Multi-class business data importing method and device, electronic equipment and storage medium

Abstract

The invention provides a multi-class business data importing method and device, electronic equipment and a storage medium, and is suitable for the fields of financial science and technology and medical services. The method comprises the steps of obtaining a business data import request, a corresponding business data file and a target data table; analyzing the business data file to obtain a business file format, and determining a target analysis rule in a preset analysis rule base; performing field analysis on the business data file based on the target analysis rule to obtain multiple pieces of data field information; for each piece of data field information, matching the data field information with each piece of target field information to determine an import mapping relationship between each piece of data field information and the target field information; performing structured splitting on the business data file according to the target analysis rule to obtain structured business data; and importing the structured business data into the target data table according to the importing mapping relation. The method and the device can improve the efficiency of importing multiple types of business data into the database.

Description

Technical Field

[0001] The present application is applicable to the fields of financial technology and medical services, and in particular relates to a method and device for importing multiple types of business data, an electronic device, and a storage medium. Background Art

[0002] With the rapid development of the digital age, the demand for processing various types of business data is increasing, especially in the fields of financial technology and medical services. The efficient and accurate import of data has become a key link in business development. The financial technology field often involves a large amount of customer information, transaction data, risk assessment and other data, while the medical service field involves sensitive information such as medical records, test reports, and medical images. These data usually exist in multiple formats and have complex data structures. How to efficiently and accurately import these diverse data into the database has become an important challenge in the current data processing field.

[0003] In the related art, when processing data import, the existing database management system usually needs to manually configure import rules for different data formats or data structures. Especially when facing multiple data formats and complex data structures, data import anomalies, data loss or omissions are prone to occur. Therefore, a data import solution with higher import efficiency is urgently needed. Summary of the invention

[0004] The main purpose of the embodiments of the present application is to propose a method and device for importing multiple types of business data, an electronic device and a storage medium, aiming to improve the efficiency of importing multiple types of business data into a database.

[0005] To achieve the above-mentioned purpose, a first aspect of an embodiment of the present application proposes a method for importing multiple types of business data, the method comprising:

[0006] Obtaining a business data import request, and a business data file and a target data table corresponding to the business data import request; wherein the target data table includes a plurality of target field information;

[0007] Parsing the business data file to obtain a corresponding business file format, and determining a target parsing rule corresponding to the business file format in a preset parsing rule library;

[0008] Performing field parsing on the business data file based on the target parsing rule to obtain multiple data field information of the business data file;

[0009] For each of the data field information, matching the data field information with each of the target field information in the target data table to determine an import mapping relationship between each of the data field information and the target field information;

[0010] Structurally splitting the business data file according to the target parsing rule to obtain structured business data;

[0011] The structured business data is imported into the target data table according to the import mapping relationship.

[0012] In some embodiments, the target parsing rules include text parsing rules, table parsing rules, and structured data parsing rules, and the business data file is structured and split according to the target parsing rules to obtain structured business data, including:

[0013] If the business file format is a text file format, the data content in the business data file is segmented into fields according to the delimiter identifier preset in the text parsing rule to obtain the structured business data;

[0014] If the business file format is a spreadsheet format, then according to the cell location identifier preset in the table parsing rule, field extraction is performed on the table content in the business data file to obtain the structured business data;

[0015] If the business file format is a structured data format, the structured business data is obtained by parsing the key-value pairs or tag structures in the business data file according to the data structure configuration preset in the structured data parsing rule.

[0016] In some embodiments, before obtaining the service data import request, the process further includes:

[0017] Obtaining the permission application of the target object for the target data table;

[0018] A temporary operation permission for the target data table is generated according to the permission application; wherein the temporary operation permission includes a validity period identifier, which is used to set the temporary operation permission to be invalid after the validity period identifier expires.

[0019] In some embodiments, for each piece of data field information, matching the data field information with each piece of target field information in the target data table to determine an import mapping relationship between each piece of data field information and the target field information includes:

[0020] For each piece of data field information, traverse and compare the data field information with the target field information;

[0021] In response to detecting that there is a field in the plurality of data field information that does not match the target field information, sending a field supplement request to the target object;

[0022] Receiving the field supplementary information returned by the target object;

[0023] The import mapping relationship is updated according to the field supplementary information.

[0024] In some embodiments, after importing the structured business data into the target data table according to the import mapping relationship, the method further includes:

[0025] Performing abnormal data detection processing on the structured business data to obtain an abnormal data detection result;

[0026] If the anomaly detection result indicates that the structured business data contains abnormal data, the abnormal data is temporarily stored in a preset abnormal data cache; wherein the abnormal data includes format abnormal data whose data format does not meet the preset format requirements, encoding abnormal data whose data encoding does not meet the preset encoding requirements, and quantity abnormal data whose number of fields is inconsistent with the number of fields of the target field information;

[0027] Generate an exception data report based on the exception data cache and return it to the target object.

[0028] In some embodiments, the method further comprises:

[0029] Receive the scheduled import task configuration information sent by the user, wherein the scheduled import task configuration information includes the scheduled execution time;

[0030] Generate a scheduled import task for the business data file according to the scheduled import task configuration information;

[0031] When it is detected that the scheduled execution time has arrived, the import operation of the business data file is automatically executed.

[0032] In some embodiments, the method further comprises:

[0033] Generate import progress information of the structured business data; wherein the import progress information includes the amount of imported data, the amount of remaining data, and the import time;

[0034] Pushing the import progress information to the target object in real time;

[0035] In response to obtaining the import interruption instruction sent by the target object, stop the current import operation and generate statistical information of the data imported before the interruption time point;

[0036] The data statistics information is returned to the target object.

[0037] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application proposes a device for importing multiple types of business data, the device comprising:

[0038] An acquisition module, used to acquire a business data import request, and a business data file and a target data table corresponding to the business data import request; wherein the target data table contains a plurality of target field information;

[0039] A parsing rule module, used to parse the business data file to obtain a corresponding business file format, and determine a target parsing rule corresponding to the business file format in a preset parsing rule library;

[0040] A data field module, used to perform field parsing on the business data file based on the target parsing rule to obtain multiple data field information of the business data file;

[0041] An import mapping module, for matching the data field information with each target field information in the target data table for each data field information, so as to determine an import mapping relationship between each data field information and the target field information;

[0042] A splitting module, used for performing structured splitting on the business data file according to the target parsing rule to obtain structured business data;

[0043] An import module is used to import the structured business data into the target data table according to the import mapping relationship.

[0044] To achieve the above objectives, a third aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in the first aspect is implemented.

[0045] To achieve the above-mentioned purpose, the fourth aspect of an embodiment of the present application proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0046] The present application proposes a method and device for importing multiple types of business data, an electronic device, and a storage medium, which obtains a business data import request, and a business data file and a target data table corresponding to the business data import request; wherein the target data table contains multiple target field information; the business data file is parsed to obtain the corresponding business file format, and the target parsing rule corresponding to the business file format is determined in a preset parsing rule library; the business data file is field parsed based on the target parsing rule to obtain multiple data field information of the business data file; for each data field information, the data field information is matched with each target field information in the target data table to determine the import mapping relationship between each data field information and the target field information; the business data file is structured and split according to the target parsing rule to obtain structured business data; and the structured business data is imported into the target data table according to the import mapping relationship.

[0047] According to the import method of multiple types of business data provided by the present invention, first, by obtaining a business data import request and corresponding business data files and target data tables, a clear target and basis are provided for subsequent data parsing and importing; then, based on the business file format of the business data file, the target parsing rule is matched in the preset parsing rule library, and the traditional manual parsing process is transformed into an automated parsing based on the file format, realizing efficient parsing of different types of business data files; based on the target parsing rule, the business data file is subjected to field parsing to obtain multiple data field information, ensuring the complete extraction of the data field; then, by matching the data field information of the business data file with the target field information in the target data table, the import mapping relationship is determined, ensuring the accurate mapping and importing of the data field; then, according to the target parsing rule, the business data file is structured and split to obtain structured business data, ensuring the normalization and standardization of the data; finally, the structured business data is imported into the target data table according to the import mapping relationship, ensuring the consistency and integrity of the data import. Through the above method, the present invention can efficiently and accurately parse and import data files under different business scenarios, and improve the efficiency of importing multiple types of business data into the database. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a flowchart of a method for importing multiple types of business data provided by an embodiment of the present application;

[0049] Figure 2 is another flow chart of the method for importing multiple types of business data provided in an embodiment of the present application;

[0050] Figure 3 is another flow chart of the method for importing multiple types of business data provided in an embodiment of the present application;

[0051] Figure 4 is another flow chart of the method for importing multiple types of business data provided in an embodiment of the present application;

[0052] Figure 5 is another flow chart of the method for importing multiple types of business data provided in an embodiment of the present application;

[0053] Figure 6 is another flow chart of the method for importing multiple types of business data provided in an embodiment of the present application;

[0054] Figure 7 is another flow chart of the method for importing multiple types of business data provided in an embodiment of the present application;

[0055] Figure 8 It is a structural diagram of a device for importing multiple types of business data provided in an embodiment of the present application;

[0056] Fig. 9 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0058] It should be noted that, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0060] First, some nouns involved in this application are analyzed:

[0061] Business Data File: refers to a file containing business data, which can be stored in a specific format (such as CSV, Excel, JSON, etc.). The business data file contains the original data that needs to be imported into the target data table, involving multiple data fields and records. In the financial field, business data files contain customer transaction records, account information, loan application data, risk assessment reports, etc. These data files are used to import into the target data table of the financial system to support business operations such as transaction processing, risk analysis, and customer management. In the field of medical services, business data files contain electronic medical records, diagnostic reports, drug prescriptions, medical equipment usage records, etc. These data files are used to import into the target data table of the medical information system to support medical service processes such as medical record management, diagnostic analysis, and drug inventory management. Business data files are the core input of the data import process, and their accuracy and completeness directly affect the quality of subsequent data processing and analysis.

[0062] Based on this, the embodiments of the present application provide a method and device for importing multiple types of business data, an electronic device and a storage medium, aiming to improve the efficiency of importing multiple types of business data into a database.

[0063] The method and device for importing multiple types of business data, electronic device and storage medium provided in the embodiments of the present application are specifically explained through the following embodiments. First, the method for importing multiple types of business data in the embodiments of the present application is described.

[0064] The method for importing multiple types of business data provided in the embodiment of the present application is applicable to the fields of financial technology and medical services. The method for importing multiple types of business data provided in the embodiment of the present application can be applied to the terminal, can also be applied to the server side, and can also be software running in the terminal or the server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or it can be configured as a server cluster or distributed system composed of multiple physical servers, and can also be configured as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the method for importing multiple types of business data, etc., but is not limited to the above forms.

[0065] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0066] It should be noted that in each specific implementation of the present application, when it comes to the need to perform relevant processing based on data related to user identity or characteristics such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of these data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.

[0067] Figure 1 is an optional flowchart of the method for importing multiple types of business data provided in an embodiment of the present application. Figure 1 The method may include but is not limited to steps S101 to S106.

[0068] Step S101, obtaining a business data import request, and a business data file and a target data table corresponding to the business data import request.

[0069] The target data table contains multiple target field information.

[0070] Step S102, parsing the business data file to obtain a corresponding business file format, and determining a target parsing rule corresponding to the business file format in a preset parsing rule library.

[0071] Step S103, performing field parsing on the business data file based on the target parsing rule to obtain information on multiple data fields of the business data file.

[0072] Step S104: for each data field information, the data field information is matched with each target field information in the target data table to determine an import mapping relationship between each data field information and the target field information.

[0073] Step S105 , structurally splitting the business data file according to the target parsing rule to obtain structured business data.

[0074] Step S106: import the structured business data into the target data table according to the import mapping relationship.

[0075] Steps S101 to S106 shown in the embodiment of the present application, firstly, by obtaining a business data import request and the corresponding business data file and target data table, provide a clear target and basis for subsequent data parsing and importing; then, based on the business file format of the business data file, match the target parsing rule in the preset parsing rule library, transform the traditional manual parsing process into an automated parsing based on the file format, and realize efficient parsing of different types of business data files; based on the target parsing rule, the business data file is subjected to field parsing to obtain multiple data field information, ensuring the complete extraction of the data field; then, by matching the data field information of the business data file with the target field information in the target data table, the import mapping relationship is determined, ensuring the accurate mapping and importing of the data field; then, according to the target parsing rule, the business data file is structured and split to obtain structured business data, ensuring the normalization and standardization of the data; finally, according to the import mapping relationship, the structured business data is imported into the target data table, ensuring the consistency and integrity of the data import. Through the above method, the present invention can efficiently and accurately parse and import data files under different business scenarios, and improve the efficiency of importing multiple types of business data into the database.

[0076] In step S101 of some embodiments, a business data import request refers to a request initiated by a user or a system, requesting that a specific business data file be imported into a target data table, and the request includes the path and format information of the business data file and the identifier of the target data table, which is used to start the data import process. The type range of business data import requests can be predetermined, and business data import requests can include but are not limited to: financial transaction data import, insurance claim data import, medical record data import, etc. By obtaining the business data import request and the corresponding business data file and target data table, the target and scope of the data import can be clarified, ensuring that the subsequent data analysis and import process has a basis to rely on, and avoiding the blindness and error rate of data import.

[0077] It is understandable that a business data file refers to a file containing business data, which is stored in a specific format (such as CSV, Excel, JSON, etc.), and the business data file contains the original data that needs to be imported into the target data table. The target data table refers to the table structure used to store business data in the database, which contains multiple target field information. The target data table defines the storage format and field type of the data and is the final destination for the business data import. The target field information refers to the field information defined in the target data table, including the field name, data type, length, constraints, etc. Obtaining a business data import request and the corresponding business data file and target data table may include: receiving a business data import request from a user or a system, the request includes the path of the business data file, format information, and the identifier of the target data table. For example, a user submits a request to import a transaction record file for a certain month into the transaction data table of the financial system.

[0078] Exemplarily, in the field of financial technology, a business data import request may be an insurance claim data import. For example, when an insurance company needs to import the claim data of a certain month into the claim management system, the system first receives the claim data import request submitted by the user. The request includes the path of the claim data file and the identifier of the target data table. Then, the claim data file is obtained according to the claim data import request. The file may contain fields such as claim number, claim amount, and claim status. At the same time, the structural information of the target data table is obtained, including target field information, such as "claim number", "claim amount", "claim status", etc.

[0079] See also Figure 2 In some embodiments, before obtaining the business data import request, the following steps may also be performed, but are not limited to, steps S201 to S202:

[0080] Step S201, obtaining the permission application of the target object for the target data table.

[0081] Step S202: Generate temporary operation permissions for the target data table according to the permission application.

[0082] The temporary operation authority includes a validity period identifier, which is used to set the temporary operation authority to be invalid after the validity period identifier expires.

[0083] In step S201 of some embodiments, in order to ensure the security of the data import operation, by obtaining the permission application of the target object for the target data table, it is ensured that only authorized users or systems can perform the data import operation. The target object refers to the user or system requesting the operation, and the permission application refers to the request submitted by the target object to the system, requesting to obtain the operation permission for the target data table. The permission application includes the identity information of the target object, the operation type (such as data import), and the identification of the target data table. By obtaining the permission application, the legality and security of the data import operation can be ensured, and unauthorized users or systems can be prevented from operating the target data table, preventing data leakage or tampering.

[0084] For example, in the field of financial technology, the target object may be a data analyst of an insurance company who needs to import the claims data of a certain month into the claims management system. The data analyst first submits a permission application, requesting permission to operate the claims data table. The permission application includes the data analyst's identity information, the operation type (data import), and the identifier of the target data table (such as "claims data table").

[0085] In step S202 of some embodiments, temporary operation permissions are generated based on the permission application to ensure that the target object can perform data import operations within the validity period. Temporary operation permissions refer to the target object's operation permissions on the target data table within a specific time, including the operation type (such as data import), the identifier of the target data table, and the validity period identifier. The validity period identifier refers to the valid time range of the temporary operation permission. After exceeding this time range, the permission will automatically expire. By generating temporary operation permissions and setting the validity period identifier, the operation time of the target object can be limited, the abuse of permissions or long-term occupation can be avoided, and the security and controllability of data management can be improved.

[0086] For example, in the field of medical services, the target object may be a medical record administrator of a hospital, who needs to import the patient medical record data of a certain day into the electronic medical record management system. Based on the permission application of the medical record administrator, a temporary operation permission is generated, allowing the administrator to perform data import operations on the target data table (such as the "medical record data table") within 24 hours. The temporary operation permission contains an effective period identifier, and the permission automatically expires after 24 hours, ensuring that the medical record administrator cannot continue to operate the data table after the permission expires.

[0087] Through the above steps S201 to S202, the security and controllability of the data import operation can be effectively improved. First, by obtaining the permission application of the target object, it is ensured that only authorized users or systems can perform data import operations, avoiding unauthorized access and operations, and preventing data leakage or tampering. Secondly, by generating temporary operation permissions and setting validity period identifiers, the operation time of the target object can be limited, avoiding abuse of permissions or long-term occupation, and ensuring that the data import operation is carried out within a safe and controllable range.

[0088] In step S102 of some embodiments, the business data file is parsed to obtain the corresponding business file format, and the target parsing rule corresponding to the business file format is determined in the preset parsing rule library. For example, in the field of medical services, the business data file may be an electronic medical record data file in Excel format. First, the business data file is parsed to determine that its file format is Excel, and then the target parsing rule corresponding to the Excel format is searched in the preset parsing rule library. The parsing rule library stores parsing rules for a variety of file formats, such as CSV, JSON, Excel, etc., which define how to extract data field information from business data files and convert it into structured data. For Excel files, the target parsing rules may include information such as worksheet name, cell range, field delimiter, etc.

[0089] It is understandable that by automatically parsing the format of business data files and matching target parsing rules, business data files of different formats can be efficiently processed, avoiding the tediousness and errors of manual parsing and improving the automation level and accuracy of data parsing.

[0090] In step S103 of some embodiments, field parsing is performed on the business data file based on the target parsing rules to obtain multiple data field information of the business data file. The data field information refers to the specific data field parsed from the business data file, including field name, field value and other information. Through field parsing, key data field information can be extracted from the business data file to ensure the integrity and accuracy of the data, laying the foundation for subsequent field matching and data import.

[0091] For example, in the field of financial technology, a business data file may be a transaction record file in the format of CSV. The CSV file is parsed according to the target parsing rules to extract data field information such as transaction time, transaction amount, and transaction type. For example, according to the field separator (such as a comma) and text encoding method of the CSV file, the file content is parsed line by line to obtain the specific value of each field.

[0092] In step S104 of some embodiments, the data field information in the business data file is matched with the target field information in the target data table to determine the import mapping relationship. The import mapping relationship refers to the corresponding relationship between the data field information in the business data file and the target field information in the target data table. Through field matching, it can be ensured that the data field can be correctly mapped to the corresponding field in the target data table, avoiding data import errors and improving the accuracy and consistency of data import.

[0093] For example, in the field of medical services, a business data file may be a patient medical record data file, which contains data field information such as patient ID, diagnosis results, and medication records. The target field information of the target data table includes fields such as "patient ID", "diagnosis results", and "medication records". Next, the "patient ID" field in the medical record data file is matched with the "patient ID" field in the target data table to determine the import mapping relationship. Similarly, the "diagnosis result" field is matched with the "diagnosis result" field in the target data table to ensure that each data field information can be correctly mapped to the corresponding field of the target data table.

[0094] See also Figure 3 In some embodiments, for each data field information, the data field information is matched with each target field information in the target data table to determine the import mapping relationship between each data field information and the target field information, which may include but is not limited to steps S301 to S304:

[0095] Step S301, for each data field information, traverse and compare the data field information with the target field information.

[0096] Step S302: in response to detecting that there is a field in the plurality of data field information that does not match the target field information, a field supplement request is sent to the target object.

[0097] Step S303: receiving the field supplementary information returned by the target object.

[0098] Step S304: update the import mapping relationship according to the field supplementary information.

[0099] In step S301 of some embodiments, by traversing and comparing, it is ensured that the data field information in the business data file can correspond to the target field information in the target data table one by one. The data field information refers to the specific data field parsed from the business data file, including field name, field value and other information. The target field information refers to the field information defined in the target data table, including field name, data type, length and the like. By traversing and comparing, the matching relationship between the data field information and the target field information can be found to ensure the accuracy of data import.

[0100] In step S302 of some embodiments, when it is found that the data field information does not match the target field information, a field supplement request is sent to the target object to request the supplement of the missing or mismatched field information. By sending the field supplement request, the mismatch between the data field information and the target field information can be discovered and corrected in a timely manner, ensuring the integrity and accuracy of the data import and avoiding data import failures caused by missing or mismatched fields.

[0101] For example, in the field of medical services, the business data file may be a patient medical record data file, which includes fields such as patient ID, diagnosis results, medication records, etc. The target data table includes fields such as "patient ID", "diagnosis results", "medication records", "allergy history", etc. If it is found that the "allergy history" field is missing in the business data file, a field supplement request is sent to the target object (such as a medical record administrator) to request the supplement of the "allergy history" field information.

[0102] In step S303 of some embodiments, field supplement information returned by the target object is received to correct or supplement the data field information. Field supplement information refers to supplemented or corrected field information returned by the target object according to the field supplement request, which is used to update the data field information to ensure that it matches the target field information.

[0103] In step S304 of some embodiments, the import mapping relationship between the data field information and the target field information is updated according to the field supplement information returned by the target object. The import mapping relationship refers to the corresponding relationship between the data field information in the business data file and the target field information in the target data table. By updating the import mapping relationship, it is ensured that the supplemented or corrected data field information can be correctly mapped to the corresponding field of the target data table.

[0104] Through the above steps S301 to S304, the accuracy and completeness of data import can be effectively improved. By traversing and comparing, the matching relationship between the data field information and the target field information is ensured, and data import errors caused by field mismatches are avoided. Secondly, by sending a field supplement request, the mismatch between the data field information and the target field information can be discovered and corrected in time to ensure the completeness and accuracy of data import. Finally, by receiving field supplement information and updating the import mapping relationship, it is ensured that the supplemented or corrected data field information can be correctly mapped to the corresponding fields of the target data table, thereby improving the accuracy and consistency of data import. This field matching and supplementation mechanism provides a more reliable guarantee for the data import process and reduces the risk of data import failure due to missing or mismatched fields.

[0105] In step S105 of some embodiments, the unstructured or semi-structured data in the business data file is converted into structured data according to the target parsing rules. Structured splitting refers to arranging and splitting the data in the business data file according to preset rules to ensure that the data format is consistent with the target data table. Structured business data refers to the normalized data obtained after splitting, which can be presented in a tabular form and contains clear fields and record information.

[0106] For example, in the field of financial technology, the business data file is a loan approval data file in JSON format. The JSON file is structured and split according to the target parsing rules to convert the unstructured data into structured data. For example, the nested objects and arrays in the JSON file are split into flat data structures to ensure that each field corresponds to the field of the target data table, and finally the structured loan approval data is obtained, including fields such as loan number, loan amount, and approval status.

[0107] See also Figure 4 In some embodiments, the target parsing rules include text parsing rules, table parsing rules, and structured data parsing rules. The business data file is structured and split according to the target parsing rules to obtain structured business data, which may include but is not limited to steps S401 to S403:

[0108] Step S401: if the business file format is a text file format, the data content in the business data file is segmented into fields according to the delimiter identifier preset in the text parsing rule to obtain structured business data.

[0109] Step S402: If the business file format is an electronic table format, then according to the cell location identifier preset in the table parsing rule, field extraction is performed on the table content in the business data file to obtain structured business data.

[0110] Step S403: if the business file format is a structured data format, then according to the data structure configuration preset in the structured data parsing rule, the key-value pairs or tag structure in the business data file are parsed to obtain structured business data.

[0111] In step S401 of some embodiments, for a business data file in a text file format, the data content is segmented into fields according to the separator identifier in the text parsing rule, and converted into structured business data. The text file format refers to a file format stored in plain text, such as CSV, TXT, etc. The text parsing rule refers to the parsing rule for the text file format, including information such as field separators (such as commas, tabs, etc.), text encoding methods, etc. The separator identifier refers to a symbol or character used to separate different fields, such as a comma, a semicolon, etc.

[0112] In step S402 of some embodiments, for a business data file in a spreadsheet format, field extraction is performed on the table content according to the cell location identifier in the table parsing rule to convert it into structured business data. Spreadsheet format refers to a file format stored in a table form, such as Excel, Google Sheets, etc. Table parsing rules refer to parsing rules for spreadsheet formats, including information such as worksheet name, cell range, field location, etc. Cell location identifiers refer to identifiers used to locate the position of fields in a table, such as column numbers, row numbers, etc.

[0113] For example, the business data file may be a patient medical record data file in Excel format. The preset cell location identifier in the table parsing rule is "A1:C10", which indicates the cell range from A1 to C10. According to the cell location identifier, the table content in the Excel file is subjected to field extraction to obtain structured business data such as patient ID, diagnosis results, and medication records.

[0114] In step S403 of some embodiments, for a business data file in a structured data format, the business data file is parsed based on a key-value pair or a tag structure according to the data structure configuration in the structured data parsing rule, and converted into structured business data. A structured data format refers to a file format stored in a structured form, such as JSON, XML, etc. A structured data parsing rule refers to a parsing rule for a structured data format, including information such as key-value pairs, tag structures, and nested objects. A data structure configuration refers to configuration information used to parse structured data, such as a key name, a tag name, etc.

[0115] For example, in the field of financial technology, the business data file may be a loan approval data file in JSON format. The data structure preset in the structured data parsing rule is configured as a key-value pair. According to the data structure configuration, the key-value pairs in the JSON file are parsed to obtain structured business data such as loan number, loan amount, and approval status.

[0116] Through the above steps S401 to S403, the efficiency and accuracy of structured splitting of business data files can be effectively improved. For text file formats, field segmentation is performed through delimiter identifiers, and unstructured text data can be converted into structured business data, ensuring the normalization and standardization of data formats. For spreadsheet formats, field extraction is performed through cell positioning identifiers, and table data can be converted into structured business data, which is convenient for subsequent data import and analysis. For structured data formats, parsing is performed through data structure configuration, and complex nested data can be converted into structured business data, ensuring the normalization and standardization of data formats.

[0117] In step S106 of some embodiments, the structured business data is imported into the target data table according to the import mapping relationship. The target data table import refers to the process of importing the structured business data into the target data table according to the import mapping relationship. Through data import, the data in the business data file can be stored in the target data table, which is convenient for subsequent data management and analysis.

[0118] For example, in the field of medical services, structured business data can be drug inventory data, including fields such as drug number, drug name, and inventory quantity. According to the import mapping relationship, the "drug number" field is mapped to the "drug number" field of the target data table, the "drug name" field is mapped to the "drug name" field of the target data table, and the "inventory quantity" field is mapped to the "inventory quantity" field of the target data table. Then, the structured business data is imported into the target data table according to the import mapping relationship to complete the data import process.

[0119] See also Figure 5 In some embodiments, after the structured business data is imported into the target data table according to the import mapping relationship, the following steps may also be performed, including but not limited to steps S501 to S503:

[0120] Step S501, performing abnormal data detection processing on structured business data to obtain an abnormal data detection result.

[0121] Step S502: If the anomaly detection result indicates that the structured business data contains abnormal data, the abnormal data is temporarily stored in a preset abnormal data cache.

[0122] Among them, the abnormal data includes format abnormal data whose data format does not meet the preset format requirements, encoding abnormal data whose data encoding does not meet the preset encoding requirements, and quantity abnormal data whose number of fields is inconsistent with the number of fields of the target field information.

[0123] Step S503: Generate an abnormal data report based on the abnormal data cache and return it to the target object.

[0124] In step S501 of some embodiments, after the data is imported, abnormal data detection processing is performed on the structured business data to ensure the integrity and accuracy of the data. Abnormal data detection processing refers to verifying the structured business data and identifying data that does not meet the preset requirements. Abnormal data includes format abnormalities, coding abnormalities, quantity abnormalities, etc. The abnormal detection result refers to the detailed information of the abnormal data found during the detection process, including abnormal type, abnormal field, abnormal value, etc.

[0125] For example, in the credit card transaction data import scenario, the structured business data includes fields such as transaction time, transaction amount, transaction type, etc. During the abnormal data detection process, if a future date (format abnormal data) is found in the transaction time field, the data is marked as abnormal data and an abnormal detection result is generated.

[0126] In step S502 of some embodiments, the detected abnormal data is temporarily stored in an abnormal data cache for subsequent processing and analysis. The abnormal data cache refers to a storage area for temporarily storing abnormal data, including detailed information of the abnormal data, such as abnormal type, abnormal field, abnormal value, etc. Format abnormal data refers to data whose data format does not meet the preset requirements, such as incorrect date format, incorrect amount format, etc. Encoding abnormal data refers to data whose data encoding does not meet the preset requirements, such as incorrect character encoding, special characters not escaped, etc. Quantity abnormal data refers to data whose number of fields is inconsistent with the number of fields of the target field information, such as missing fields, extra fields, etc.

[0127] For example, in the scenario of importing drug inventory data, structured business data includes fields such as drug number, drug name, inventory quantity, etc. During the abnormal data detection process, if a negative number (format abnormal data) is found in the inventory quantity field, the data is temporarily stored in the abnormal data cache.

[0128] In step S503 of some embodiments, an abnormal data report is generated based on the abnormal data in the abnormal data cache and returned to the target object, so that the target object can correct and process the abnormal data. The abnormal data report refers to a report containing detailed information of the abnormal data, including information such as the abnormal type, abnormal field, abnormal value, and abnormal cause. The target object refers to the user or system responsible for processing the abnormal data, such as a data analyst, a system administrator, etc.

[0129] Through the above steps S501 to S503, the efficiency of data quality management and exception handling after data import can be effectively improved. Through abnormal data detection, abnormal data in structured business data can be discovered and identified in a timely manner to ensure the data quality in the target data table. By temporarily storing abnormal data in the abnormal data cache, the impact of abnormal data on the target data table can be avoided, and data support can be provided for subsequent abnormal data processing and analysis. Finally, by generating an abnormal data report and returning it to the target object, abnormal data in the data import process can be discovered and corrected in a timely manner to ensure the data quality in the target data table, reducing system errors or business problems caused by abnormal data.

[0130] See also Figure 6 In some embodiments, the method for importing multiple types of business data may also include but is not limited to steps S601 to S603:

[0131] Step S601: receiving the scheduled import task configuration information sent by the user, where the scheduled import task configuration information includes the scheduled execution time.

[0132] Step S602: Generate a scheduled import task for the business data file according to the scheduled import task configuration information.

[0133] Step S603: When it is detected that the scheduled execution time has arrived, the import operation of the business data file is automatically executed.

[0134] In step S601 of some embodiments, the scheduled import task configuration information configured by the user is received so that the import operation of the business data file can be automatically executed at the scheduled time. The scheduled import task configuration information refers to the relevant parameters of the scheduled task set by the user, including the scheduled execution time, the business data file path, the target data table information, etc. The scheduled execution time refers to the task execution time specified by the user, and the system will automatically trigger the data import operation at this time point. For example, in the daily transaction data import scenario, the user configures the scheduled import task and sets the scheduled execution time to 2 a.m. every day. The financial system receives the scheduled import task configuration information and automatically imports the transaction data file at the specified time.

[0135] In step S602 of some embodiments, a specific scheduled import task is generated. The scheduled import task refers to a task generated according to user-configured parameters such as scheduled execution time, business data file path, target data table information, etc., and the task will be automatically triggered at a specified time.

[0136] In step S603 of some embodiments, when the scheduled execution time is detected, the import operation of the business data file is automatically triggered and executed. The automatic import operation refers to automatically reading the business data file, parsing the data field information, and importing it into the target data table according to the configuration of the scheduled import task. When the scheduled execution time arrives, the system will automatically start the import process without manual intervention, thereby improving the automation level and efficiency of data import.

[0137] Through the above steps S601 to S603, the automation level and efficiency of importing business data files can be effectively improved. By receiving the scheduled import task configuration information sent by the user, the import operation of business data files can be automatically executed at the scheduled time, reducing the need for manual intervention. By generating a scheduled import task, the data import operation can be automatically triggered according to the time configured by the user, thereby improving the automation level of data import. By automatically executing the import operation of business data files, the timeliness and accuracy of data import are ensured. The scheduled import mechanism provides a more flexible and efficient solution for the import of business data files, reducing the tediousness and errors of manual operations.

[0138] See also Figure 7 In some embodiments, the method for importing multiple types of business data may also include but is not limited to steps S701 to S704:

[0139] Step S701: Generate import progress information of structured business data.

[0140] The import progress information includes the amount of data imported, the amount of data remaining, and the import time.

[0141] Step S702: Push the import progress information to the target object in real time.

[0142] Step S703, in response to obtaining the import interruption instruction sent by the target object, stop the current import operation and generate statistical information of the data imported before the interruption time point.

[0143] Step S704: Return the data statistics information to the target object.

[0144] In step S701 of some embodiments, during the data import process, import progress information is generated and updated in real time so that the user can understand the execution status of the current import task. Import progress information refers to real-time status information during the data import process, including the amount of imported data, the amount of remaining data, and the import time. The amount of imported data refers to the amount of data that has been successfully imported into the target data table. The amount of remaining data refers to the amount of data that has not yet been imported. The import time refers to the time spent from the start of the import task to the current time.

[0145] In step S702 of some embodiments, the generated import progress information is pushed to the target object in real time to ensure that the user can timely understand the execution status of the import task. Real-time push means that during the import process, the import progress information is continuously sent to the target object, for example, through message notification, email, dashboard, etc.

[0146] In step S703 of some embodiments, when the target object sends an import interruption instruction, the current import operation can be stopped immediately, and statistical information of the data imported before the interruption time point is generated. The import interruption instruction refers to an instruction sent by the user, requiring the current data import operation to be stopped immediately. The data statistical information refers to the summary information of the data imported before the interruption time point, including the amount of imported data, the import time, the import success rate, etc.

[0147] In step S704 of some embodiments, the generated data statistics are returned to the target object to facilitate the user to understand the execution status of the import task. By returning the data statistics to the target object, the target object can understand the execution status of the import task, which is convenient for subsequent data analysis and processing. For example, in the medical record data import scenario, the import progress information is generated, showing that 500 medical record records have been imported, 200 records remain to be imported, and the import time is 5 minutes. The import progress information is pushed in real time via email. After the user sends the import interruption instruction, the import operation is stopped immediately, and data statistics are generated, showing that 500 medical record records have been imported, the import time is 5 minutes, and the import success rate is 98%. The data statistics are returned to the target object.

[0148] Through steps S701 to S704, the controllability and transparency of the data import process can be effectively improved. By generating import progress information, users can understand the progress of data import in real time, which is convenient for monitoring the execution status of import tasks. By pushing import progress information in real time, users can understand the progress of data import in a timely manner, which is convenient for timely discovery and handling of problems that may arise during the import process. By responding to import interrupt instructions and generating data statistics, the import operation can be stopped immediately when the target object needs it, and summary information of the imported data can be generated, which is convenient for users to understand the execution status of the import task.

[0149] The present application proposes a method and device for importing multiple types of business data, an electronic device, and a storage medium, which obtains a business data import request, and a business data file and a target data table corresponding to the business data import request; wherein the target data table contains multiple target field information; the business data file is parsed to obtain the corresponding business file format, and the target parsing rule corresponding to the business file format is determined in a preset parsing rule library; the business data file is field parsed based on the target parsing rule to obtain multiple data field information of the business data file; for each data field information, the data field information is matched with each target field information in the target data table to determine the import mapping relationship between each data field information and the target field information; the business data file is structured and split according to the target parsing rule to obtain structured business data; and the structured business data is imported into the target data table according to the import mapping relationship.

[0150] According to the method for importing multi-class service data provided by the present invention, first, by obtaining a service data import request, the corresponding service data file, and the target data table, it provides a clear target and basis for subsequent data parsing and import. Then, based on the service file format of the service data file, the target parsing rule is matched in the preset parsing rule library, transforming the traditional manual parsing process into an automated parsing based on the file format, and achieving efficient parsing of different types of service data files. Based on the target parsing rule, the service data file is field-parsed to obtain multiple data field information, ensuring the complete extraction of data fields. Subsequently, by matching the data field information of the service data file with the target field information in the target data table, the import mapping relationship is determined, ensuring the accurate mapping and import of data fields. Then, according to the target parsing rule, the service data file is structurally split to obtain structured service data, ensuring the standardized and normalized processing of data. Finally, the structured service data is imported into the target data table according to the import mapping relationship, ensuring the consistency and integrity of data import. Through the above method, the present invention can efficiently and accurately parse and import data files in different service scenarios, improving the efficiency of importing multi-class service data into the database.

[0151] Please refer to Figure 8 , the embodiment of the present application also provides an import device for multi-class service data, which can implement the above method for importing multi-class service data. The device includes:

[0152] An acquisition module, configured to acquire a service data import request, as well as the service data file and the target data table corresponding to the service data import request; wherein, the target data table contains multiple target field information;

[0153] A parsing rule module, configured to parse the service data file to obtain the corresponding service file format, and determine the target parsing rule corresponding to the service file format in the preset parsing rule library;

[0154] A data field module, configured to perform field parsing on the service data file based on the target parsing rule to obtain multiple data field information of the service data file;

[0155] An import mapping module, configured to match the data field information with each target field information in the target data table for each data field information to determine the import mapping relationship between each data field information and the target field information;

[0156] A splitting module, configured to structurally split the service data file according to the target parsing rule to obtain structured service data;

[0157] An import module, configured to import the structured service data into the target data table according to the import mapping relationship.

[0158] The specific implementation manner of the multi-class service data import device is basically the same as the specific embodiment of the above multi-class service data import method, and will not be elaborated here.

[0159] An embodiment of the present application further provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the above multi-class service data import method is implemented. The electronic device can be any intelligent terminal including a tablet computer, a vehicle-mounted computer, etc.

[0160] Please refer to Fig. 9 , Fig. 9 which schematically shows the hardware structure of an electronic device in another embodiment. The electronic device includes:

[0161] A processor 901, which can be implemented in ways such as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided by the embodiments of the present application;

[0162] A memory 902, which can be implemented in forms such as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an operating system and other application programs. When implementing the technical solutions provided by the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 902, and the processor 901 is called to execute the multi-class service data import method of the embodiments of the present application;

[0163] An input / output interface 903, which is used to implement information input and output;

[0164] A communication interface 904, which is used to implement communication interaction between this device and other devices, and can implement communication through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.);

[0165] A bus 905, which transmits information between various components of the device (such as the processor 901, the memory 902, the input / output interface 903, and the communication interface 904);

[0166] Among them, the processor 901, the memory 902, the input / output interface 903, and the communication interface 904 are communicatively connected to each other inside the device through the bus 905.

[0167] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above method for importing multiple types of service data is implemented.

[0168] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above networks include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0169] The method and apparatus for importing multiple types of service data, an electronic device, and a storage medium proposed in the present application obtain a service data import request, as well as a service data file and a target data table corresponding to the service data import request; wherein the target data table contains multiple target field information; parse the service data file to obtain the corresponding service file format, and determine the target parsing rule corresponding to the service file format in a preset parsing rule library; perform field parsing on the service data file based on the target parsing rule to obtain multiple data field information of the service data file; for each data field information, match the data field information with each target field information in the target data table to determine the import mapping relationship between each data field information and the target field information; perform structured splitting on the service data file according to the target parsing rule to obtain structured service data; and import the structured service data into the target data table according to the import mapping relationship.

[0170] According to the method for importing multiple types of service data provided by the present invention, first, by obtaining a service data import request, the corresponding service data file, and the target data table, it provides a clear target and basis for subsequent data parsing and import; then, based on the service file format of the service data file, it matches the target parsing rule in the preset parsing rule library, transforms the traditional manual parsing process into an automated parsing based on the file format, and realizes the efficient parsing of different types of service data files; based on the target parsing rule, it performs field parsing on the service data file to obtain multiple data field information, ensuring the complete extraction of data fields; subsequently, by matching the data field information of the service data file with the target field information in the target data table, it determines the import mapping relationship, ensuring the accurate mapping and import of data fields; then, according to the target parsing rule, it performs structured splitting on the service data file to obtain structured service data, ensuring the standardized and normalized processing of data; finally, it imports the structured service data into the target data table according to the import mapping relationship, ensuring the consistency and integrity of data import. Through the above method, the present invention can efficiently and accurately parse and import data files in different service scenarios, improving the efficiency of importing multiple types of service data into the database.

[0171] The embodiments described in the embodiments of the present application are for more clearly illustrating the technical solutions of the embodiments of the present application, and do not constitute a limitation to the technical solutions provided by the embodiments of the present application. Those skilled in the art know that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

[0172] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation to the embodiments of the present application, and may include more or fewer steps than shown in the figures, or combine certain steps, or different steps.

[0173] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0174] Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices can be implemented as software, firmware, hardware, and their appropriate combinations.

[0175] In the description of this application and the above-mentioned accompanying drawings, terms such as "first", "second", "third", "fourth", etc. (if any) are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments of this application described here can be implemented in an order different from those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that comprises a series of steps or units does not necessarily have 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.

[0176] It should be understood that in this application, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects and indicates that there can be three relationships. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist at the same time. Here, A and B can be singular or plural. The character " / " generally means that the associated objects before and after are in an "or" relationship. "At least one (one) of the following" or its similar expressions refer to any combination of these items, including any combination of single items (ones) or plural items (ones). For example, at least one (one) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0177] In several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the above-mentioned division of units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of devices or units can be in electrical, mechanical, or other forms.

[0178] The units described above as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0179] In addition, in each embodiment of the present application, each functional unit may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of a software functional unit.

[0180] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product. The computer software product is stored in a storage medium and includes multiple instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in the various embodiments of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs that can store programs.

[0181] The preferred embodiments of the embodiments of the present application have been described above with reference to the accompanying drawings. However, this does not limit the scope of the rights of the embodiments of the present application. Any modifications, equivalent replacements, and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall fall within the scope of the rights of the embodiments of the present application.

Claims

1. A method for importing multiple types of business data, characterized in that: The method comprises: Obtaining a business data import request, and a business data file and a target data table corresponding to the business data import request; wherein the target data table includes a plurality of target field information; Parsing the business data file to obtain a corresponding business file format, and determining a target parsing rule corresponding to the business file format in a preset parsing rule library; Performing field parsing on the business data file based on the target parsing rule to obtain multiple data field information of the business data file; For each of the data field information, matching the data field information with each of the target field information in the target data table to determine an import mapping relationship between each of the data field information and the target field information; Structurally splitting the business data file according to the target parsing rule to obtain structured business data; The structured business data is imported into the target data table according to the import mapping relationship.

2. The method for importing multiple types of business data according to claim 1, characterized in that: The target parsing rules include text parsing rules, table parsing rules and structured data parsing rules. The business data file is structured and split according to the target parsing rules to obtain structured business data, including: If the business file format is a text file format, the data content in the business data file is segmented into fields according to the delimiter identifier preset in the text parsing rule to obtain the structured business data; If the business file format is a spreadsheet format, then according to the cell location identifier preset in the table parsing rule, field extraction is performed on the table content in the business data file to obtain the structured business data; If the business file format is a structured data format, the structured business data is obtained by parsing the key-value pairs or tag structures in the business data file according to the data structure configuration preset in the structured data parsing rule.

3. The method for importing multiple types of business data according to claim 1, characterized in that: Before obtaining the business data import request, the method further includes: Obtaining the permission application of the target object for the target data table; A temporary operation permission for the target data table is generated according to the permission application; wherein the temporary operation permission includes a validity period identifier, which is used to set the temporary operation permission to be invalid after the validity period identifier expires.

4. The method for importing multiple types of business data according to claim 1, characterized in that: For each of the data field information, matching the data field information with each of the target field information in the target data table to determine an import mapping relationship between each of the data field information and the target field information includes: For each piece of data field information, traverse and compare the data field information with the target field information; In response to detecting that there is a field in the plurality of data field information that does not match the target field information, sending a field supplement request to the target object; Receiving the field supplementary information returned by the target object; The import mapping relationship is updated according to the field supplementary information.

5. The method for importing multiple types of business data according to claim 1, characterized in that: After importing the structured business data into the target data table according to the import mapping relationship, the method further includes: Performing abnormal data detection processing on the structured business data to obtain an abnormal data detection result; If the anomaly detection result indicates that the structured business data contains abnormal data, the abnormal data is temporarily stored in a preset abnormal data cache; wherein the abnormal data includes format abnormal data whose data format does not meet the preset format requirements, encoding abnormal data whose data encoding does not meet the preset encoding requirements, and quantity abnormal data whose number of fields is inconsistent with the number of fields of the target field information; Generate an exception data report based on the exception data cache and return it to the target object.

6. The method for importing multiple types of business data according to claim 1, characterized in that: The method further comprises: Receive the scheduled import task configuration information sent by the user, wherein the scheduled import task configuration information includes the scheduled execution time; Generate a scheduled import task for the business data file according to the scheduled import task configuration information; When it is detected that the scheduled execution time has arrived, the import operation of the business data file is automatically executed.

7. The method for importing multiple types of business data according to claim 1, characterized in that: The method further comprises: Generate import progress information of the structured business data; wherein the import progress information includes the amount of imported data, the amount of remaining data, and the import time; Pushing the import progress information to the target object in real time; In response to obtaining the import interruption instruction sent by the target object, stop the current import operation and generate statistical information of the data imported before the interruption time point; The data statistics information is returned to the target object.

8. A device for importing multiple types of business data, characterized in that: The device comprises: An acquisition module, used to acquire a business data import request, and a business data file and a target data table corresponding to the business data import request; wherein the target data table contains a plurality of target field information; A parsing rule module, used to parse the business data file to obtain a corresponding business file format, and determine a target parsing rule corresponding to the business file format in a preset parsing rule library; A data field module, used to perform field parsing on the business data file based on the target parsing rule to obtain multiple data field information of the business data file; An import mapping module, for matching the data field information with each target field information in the target data table for each data field information, so as to determine an import mapping relationship between each data field information and the target field information; A splitting module, used for performing structured splitting on the business data file according to the target parsing rule to obtain structured business data; An import module is used to import the structured business data into the target data table according to the import mapping relationship.

9. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the method for importing multiple types of business data as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the method for importing multiple types of business data according to any one of claims 1 to 7.

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