the application data, or the business model contains the application data and the application data does not conform to the business logic, determine that the usability of the business model is unavailable.

5. The method according to claim 1, characterized in that, The step of developing the business data based on the technical caliber includes: Output the technical caliber; When receiving a query instruction input for the technical caliber, determine the business terms in the technical caliber corresponding to the query instruction; Input the business term into the natural language processing tool, and obtain the term explanation of the business term according to the output result of the natural language processing tool, so as to develop the business data based on the technical caliber and the term explanation.

6. The method according to claim 5, wherein, the natural language processing tool is pre-learned based on the business information of the target business to which the business data belongs; The step of inputting the business term into the natural language processing tool and obtaining the term explanation of the business term according to the output result of the natural language processing tool includes: Input the business term into the natural language processing tool, so as to determine and output the term explanation of the business term based on the business information through the natural language processing tool; Obtain the term explanation according to the output result of the natural language processing tool.

7. The method according to claim 1, wherein, The step of developing the business data based on the technical caliber includes: Obtain common fields, wherein the common fields are obtained by analyzing the technical caliber, and the common implementation logic of the common fields is common in the target business to which the business data belongs; Input the common fields into the natural language processing tool, and obtain the common implementation logic according to the output result of the natural language processing tool, so as to develop the business data according to the common implementation logic and the core implementation logic of the core fields, wherein the core fields are obtained by analyzing the technical caliber, and the core implementation logic matches the business requirements.

8. The method according to claim 7, wherein, the natural language processing tool is at least pre-learned based on a general template, and the general template is pre-generated according to the common implementation logic of general fields, and the general fields include the common fields; The step of inputting the common fields into the natural language processing tool and obtaining the common implementation logic according to the output result of the natural language processing tool includes: Input the common fields into the natural language processing tool, so as to generate and output the common implementation logic according to the general template through the natural language processing tool; Obtain the common implementation logic according to the output result of the natural language processing tool.

9. The method according to claim 7, wherein, the number of the core fields is at least one, and the step of inputting the common fields into the natural language processing tool and obtaining the common implementation logic according to the output result of the natural language processing tool includes: For the target fields associated with the common fields among the at least one core fields, input the common fields and the target fields into the natural language processing tool, so as to generate and output the common implementation logic according to the dimension table associated with the target fields through the natural language processing tool; Obtain the common implementation logic according to the output result of the natural language processing tool.

10. A business data development device, wherein, comprising: A description text acquisition module, configured to acquire a description text of business requirements that the business data to be developed needs to meet for the business data to be developed; A natural language processing tool acquisition module, configured to acquire a pre-learned natural language processing tool; A business data development module, configured to input the description text into the natural language processing tool, and obtain a technical specification corresponding to the business requirements according to the output result of the natural language processing tool, so as to develop the business data based on the technical specification.

11. An electronic device Characterized in that Comprising: At least one processor; And A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor executes the business data development method according to any one of claims 1-9.

12. A computer-readable storage medium Characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the business data development method according to any one of claims 1-9 when executed by a processor.

Images