Verification method and device for business data

Abstract

The application provides a business data verification method and device, and relates to the technical field of data processing. The application collects structured first business data from various institutions; identifies a matter identifier carried by the first business data to determine a target matter corresponding to the first business data; obtains a stage parameter related to the target matter in the first business data to identify a target matter monitoring stage currently reached by the target matter; determines at least one type of field that needs to be extracted from the first business data according to the target matter monitoring stage, and extracts the at least one type of field from the first business data as a to-be-verified field of the first business data; determines one or more to-be-verified objects associated with the target matter according to the to-be-verified field; determines monitoring information and attribute information of the to-be-verified objects, performs rule verification on the to-be-verified field according to the monitoring information and the attribute information, and determines a data verification result of the first business data according to a field verification result of the to-be-verified field.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method and apparatus for verifying business data. Background Technology

[0002] With the development of information technology, government agencies and enterprises need to process increasingly large-scale datasets. In practical applications, government agencies such as departments and general offices of the state often need to collect data from different sources and conduct comprehensive analysis to formulate policies or provide decision support. However, during the data exchange process, data quality issues often affect the reliability of the final analysis results. Therefore, an effective data processing and verification method is needed to ensure data quality. Summary of the Invention

[0003] This disclosure provides a method and apparatus for verifying business data, so as to at least solve the problem of data quality being difficult to guarantee in related technologies.

[0004] The first aspect of this application proposes a method for verifying business data, comprising: collecting structured first business data from various organizations; identifying the item identifier carried by the first business data and determining the target item corresponding to the first business data based on the item identifier; obtaining stage parameters related to the target item in the first business data and identifying the target item monitoring stage currently in which the target item is located based on the stage parameters; determining at least one type of field to be extracted from the first business data based on the target item monitoring stage, and extracting at least one type of field from the first business data as the field to be verified of the first business data; determining one or more objects to be verified associated with the target item based on the field to be verified; determining the monitoring information and attribute information of the objects to be verified, performing rule verification on the field to be verified based on the monitoring information and attribute information, and determining the data verification result of the first business data based on the field verification result of the field to be verified.

[0005] According to one embodiment of this application, the business data verification method further includes: in response to the target matter monitoring stage being a management relationship determination stage, extracting a management relationship field from the first business data as a field to be verified; and in response to the target matter monitoring stage being a management implementation update stage, extracting a management implementation field from the first business data as a field to be verified.

[0006] According to one embodiment of this application, in response to the field to be verified being a management relationship field, determining one or more objects to be verified associated with the target item based on the field to be verified includes: obtaining the management organization included in the management relationship field as the object to be verified; determining the monitoring information and attribute information of the object to be verified, and performing rule verification on the field to be verified based on the monitoring information and attribute information, including: determining the management flag and attribute information of the object to be verified, wherein the attribute information includes the affiliation information and / or organizational level of the management organization; in response to the management flag indicating that the management organization is in a management state for the target item, obtaining the management jurisdiction to which the management organization belongs based on the affiliation information; and performing rule verification on the management relationship field based on the management jurisdiction to which the management organization belongs and / or the organizational level of the management organization.

[0007] According to one embodiment of this application, a rule-based verification of the management relationship field is performed based on the management jurisdiction to which the management agency belongs and / or the agency's organizational level. This includes: obtaining candidate agencies belonging to the management jurisdiction and obtaining the management flag of each candidate agency for the target matter; if any candidate agency's management flag for the target matter indicates a management status, then the management relationship field is determined to have failed verification; and / or, comparing the organizational level with a preset organizational level that has the management qualification for the target matter to determine whether the management agency has the management qualification for the target matter; if the management agency does not have the management qualification for the target matter, then the management relationship field is determined to have failed verification.

[0008] According to one embodiment of this application, in response to the field to be verified being a management implementation field, determining one or more objects to be verified associated with a target item based on the field to be verified includes: obtaining target sub-items included in the management implementation field as objects to be verified, wherein the target sub-items belong to the target item; determining the monitoring information and attribute information of the objects to be verified, and performing rule verification on the field to be verified based on the monitoring information and attribute information, including: determining the first status information and attribute information of the objects to be verified, wherein the attribute information includes the number of implementation lists of the target sub-items; in response to the first status information indicating that the target sub-item is in a deleted state, obtaining the second status information of the sub-item implementation list corresponding to the target sub-item; and performing rule verification on the management implementation field based on the number of implementation lists of the target sub-item and / or the second status information of the sub-item implementation list corresponding to the target sub-item.

[0009] According to one embodiment of this application, rule verification is performed on the management implementation field based on the number of implementation lists of the target sub-item and / or the second status information of the sub-item implementation list corresponding to the target sub-item, including: in response to the number of implementation lists of the target sub-item being greater than a preset number threshold, it is determined that the management implementation field has failed verification; and / or, in response to the second status information indicating that the sub-item implementation list corresponding to the target sub-item is in an existing state, it is determined that the management implementation field has failed verification.

[0010] According to one embodiment of this application, the business data verification method further includes: in response to the target matter monitoring stage being a management relationship determination stage, extracting a first identification field to be verified from the first business data and performing validity verification on the first identification field to be verified; in response to the presence of identification information that has failed verification in the first identification field to be verified, determining that the first identification field to be verified has failed verification; or, in response to the target matter monitoring stage being a management implementation update stage, extracting a second identification field to be verified from the first business data and performing validity verification on the second identification field to be verified; in response to the presence of identification information that has failed verification in the second identification field to be verified, determining that the second identification field to be verified has failed verification.

[0011] According to one embodiment of this application, after collecting structured first business data from various institutions, the method further includes: obtaining the source institution and timestamp corresponding to the first business data; determining the source data table corresponding to the first business data based on the source institution; storing the first business data in the source data table; and generating data tags for the first business data based on the source institution and timestamp.

[0012] According to one embodiment of this application, after determining the data verification result of the first business data, the method further includes: filtering out the verified second business data from the first business data based on the data verification result; integrating the business data based on the second business data to obtain the integrated business data table; and performing business indicator analysis based on the business data table to generate indicator analysis results.

[0013] According to one embodiment of this application, business data integration is performed based on second business data to obtain a business data table generated after integration, including: for each piece of second business data, obtaining the business primary key contained in the second business data, and obtaining the business primary key related data corresponding to the business primary key; determining the business data table corresponding to the business primary key related data according to the business primary key; and integrating the business primary key related data into the business data table according to preset organizational priority information and data tags.

[0014] According to one embodiment of this application, the business data verification method further includes: in response to a data verification result indicating that the first business data verification has failed, obtaining the verification failure field of the first business data; generating a verification failure reason for the first business data based on the verification failure field, and sending the verification failure reason to the source organization of the first business data.

[0015] According to one embodiment of this application, the business data verification method further includes: receiving a query statement sent by a client; parsing the query statement to obtain the target business data table and query range corresponding to the query statement; obtaining relevant data from the target business data table based on the query range; and returning the relevant data to the client.

[0016] A second aspect of this application provides a business data verification device, comprising: a data acquisition module for collecting structured first business data from various organizations; a first identification module for identifying a matter identifier carried by the first business data and determining the target matter corresponding to the first business data based on the matter identifier; a second identification module for acquiring stage parameters related to the target matter in the first business data and identifying the target matter monitoring stage currently in which the target matter is located based on the stage parameters; a field extraction module for determining at least one type of field to be extracted from the first business data based on the target matter monitoring stage, and extracting at least one type of field from the first business data as the field to be verified of the first business data; and a rule verification module for determining one or more objects to be verified associated with the target matter based on the field to be verified, determining the monitoring information and attribute information of the objects to be verified, performing rule verification on the field to be verified based on the monitoring information and attribute information, and determining the data verification result of the first business data based on the field verification result of the field to be verified.

[0017] According to one embodiment of this application, the field extraction module is further configured to: extract a management relationship field from the first business data as a field to be verified in response to the target matter monitoring stage being a management relationship determination stage; and extract a management implementation field from the first business data as a field to be verified in response to the target matter monitoring stage being a management implementation update stage.

[0018] According to one embodiment of this application, the rule verification module is further configured to: obtain the management institutions included in the management relationship field as the objects to be verified; determine the management flag and attribute information of the objects to be verified, wherein the attribute information includes the affiliation information and / or organizational level of the management institution; in response to the management flag indicating that the management institution is in a management state for the target matter, obtain the management jurisdiction to which the management institution belongs based on the affiliation information; and perform rule verification on the management relationship field based on the management jurisdiction to which the management institution belongs and / or the organizational level of the management institution.

[0019] According to one embodiment of this application, the rule verification module is further configured to: obtain candidate institutions belonging to the management jurisdiction, and obtain the management flag of each candidate institution for the target matter; in response to any candidate institution having a management flag indicating a management status for the target matter, determine that the management relationship field has failed verification; and / or, compare the institution level with a preset institution level that has the management qualification for the target matter to determine whether the management institution has the management qualification for the target matter; in response to the management institution not having the management qualification for the target matter, determine that the management relationship field has failed verification.

[0020] According to one embodiment of this application, the rule verification module is further configured to: obtain target sub-items included in the management implementation field as objects to be verified, wherein the target sub-items belong to target items; determine the first status information and attribute information of the objects to be verified, wherein the attribute information includes the number of implementation lists of the target sub-items; in response to the first status information indicating that the target sub-item is in a deleted state, obtain the second status information of the sub-item implementation list corresponding to the target sub-item; and perform rule verification on the management implementation field according to the number of implementation lists of the target sub-items and / or the second status information of the sub-item implementation list corresponding to the target sub-item.

[0021] According to one embodiment of this application, the rule verification module is further configured to: determine that the management implementation field has failed verification if the number of implementation lists of the target sub-item is greater than a preset number threshold; and / or, determine that the management implementation field has failed verification if the second status information indicates that the sub-item implementation list corresponding to the target sub-item is in an existing state.

[0022] According to one embodiment of this application, the rule verification module is further configured to: in response to the target matter monitoring stage being a management relationship determination stage, extract a first identification field to be verified from the first business data, and perform validity verification on the first identification field to be verified; in response to the presence of identification information that fails verification in the first identification field to be verified, determine that the first identification field to be verified has failed verification; or, in response to the target matter monitoring stage being a management implementation update stage, extract a second identification field to be verified from the first business data, and perform validity verification on the second identification field to be verified; in response to the presence of identification information that fails verification in the second identification field to be verified, determine that the second identification field to be verified has failed verification.

[0023] According to one embodiment of this application, the data acquisition module is further configured to: acquire the source organization and timestamp corresponding to the first business data; determine the source data table corresponding to the first business data based on the source organization; store the first business data in the source data table, and generate a data tag for the first business data based on the source organization and timestamp.

[0024] According to one embodiment of this application, the business data verification device further includes: a data integration module, used to filter out verified second business data from the first business data based on the data verification result, integrate the business data based on the second business data, and obtain a business data table generated after integration; and an indicator analysis module, used to perform business indicator analysis based on the business data table and generate indicator analysis results.

[0025] According to one embodiment of this application, the data integration module is further configured to: for each piece of second business data, obtain the business primary key contained in the second business data, and obtain the business primary key related data corresponding to the business primary key; determine the business data table corresponding to the business primary key related data based on the business primary key; and integrate the business primary key related data into the business data table based on preset organizational priority information and data tags.

[0026] According to one embodiment of this application, the rule verification module is further configured to: in response to a data verification result indicating that the verification of the first business data has failed, obtain the verification failure field of the first business data; generate a verification failure reason for the first business data based on the verification failure field, and send the verification failure reason to the source organization of the first business data.

[0027] According to one embodiment of this application, the business data verification device further includes: a query module, configured to receive a query statement sent by a client, parse the query statement, obtain the target business data table and query range corresponding to the query statement, obtain relevant data from the target business data table based on the query range, and return the relevant data to the client.

[0028] A third aspect of this application provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to implement a business data verification method as described in the first aspect of this application.

[0029] A fourth aspect of this application provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to implement a method for verifying business data as described in a first aspect of this application.

[0030] The fifth aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the business data verification method as described in the first aspect of this application.

[0031] The technical solutions provided by the embodiments of this disclosure bring at least the following beneficial effects: This application performs rule verification by structuring business data, identifying target items, and determining fields to be verified according to the target item monitoring stage. The automated verification process reduces the possibility of human error, which can significantly improve the efficiency and quality of business data processing, while ensuring the accuracy and compliance of the data. Furthermore, after the business data is verified, it helps to conduct subsequent business analysis to obtain more accurate analysis data.

[0032] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0033] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0034] Figure 1 This is a schematic diagram illustrating an exemplary implementation of a business data verification method according to one embodiment of this application.

[0035] Figure 2 This is a schematic diagram illustrating an exemplary implementation of a business data verification method according to one embodiment of this application.

[0036] Figure 3 This is a schematic diagram illustrating an exemplary implementation of a business data verification method according to one embodiment of this application.

[0037] Figure 4 This is a schematic diagram of a business data verification device shown in one embodiment of this application.

[0038] Figure 5 This is a schematic diagram of a business data verification device shown in one embodiment of this application.

[0039] Figure 6 This is a schematic diagram of an electronic device according to one embodiment of this application. Detailed Implementation

[0040] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0041] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application all comply with the relevant provisions of national laws and regulations.

[0042] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0043] The following is a description of some of the technical terms used in this application:

[0044] Item: An item refers to a specific activity or task that defines the main objectives and scope of the activity. For example, "food safety inspection" can be considered an item.

[0045] Sub-items: Sub-items refer to specific inspection items or tasks under an item, representing a further breakdown of the item. For example, under the item "Food Safety Inspection," there may be sub-items such as "Food Production License Inspection" and "Food Label Compliance Inspection."

[0046] Implementation list of sub-items: The implementation list of sub-items refers to the specific implementation details and standards for a particular sub-item.

[0047] Figure 1 This is a schematic diagram illustrating an exemplary implementation of a business data verification method as shown in this application, such as... Figure 1 As shown, the verification method for this business data includes the following steps:

[0048] S101 collects structured first business data from various agencies.

[0049] Structured business data is collected from various sources (such as different organizations and departments) as the primary business data. This can be achieved through various methods, including exporting from a database, importing from files, and making API requests.

[0050] Structured data refers to data with a fixed format or finite length, which facilitates subsequent data processing and analysis.

[0051] S102, identify the item identifier carried by the first business data, and determine the target item corresponding to the first business data based on the item identifier.

[0052] Each item corresponds to a unique item identifier.

[0053] For example, if the first business data is data related to food quality supervision, the target item corresponding to the first business data can be identified as "food quality supervision" based on the item identifier carried by the first business data.

[0054] S103, obtain the stage parameters related to the target item from the first business data, and identify the target item monitoring stage that the target item is currently in based on the stage parameters.

[0055] For example, if the stage parameter of the first business data is intended to express the management relationship between the target matter and its related institutions, such as a matter claiming form, then the target matter monitoring stage in which the first business data is located can be determined as the management relationship determination stage. For example, if the first business data is intended to express that the target matter is managed by institution A, it can also be understood that institution A has claimed the management rights over the target matter. For example, if the first business data is intended to express that the Food and Drug Administration has claimed the management rights over the matter of "food quality supervision," then the target matter monitoring stage in which the first business data is located can be determined as the management relationship determination stage.

[0056] For example, if the stage parameter of the first business data is intended to express relevant update information during the implementation of the target matter, such as the stage parameter being an instruction to create an implementation list, then the target matter monitoring stage in which the first business data is located can be determined to be the management implementation update stage. For example, this could refer to the creation or updating of a relevant implementation list for the target matter, or the relevant management data for the target matter (such as penalty information imposed on a company by law enforcement personnel based on a certain implementation list).

[0057] S104, determine at least one type of field that needs to be extracted from the first business data based on the target item monitoring stage, and extract at least one type of field from the first business data as the field to be verified in the first business data.

[0058] Based on the current monitoring stage of the target item, determine which fields are necessary for verification, and extract these fields from the first business data as the fields to be verified in the first business data.

[0059] S105, Based on the fields to be verified, determine one or more objects to be verified associated with the target item.

[0060] The object to be verified refers to the object that needs to be verified contained in the field to be verified. For example, if the field to be verified includes the management organization corresponding to the first business data, and it is pre-set that the authenticity of the management organization or whether the organization level of the management organization meets the requirements needs to be verified, then the management organization will be the object that needs to be verified contained in the field to be verified.

[0061] S106, determine the monitoring information and attribute information of the object to be verified, perform rule verification on the field to be verified based on the monitoring information and attribute information, and determine the data verification result of the first business data based on the field verification result of the field to be verified.

[0062] The monitoring information may include the management flag or status information of the object to be verified, which generally refers to information that is subject to change. For example, if the object to be verified is the management organization corresponding to the first business data, the monitoring information may be the management flag of the management organization, which indicates whether the management organization is currently in a management status for the target matter.

[0063] Among them, the attribute information is the self-attribute of the object to be verified. For example, if the object to be verified is the management organization corresponding to the first business data, the attribute information can be the organization level information or the subordinate information of the management organization.

[0064] Obtain the verification rules corresponding to each field to be verified, and perform rule verification on each field to be verified based on the verification rules, and obtain the field verification result for each field to be verified.

[0065] If all fields to be verified in the first business data pass the verification, then the first business data is deemed to have passed the verification.

[0066] If any field in the first business data fails verification, then the first business data is determined to have failed verification.

[0067] The verification rules include, but are not limited to, the following:

[0068] 1. Within the same administrative jurisdiction, a matter can only be claimed by one organization (to avoid unclear authority over the matter).

[0069] 2. Cross-level claims of matters are not permitted.

[0070] 3. Each item may include one or more sub-items, but each sub-item can only have one implementation list (to avoid multiple sets of management standards for one sub-item).

[0071] 4. To delete a sub-item, you must first delete the implementation list corresponding to that sub-item.

[0072] This application proposes a method for verifying business data, comprising: collecting structured first business data from various organizations; identifying the item identifier carried by the first business data and determining the target item corresponding to the first business data based on the item identifier; obtaining stage parameters related to the target item in the first business data and identifying the target item monitoring stage currently in which the target item is located based on the stage parameters; determining at least one type of field to be extracted from the first business data based on the target item monitoring stage, and extracting at least one type of field from the first business data as the field to be verified of the first business data; determining one or more objects to be verified associated with the target item based on the field to be verified; determining the monitoring information and attribute information of the objects to be verified, performing rule verification on the field to be verified based on the monitoring information and attribute information, and determining the data verification result of the first business data based on the field verification result of the field to be verified. This application performs rule-based verification by structuring business data, identifying target items, and determining fields to be verified based on the monitoring stage of the target items. Through an automated verification process, the possibility of human error is reduced, which can significantly improve the efficiency and quality of business data processing, while ensuring the accuracy and compliance of the data. Furthermore, after the business data is verified, it helps to obtain more accurate analytical data for subsequent business analysis.

[0073] Furthermore, if the data verification result indicates that the verification of the first business data failed, the verification failure field of the first business data is retrieved; based on the verification failure field, a reason for the verification failure of the first business data is generated and sent to the source organization of the first business data. In this way, the field causing the verification failure of the first business data can be accurately identified, ensuring that the reason for the verification failure is promptly communicated to the relevant organization, forming a feedback loop, ensuring that the problem is resolved, and after the relevant organization modifies the business data that failed verification, the modified business data can be received again and the data verification can be performed again.

[0074] Figure 2 This is a schematic diagram illustrating an exemplary implementation of a business data verification method as shown in this application, such as... Figure 2 As shown, the verification method for this business data includes the following steps:

[0075] S201 collects structured first business data from various agencies.

[0076] S202, identify the item identifier carried by the first business data, and determine the target item corresponding to the first business data based on the item identifier.

[0077] S203, obtain the stage parameters related to the target item from the first business data, and identify the target item monitoring stage that the target item is currently in based on the stage parameters.

[0078] For details on the specific implementation of steps S201 to S203, please refer to the relevant parts of the above embodiments, which will not be repeated here.

[0079] S204, in response to the target item monitoring phase being the management relationship determination phase, extract the management relationship field from the first business data as the field to be verified.

[0080] Among them, the management relationship field refers to the field related to the management relationship of the target matter, such as the management organization and management mark fields.

[0081] S205, in response to the target item monitoring phase being the management implementation update phase, extract the management implementation field from the first business data as the field to be verified.

[0082] Among them, the management implementation field refers to the fields related to the management implementation process of the target matter, such as sub-items, implementation list, and other fields.

[0083] S206, Based on the fields to be verified, determine one or more objects to be verified associated with the target item.

[0084] S207, determine the monitoring information and attribute information of the object to be verified, and perform rule verification on the field to be verified based on the monitoring information and attribute information.

[0085] If the field to be verified is a management relationship field, then obtain the management institutions included in the management relationship field as the objects to be verified; then determine the management flag (here the management flag is used as the monitoring information of the objects to be verified) and attribute information of the objects to be verified, and perform rule verification on the fields to be verified according to the management flag and attribute information.

[0086] As a possible scenario, the attribute information of the management organization includes its affiliation information. If the management flag indicates that the management organization has a management status for the target item, the management jurisdiction to which the management organization belongs is obtained based on the affiliation information. Candidate organizations belonging to the management jurisdiction are then identified, and the management flag for each candidate organization regarding the target item is retrieved. If any candidate organization's management flag for the target item indicates a management status, then the management relationship field fails verification. The corresponding verification rule here is: within the same management jurisdiction, a single item can only be claimed by one organization. This ensures that no two or more management organizations simultaneously possess management authority over the same target item, avoiding potential permission conflicts or management confusion.

[0087] As another possible scenario, the management organization's attribute information includes its organizational level. This level is compared to a preset level of organization with the qualification to manage the target matter to determine if the management organization is qualified to manage it. If the management organization is deemed not qualified, the management relationship field fails verification. The corresponding verification rule here is: cross-level claiming of matters is not allowed. This ensures the effectiveness and compliance of management activities by confirming whether the management organization's level meets the preset standards.

[0088] If the field to be verified is a management implementation field, then the target sub-items included in the management implementation field are obtained as the objects to be verified. The target sub-items belong to the scope of the target items. The first status information (here, the first status information is used as the monitoring information of the objects to be verified) and attribute information of the objects to be verified are determined. The attribute information includes the number of implementation lists of the target sub-items. The fields to be verified are verified according to the rules based on the first status information and attribute information.

[0089] As a possible scenario, if the number of implementation lists for a target sub-item exceeds a preset threshold (set to 1 in this application), the management implementation field is deemed to have failed verification. The corresponding verification rule here is: each sub-item can only have one implementation list. This ensures that each sub-item has only one implementation list, preventing multiple sets of management standards from appearing for the same sub-item during management implementation.

[0090] As another possible scenario, if the first status information indicates that the target sub-item is in a deleted state, the second status information of the sub-item implementation list corresponding to the target sub-item is obtained. If the second status information indicates that the sub-item implementation list corresponding to the target sub-item is in an existing state, then it is determined that the management implementation field has failed verification. The corresponding verification rule here is: if a sub-item is to be deleted, the implementation list corresponding to that sub-item must first be deleted. Since deleting a sub-item means no longer managing that sub-item, the corresponding implementation list also needs to be deleted to avoid implementation list data residue.

[0091] S208, determine the data verification result of the first business data based on the field verification result of the field to be verified.

[0092] If all fields to be verified in the first business data pass the verification, then the first business data is deemed to have passed the verification.

[0093] If any field in the first business data fails verification, then the first business data is determined to have failed verification.

[0094] This application embodiment determines the fields to be verified based on the target item monitoring stage for rule verification, and details the verification rules for each field, which can significantly improve the efficiency and quality of business data processing, while ensuring the accuracy and compliance of the data. Furthermore, after the business data is verified, it helps to conduct subsequent business analysis to obtain more accurate analytical data.

[0095] Furthermore, in order to ensure the validity of the first business data and avoid the presence of expired identification information in the first business data, this application also needs to verify the relevant identifications contained in the first business data.

[0096] As one feasible approach, in response to the target item monitoring phase being the management relationship determination phase, the first verification identifier field is extracted from the first business data. Here, the first verification identifier field refers to the identifier field in the first business data that needs to be validated during the management relationship determination phase, such as item code, department code, etc.

[0097] After determining the first identifier field to be verified, the validity of the first identifier field to be verified is verified. If there is an identifier information in the first identifier field to be verified that has failed verification, it is determined that the first identifier field to be verified has failed verification, that is, the first business data has failed verification.

[0098] As another feasible approach, in response to the target item monitoring phase becoming the management implementation update phase, a second verification identifier field is extracted from the first business data. This second verification identifier field is an identifier field in the first business data during the management implementation update phase that requires validity verification; examples include identifier fields such as item codes, sub-item codes, and implementation list codes.

[0099] After determining the second identifier field to be verified, the validity of the second identifier field to be verified is verified. If there is an identifier information in the second identifier field to be verified that has failed verification, it is determined that the second identifier field to be verified has failed verification, that is, the first business data has failed verification.

[0100] Among them, the identifier fields contained in the first and second identifier fields to be verified may be duplicated. For example, both may have an item code.

[0101] Figure 3 This is a schematic diagram illustrating an exemplary implementation of a business data verification method as shown in this application, such as... Figure 3 As shown, the verification method for this business data includes the following steps:

[0102] S301 collects structured first business data from various agencies.

[0103] The process, after collecting structured first business data from various institutions, also includes: obtaining the source institution and timestamp corresponding to the first business data; determining the source data table corresponding to the first business data based on the source institution; storing the first business data in the source data table; and generating data tags for the first business data based on the source institution and timestamp. This allows the first business data to be stored in the corresponding source data table based on its source institution, facilitating retrieval of the first business data when needed.

[0104] S302, identify the item identifier carried by the first business data, and determine the target item corresponding to the first business data based on the item identifier.

[0105] S303, obtain the stage parameters related to the target item from the first business data, and identify the target item monitoring stage that the target item is currently in based on the stage parameters.

[0106] S304, based on the target item monitoring phase, determine at least one type of field that needs to be extracted from the first business data, and extract at least one type of field from the first business data as the field to be verified in the first business data.

[0107] S305, Based on the fields to be verified, determine one or more objects to be verified associated with the target item;

[0108] S306, determine the monitoring information and attribute information of the object to be verified, perform rule verification on the field to be verified based on the monitoring information and attribute information, and determine the data verification result of the first business data based on the field verification result of the field to be verified.

[0109] For details on the specific implementation of steps S302 to S306, please refer to the relevant parts of the above embodiments, which will not be repeated here.

[0110] S307, Based on the data verification results, select the verified second business data from the first business data.

[0111] The first business data that passes verification will be used as the second business data.

[0112] S308, integrate business data based on the second business data, and obtain the business data table generated after integration.

[0113] Based on the second business data, business data is integrated to obtain the resulting business data table. This includes: for each piece of second business data, obtaining the business primary key contained in that second business data, and obtaining the business primary key-related data corresponding to that business primary key; determining the business data table corresponding to the business primary key-related data based on the business primary key; and integrating the business primary key-related data into the business data table.

[0114] For example, if a certain business data table is specifically used to store data related to law enforcement personnel, then the business primary key corresponding to the business data table is the ID number of the law enforcement personnel. That is, the ID number of the law enforcement personnel contained in the second business data, as well as the business primary key related data of the law enforcement personnel contained in the second business data (such as the law enforcement personnel's gender, education, etc.), are obtained and integrated into the business data table of law enforcement personnel related data.

[0115] If multiple records for the same business primary key are present, the latest timestamp will be used as the first criterion based on the preset institutional priority information and data tags. If the timestamps are the same, the data from the source institution with the higher priority will be used to integrate the business primary key related data into the business data table.

[0116] The business data table is used to store data from different organizations that share the same business primary key. For example, the law enforcement personnel data of organizations A, B, and C are all stored in the same business data table for law enforcement personnel.

[0117] After integrating the business data tables, a batch number (with a time field for easy subsequent traceability) is added to each business data table.

[0118] S309 performs business indicator analysis based on business data tables and generates indicator analysis results.

[0119] For example, a business data table used to store data related to law enforcement personnel can be used to analyze the distribution of education level and gender among law enforcement personnel.

[0120] For example, for a business data table used to store data related to matters, analysis can be performed on the number of claimed matters, the number of claimed matters, the number of new matters, the number of new sub-items, the matter coverage rate, the number of administrative inspection matters, the number of mandatory inspection matters, and the number of administrative penalty matters.

[0121] For example, for a business data table used to store data related to managed objects, analysis can be performed on the total number of managed objects, the proportion of enterprises among the managed objects, the average number of times each enterprise is inspected, and the enterprise problem detection rate.

[0122] This application embodiment determines the fields to be verified based on the target item monitoring stage for rule verification, which can significantly improve the efficiency and quality of business data processing, while ensuring the accuracy and compliance of the data. Furthermore, after the business data is verified, it is integrated into the relevant business data table, making the analysis results of relevant business indicators more accurate.

[0123] Furthermore, in addition to calculating relevant metrics, users often need to query business data. Accordingly, the system receives query statements sent by the client; parses the query statements to obtain the target business data table and query range corresponding to the query statement; retrieves relevant data from the target business data table based on the query range, and returns the relevant data to the client. This facilitates users' querying of relevant data in the business data table, and by quickly and accurately returning query results, it enhances the system's interactivity and usability, and improves user satisfaction.

[0124] Figure 4 This is a schematic diagram of a business data verification device shown in this application, such as... Figure 4 As shown, the business data verification device 400 includes a data acquisition module 401, a first identification module 402, a second identification module 403, a field extraction module 404, and a rule verification module 405, wherein:

[0125] Data acquisition module 401 is used to collect structured first business data from various organizations.

[0126] The first identification module 402 is used to identify the item identifier carried by the first business data and determine the target item corresponding to the first business data based on the item identifier.

[0127] The second identification module 403 is used to obtain the stage parameters related to the target item in the first business data, and identify the target item monitoring stage that the target item is currently in based on the stage parameters.

[0128] The field extraction module 404 is used to determine, based on the target item monitoring stage, at least one type of field that needs to be extracted from the first business data, and to extract at least one type of field from the first business data as the field to be verified in the first business data.

[0129] The rule verification module 405 is used to determine one or more objects to be verified associated with the target item based on the field to be verified, determine the monitoring information and attribute information of the objects to be verified, perform rule verification on the field to be verified based on the monitoring information and attribute information, and determine the data verification result of the first business data based on the field verification result of the field to be verified.

[0130] This device performs rule-based verification by structuring business data, identifying target items, and determining fields to be verified based on the monitoring stage of the target items. Through an automated verification process, it reduces the possibility of human error, significantly improving the efficiency and quality of business data processing while ensuring data accuracy and compliance. Furthermore, verified business data helps in subsequent business analysis to obtain more accurate analytical data.

[0131] Furthermore, the field extraction module 404 is also used to: extract the management relationship field from the first business data as a field to be verified in response to the target item monitoring stage being the management relationship determination stage; and extract the management implementation field from the first business data as a field to be verified in response to the target item monitoring stage being the management implementation update stage.

[0132] Furthermore, the rule verification module 405 is also used to: obtain the management institutions included in the management relationship field as the objects to be verified; determine the management flag and attribute information of the objects to be verified, wherein the attribute information includes the affiliation information and / or organizational level of the management institution; in response to the management flag indicating that the management institution is in a management state for the target matter, obtain the management jurisdiction to which the management institution belongs based on the affiliation information; and perform rule verification on the management relationship field based on the management jurisdiction to which the management institution belongs and / or the organizational level of the management institution.

[0133] Furthermore, the rule verification module 405 is also used to: obtain candidate institutions belonging to the management jurisdiction, and obtain the management flag of each candidate institution for the target matter; in response to the existence of any candidate institution whose management flag for the target matter indicates a management status, determine that the management relationship field has failed verification; and / or, compare the institution level with the preset institution level that has the management qualification for the target matter to determine whether the management institution has the management qualification for the target matter; in response to the management institution not having the management qualification for the target matter, determine that the management relationship field has failed verification.

[0134] Furthermore, the rule verification module 405 is also used to: obtain the target sub-items included in the management implementation field as the objects to be verified, wherein the target sub-items belong to the target items; determine the first status information and attribute information of the objects to be verified, wherein the attribute information includes the number of implementation lists of the target sub-items; in response to the first status information indicating that the target sub-item is in a deleted state, obtain the second status information of the sub-item implementation list corresponding to the target sub-item; and perform rule verification on the management implementation field according to the number of implementation lists of the target sub-items and / or the second status information of the sub-item implementation list corresponding to the target sub-item.

[0135] Furthermore, the rule verification module 405 is also used to: determine that the management implementation field has failed verification if the number of implementation lists of the target sub-item is greater than a preset number threshold; and / or, determine that the management implementation field has failed verification if the second status information indicates that the sub-item implementation list corresponding to the target sub-item is in an existing state.

[0136] Furthermore, the rule verification module 405 is also used to: in response to the target item monitoring stage being the management relationship determination stage, extract a first identification field to be verified from the first business data, and perform validity verification on the first identification field to be verified; if there is identification information that fails verification in the first identification field to be verified, then determine that the first identification field to be verified has failed verification; or, in response to the target item monitoring stage being the management implementation update stage, extract a second identification field to be verified from the first business data, and perform validity verification on the second identification field to be verified; if there is identification information that fails verification in the second identification field to be verified, then determine that the second identification field to be verified has failed verification.

[0137] Furthermore, the data acquisition module 401 is also used to: acquire the source organization and timestamp corresponding to the first business data; determine the source data table corresponding to the first business data based on the source organization; store the first business data in the source data table, and generate data tags for the first business data based on the source organization and timestamp.

[0138] Furthermore, the business data verification device 400 also includes: a data integration module, used to filter out the verified second business data from the first business data according to the data verification results, integrate the business data based on the second business data, and obtain the integrated business data table; and an indicator analysis module, used to perform business indicator analysis based on the business data table and generate indicator analysis results.

[0139] Furthermore, the data integration module is also used to: for each piece of second business data, obtain the business primary key contained in the second business data, and obtain the business primary key related data corresponding to the business primary key; determine the business data table corresponding to the business primary key related data based on the business primary key; and integrate the business primary key related data into the business data table based on the preset organizational priority information and data tags.

[0140] Furthermore, the rule verification module 405 is also used to: in response to the data verification result indicating that the first business data verification failed, obtain the verification failure field of the first business data; generate the verification failure reason of the first business data based on the verification failure field, and send the verification failure reason to the source organization of the first business data.

[0141] Furthermore, the business data verification device 400 also includes a query module, which is used to receive query statements sent by the client, parse the query statements, obtain the target business data table and query range corresponding to the query statements, obtain relevant data from the target business data table based on the query range, and return the relevant data to the client.

[0142] Figure 5This is a schematic diagram of a business data verification device shown in one embodiment of this application, as follows: Figure 5 As shown, the business data verification device can be divided into 5 layers: aggregation layer, verification layer, integration layer, analysis layer, and push layer.

[0143] The aggregation layer includes a data acquisition module.

[0144] The verification layer includes a first identification module, a second identification module, a field extraction module, and a rule verification module.

[0145] The integration layer includes a data integration module.

[0146] The analysis layer includes an indicator analysis module.

[0147] The functions of each module have been described in detail in the relevant sections above, and will not be repeated here.

[0148] The push layer includes an analysis result push module, which is used to push the indicator analysis data obtained by the analysis layer to an external integrated platform.

[0149] The verification device for business data can be a data warehouse.

[0150] When the aggregation layer acquires data, it can use SQOOP to extract data from the business relational database to the distributed file system (Hadoop Distributed File System, HDFS) and automatically create tables on Hive to achieve automated data extraction. At the same time, the extracted data is tagged with timestamps and data source tags.

[0151] The verification layer uses Spark to verify the data in the aggregation layer of Hive according to business rules. At the same time, data that fails to meet the business rules is tagged and sent back to the source organization. After the source organization fixes the problem, it resubmits the data, thus forming a closed loop in the data chain.

[0152] In this application, Airflow is used for the scheduling and management of data verification tasks. Each step of data processing is configured within the scheduler, which reflects the detailed processing process and establishes data lineage. The scheduling configuration is written in Python scripts, and scheduling failure alarms are added. The system is integrated with external software to send failed scheduling log messages to the external software for alerting.

[0153] In this application, Spark and MapReduce are used as distributed computing engines.

[0154] To implement the above embodiments, this application also proposes an electronic device 600, such as... Figure 6 As shown, the electronic device 600 includes a processor 601 and a memory 602 communicatively connected to the processor. The memory 602 stores instructions that can be executed by at least one processor. The instructions are executed by at least one processor 601 to implement the business data verification method as shown in the above embodiment.

[0155] To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to implement the business data verification method shown in the above embodiments.

[0156] To implement the above embodiments, this application also proposes a computer program product, including a computer program that, when executed by a processor, implements the business data verification method shown in the above embodiments.

[0157] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., indicating the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application.

[0158] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0159] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0160] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0161] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for verifying business data, characterized in that, include: Collect structured primary business data from various institutions; Identify the item identifier carried by the first business data, and determine the target item corresponding to the first business data based on the item identifier; Obtain the stage parameters related to the target matter from the first business data, and identify the target matter monitoring stage currently in which the target matter is located based on the stage parameters. If the stage parameters of the first business data are intended to express the management relationship between the target matter and its related institutions, the target matter monitoring stage in which the first business data is located is determined to be the management relationship determination stage. If the stage parameters of the first business data are intended to express the relevant update information during the implementation of the target matter, the target matter monitoring stage in which the first business data is located is determined to be the management implementation update stage. In response to the target matter monitoring stage being the management relationship determination stage, the management relationship field is extracted from the first business data as a field to be verified. The management relationship field refers to the field related to the management relationship of the target matter. The management organization included in the management relationship field is obtained as the object to be verified. The management flag and attribute information of the object to be verified are determined, wherein the attribute information includes the affiliation information and / or organizational level of the management organization. In response to the management flag indicating that the management organization is in a management status for the target matter, the management jurisdiction to which the management organization belongs is obtained according to the affiliation information. The management relationship field is then verified according to rules based on the management jurisdiction to which the management organization belongs and / or the organizational level of the management organization. In response to the target item monitoring stage being a management implementation update stage, the management implementation field is extracted from the first business data as a field to be verified. The management implementation field refers to the field related to the management implementation process of the target item. The target sub-items included in the management implementation field are obtained as objects to be verified, wherein the target sub-items belong to the target item. The first status information and attribute information of the objects to be verified are determined, wherein the attribute information includes the number of implementation lists of the target sub-items. In response to the first status information indicating that the target sub-item is in a deleted state, the second status information of the sub-item implementation list corresponding to the target sub-item is obtained. According to the number of implementation lists of the target sub-item and / or the second status information of the sub-item implementation list corresponding to the target sub-item, rule verification is performed on the management implementation field. The data verification result of the first business data is determined based on the field verification result of the field to be verified.

2. The method according to claim 1, characterized in that, The step of performing rule verification on the management relationship field based on the management jurisdiction to which the management organization belongs and / or the organizational level of the management organization includes: Obtain candidate organizations belonging to the management jurisdiction, and obtain the management flag of each candidate organization for the target matter. In response to any candidate organization having a management flag indicating a management status for the target matter, determine that the management relationship field has failed verification; and / or, The management organization is compared with the preset organization level that has the management qualification for the target matter to determine whether the management organization has the management qualification for the target matter. If the management organization does not have the management qualification for the target matter, the management relationship field is determined to have failed the verification.

3. The method according to claim 1, characterized in that, The step of performing rule verification on the management implementation field based on the number of implementation lists of the target sub-item and / or the second status information of the sub-item implementation list corresponding to the target sub-item includes: If the number of implementations for the target sub-item exceeds a preset threshold, then the management implementation field is determined to have failed verification; and / or, If the second status information indicates that the sub-item implementation list corresponding to the target sub-item is in an existing state, then it is determined that the management implementation field has failed verification.

4. The method according to any one of claims 1-3, characterized in that, The method further includes: In response to the target item monitoring stage being the management relationship determination stage, a first verification identifier field is extracted from the first business data, and the validity of the first verification identifier field is verified. If there is any failed verification identifier information in the first verification identifier field, then it is determined that the first verification identifier field has failed verification; or... In response to the target item monitoring stage being the management implementation update stage, a second verification identifier field is extracted from the first business data, and the validity of the second verification identifier field is verified. If there is an identifier information that fails verification in the second verification identifier field, it is determined that the second verification identifier field has failed verification.

5. The method according to claim 1, characterized in that, After collecting the structured first business data from various institutions, the process also includes: Obtain the source organization and timestamp corresponding to the first business data; The source data table corresponding to the first business data is determined based on the source organization; The first business data is stored in the source data table, and a data tag for the first business data is generated based on the source organization and the timestamp.

6. The method according to claim 5, characterized in that, After determining the data verification result of the first business data, the method further includes: Based on the data verification results, the second business data that has passed verification is selected from the first business data; Based on the second business data, integrate the business data to obtain the integrated business data table; Based on the business data table, business indicator analysis is performed to generate indicator analysis results.

7. The method according to claim 6, characterized in that, The step of integrating business data based on the second business data to obtain the integrated business data table includes: For each piece of the second business data, obtain the business primary key contained in the second business data, and obtain the business primary key related data corresponding to the business primary key; Determine the business data table corresponding to the business primary key based on the business primary key; Based on the preset organization priority information and combined with the data tags, the business primary key related data is integrated into the business data table.

8. The method according to claim 6, characterized in that, The method further includes; In response to the data verification result indicating that the first business data verification failed, the field indicating that the first business data verification failed is retrieved; Based on the verification failure field, a reason for the verification failure of the first business data is generated, and the reason for the verification failure is sent to the source organization of the first business data.

9. The method according to claim 6, characterized in that, The method further includes; Receive query statements sent by the client; The query statement is parsed to obtain the target business data table and query range corresponding to the query statement; Based on the query range, relevant data is retrieved from the target business data table and returned to the client.

10. A verification device for business data, characterized in that, include: The data acquisition module is used to collect structured primary business data from various organizations; The first identification module is used to identify the item identifier carried by the first business data and determine the target item corresponding to the first business data based on the item identifier. The second identification module is used to obtain the stage parameters related to the target matter in the first business data, and identify the target matter monitoring stage currently in which the target matter is located according to the stage parameters. If the stage parameters of the first business data are intended to express the management relationship between the target matter and its related institutions, the target matter monitoring stage in which the first business data is located is determined to be the management relationship determination stage. If the stage parameters of the first business data are intended to express the relevant update information during the implementation of the target matter, the target matter monitoring stage in which the first business data is located is determined to be the management implementation update stage. The field extraction module is used to extract management relationship fields from the first business data as fields to be verified in response to the target item monitoring stage being the management relationship determination stage, wherein the management relationship fields refer to fields related to the management relationship of the target item; and to extract management implementation fields from the first business data as fields to be verified in response to the target item monitoring stage being the management implementation update stage, wherein the management implementation fields refer to fields related to the management implementation process of the target item. The rule verification module is used to: In response to the target matter monitoring stage being a management relationship determination stage, obtain the management institutions included in the management relationship field as verification objects; determine the management flag and attribute information of the verification objects, wherein the attribute information includes the affiliation information and / or organizational level of the management institution; In response to the management flag indicating that the management institution is in a management status for the target matter, obtain the management jurisdiction to which the management institution belongs based on the affiliation information; Perform rule verification on the management relationship field based on the management jurisdiction to which the management institution belongs and / or the organizational level of the management institution; In response to the target matter monitoring stage being a management implementation update stage, retrieve... The management implementation field includes target sub-items as objects to be verified, wherein the target sub-items belong to the target item; determine the first status information and attribute information of the objects to be verified, wherein the attribute information includes the number of implementation lists of the target sub-items; in response to the first status information indicating that the target sub-item is in a deleted state, obtain the second status information of the sub-item implementation list corresponding to the target sub-item; perform rule verification on the management implementation field according to the number of implementation lists of the target sub-item and / or the second status information of the sub-item implementation list corresponding to the target sub-item; and determine the data verification result of the first business data according to the field verification result of the fields to be verified.

11. The apparatus according to claim 10, characterized in that, The rule verification module is also used for: Obtain candidate organizations belonging to the management jurisdiction, and obtain the management flag of each candidate organization for the target matter. In response to any candidate organization having a management flag indicating a management status for the target matter, determine that the management relationship field has failed verification; and / or, The management organization is compared with the preset organization level that has the management qualification for the target matter to determine whether the management organization has the management qualification for the target matter. If the management organization does not have the management qualification for the target matter, the management relationship field is determined to have failed the verification.

12. The apparatus according to claim 10, characterized in that, The rule verification module is also used for: If the number of implementations for the target sub-item exceeds a preset threshold, then the management implementation field is determined to have failed verification; and / or, If the second status information indicates that the sub-item implementation list corresponding to the target sub-item is in an existing state, then it is determined that the management implementation field has failed verification.

13. The apparatus according to any one of claims 10-12, characterized in that, The rule verification module is also used for: In response to the target item monitoring stage being the management relationship determination stage, a first verification identifier field is extracted from the first business data, and the validity of the first verification identifier field is verified. If there is any failed verification identifier information in the first verification identifier field, then it is determined that the first verification identifier field has failed verification; or... In response to the target item monitoring stage being the management implementation update stage, a second verification identifier field is extracted from the first business data, and the validity of the second verification identifier field is verified. If there is an identifier information that fails verification in the second verification identifier field, it is determined that the second verification identifier field has failed verification.

14. The apparatus according to claim 10, characterized in that, The data acquisition module is also used for: Obtain the source organization and timestamp corresponding to the first business data; The source data table corresponding to the first business data is determined based on the source organization; The first business data is stored in the source data table, and a data tag for the first business data is generated based on the source organization and the timestamp.

15. The apparatus according to claim 14, characterized in that, The device further includes: The data integration module is used to filter out the verified second business data from the first business data according to the data verification result, integrate the business data based on the second business data, and obtain the integrated business data table. The indicator analysis module is used to perform business indicator analysis based on the business data table and generate indicator analysis results.

16. The apparatus according to claim 15, characterized in that, The data integration module is also used for: For each piece of the second business data, obtain the business primary key contained in the second business data, and obtain the business primary key related data corresponding to the business primary key; Determine the business data table corresponding to the business primary key based on the business primary key; Based on the preset organization priority information and combined with the data tags, the business primary key related data is integrated into the business data table.

17. The apparatus according to claim 15, characterized in that, The rule verification module is also used for: In response to the data verification result indicating that the first business data verification failed, the field indicating that the first business data verification failed is retrieved; Based on the verification failure field, a reason for the verification failure of the first business data is generated, and the reason for the verification failure is sent to the source organization of the first business data.

18. The apparatus according to claim 15, characterized in that, The device further includes: The query module is used to receive query statements sent by the client, parse the query statements, obtain the target business data table and query range corresponding to the query statements, obtain relevant data from the target business data table based on the query range, and return the relevant data to the client.

19. An electronic device comprising: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-9.

20. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-9.

21. A computer program product comprising a computer program that, when executed by a processor, implements the steps of the method according to any one of claims 1-9.

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