Data processing method and device, storage medium and electronic equipment

Abstract

The invention discloses a data processing method and device, a storage medium and electronic equipment. The method relates to the field of big data, and comprises the following steps: obtaining a target service message, the target service message comprising aviation service data to be published by an aviation institution; determining at least one target verification rule matched with the service data from a plurality of data verification rules according to the service data in the target service message; and performing data verification on the business data based on the at least one target verification rule to obtain a verification result, the verification result being used for representing whether the business data is abnormal or not. According to the invention, the technical problem of low detection accuracy caused by the fact that whether the business data to be published are abnormal or not depends on manual detection in related technologies is solved.

Description

Technical Field

[0001] The present invention relates to the field of big data, and in particular to a data processing method, device, storage medium and electronic device. Background Art

[0002] In recent years, with the booming aviation industry, continuous technological advancements, and intensified market competition, adjustments to aviation business data (e.g., flight prices) have become increasingly frequent and complex. Faced with large-scale flight data, passenger information, and price fluctuations, the publication of erroneous business data (e.g., incorrect airfares) is highly susceptible to errors. This not only impacts the economic performance of aviation organizations, but can also harm consumer rights and reduce customer satisfaction.

[0003] Currently, related technologies rely on traditional manual monitoring methods to detect whether there are anomalies in the business data to be released, which results in a problem of low detection accuracy.

[0004] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0005] Embodiments of the present invention provide a data processing method, device, storage medium, and electronic device to at least solve the technical problem in related technologies of relying on manual detection of whether business data to be published is abnormal, resulting in low detection accuracy.

[0006] According to one aspect of an embodiment of the present invention, a data processing method is provided, comprising: obtaining a target business message, wherein the target business message includes aviation business data to be released by an aviation agency; determining, based on the business data in the target business message, at least one target verification rule that matches the business data from a plurality of data verification rules; performing data verification on the business data based on the at least one target verification rule to obtain a verification result, wherein the verification result is used to characterize whether there is an anomaly in the business data.

[0007] Furthermore, the data processing method also includes: extracting target information from the business data, wherein the target information includes at least one of the following: organizational information of the aviation agency, data source channels associated with the business data; obtaining the association relationship between multiple data verification rules and organizational information of multiple aviation agencies and multiple data source channels; based on the association relationship and the target information, determining at least one target verification rule that matches the business data from multiple data verification rules.

[0008] Furthermore, the data processing method also includes: based on the association relationship, determining a data verification rule that matches the target information from multiple data verification rules to obtain at least one candidate verification rule; extracting multiple business fields from the business data, and for each candidate verification rule, when all business condition fields in the candidate verification rule belong to multiple business fields, determining the candidate verification rule as the target verification rule.

[0009] Furthermore, the data processing method also includes: before determining at least one target verification rule that matches the business data from multiple data verification rules based on the business data in the target business message, obtaining multiple initial data verification rules, wherein the target threshold in the initial data verification rule is a null value; for each initial data verification rule, when the verification threshold input by the target object is received, updating the target threshold in the initial data verification rule based on the verification threshold to obtain the data verification rule; when the verification threshold is not received, updating the target threshold in the initial data verification rule based on the published historical business data to obtain the data verification rule.

[0010] Furthermore, the data processing method also includes: determining target historical business data that matches the initial data verification rules from the published historical business data; based on the threshold type in the initial data verification rules, determining the maximum or minimum value corresponding to the threshold type from the target historical business data; updating the target threshold in the initial data verification rules based on the maximum or minimum value corresponding to the threshold type to obtain the data verification rules.

[0011] Furthermore, the data processing method also includes: when all target verification rules pass the data verification of the business data, determining that the verification result indicates that there is no abnormality in the business data; when there are target verification rules that fail the data verification of the business data, determining that the verification result indicates that there is an abnormality in the business data.

[0012] Furthermore, the data processing method also includes: after obtaining the verification result, if the verification result indicates that the business data is abnormal, generating warning information based on the verification result, and sending the warning information to the target object based on at least one information push channel.

[0013] According to another aspect of an embodiment of the present invention, a data processing device is also provided, including: a first acquisition module, used to acquire a target business message, wherein the target business message includes aviation business data to be released by an aviation agency; a determination module, used to determine at least one target verification rule that matches the business data from multiple data verification rules based on the business data in the target business message; a verification module, used to perform data verification on the business data based on at least one target verification rule to obtain a verification result, wherein the verification result is used to characterize whether there is an abnormality in the business data.

[0014] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, in which a computer program is stored. The computer program is configured to execute the above-mentioned data processing method when running.

[0015] According to another aspect of an embodiment of the present invention, an electronic device is also provided, which includes one or more processors; a memory for storing one or more programs, which enables the one or more processors to run the programs when the one or more programs are executed by the one or more processors, wherein the programs are configured to execute the above-mentioned data processing method when running.

[0016] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program / instruction, which implements the above-mentioned data processing method when the computer program / instruction is executed by a processor.

[0017] In an embodiment of the present invention, a method is employed to detect whether business data to be published contains anomalies based on data verification rules that match the business data to be published. A target business message is obtained, and then, based on the business data in the target business message, at least one target verification rule that matches the business data is determined from multiple data verification rules. The business data is then verified based on the at least one target verification rule to obtain a verification result. The target business message includes aviation business data to be published by an aviation organization, and the verification result is used to indicate whether the business data contains anomalies.

[0018] In the above process, by determining at least one target verification rule that matches the service data in the target service message from multiple data verification rules, the appropriate data verification rule is selected based on the aviation service data to be released, thereby improving the accuracy of the determined target verification rule. By performing data verification on the service data based on at least one target verification rule and obtaining a verification result, the service data is verified according to the targeted data verification rule, thereby effectively improving detection accuracy.

[0019] It can be seen from this that the solution provided by this application achieves the purpose of detecting whether the business data to be published has anomalies based on the data verification rules that match the business data to be published, thereby achieving the technical effect of improving the detection accuracy, and further solving the technical problem of relying on manual detection of whether the business data to be published has anomalies, resulting in low detection accuracy in related technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0021] Figure 1 is a schematic diagram of an optional data processing method according to an embodiment of the present invention;

[0022] Figure 2 is a schematic diagram of an optional method for determining data verification rules according to an embodiment of the present invention;

[0023] Figure 3 is a schematic diagram of an optional target processing system according to an embodiment of the present invention;

[0024] Figure 4 is a flow chart of an optional data processing method according to an embodiment of the present invention;

[0025] Figure 5 is a schematic diagram of an optional data processing device according to an embodiment of the present invention;

[0026] Figure 6 is a schematic diagram of an optional electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0030] Example 1

[0031] According to an embodiment of the present invention, an embodiment of a data processing method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0032] Figure 1 is a schematic diagram of an optional data processing method according to an embodiment of the present invention, such as Figure 1 As shown, the method includes the following steps:

[0033] Step S101: Acquire a target business message, wherein the target business message includes aviation business data to be released by an aviation organization.

[0034] Alternatively, electronic devices, application systems, servers, and other devices may be used as the execution entities of this application. In this embodiment, the target processing system is used as the execution entity to execute the above-mentioned data processing method. In an optional embodiment, the target processing system may be a freight rate publishing system, which supports multiple deployment modes, including standalone and embedded deployment.

[0035] Optionally, the target business message may be sent by an aviation agency. When the aviation agency is ready to release aviation business data, the aviation agency may send the target business message to the target processing system through various channels (such as the fare management system within the aviation agency, the fare management system of a third-party cooperative agency, etc.). The target business message includes the aviation business data to be released by the aviation agency. After receiving the target business message, the target processing system verifies the aviation business data in the target business message. If the verification passes, the aviation business data is released to the corresponding channel. After the aviation business data is released, users (such as users who hope to purchase air tickets) can view the relevant business data through software, applets, web pages, etc. On the contrary, if the verification fails, it is prohibited to release the aviation business data to the corresponding channel. In this case, the user cannot view the relevant business data through software, applets, web pages, etc.

[0036] Optionally, aviation business data refers to data related to aviation business. For example, aviation business data may be air fares. In layman's terms, aviation business data may be air ticket prices.

[0037] Step S102: Determine, based on the service data in the target service message, at least one target verification rule that matches the service data from a plurality of data verification rules.

[0038] Optionally, after acquiring the target business message, the target processing system may extract business data from the target business message. The business data is the data to be released by the aviation agency, that is, the data to be verified.

[0039] Optionally, data verification rules are used to verify whether there are any anomalies in the business data. The data verification rules include conditions that must be met to determine whether the business data is normal business data. For example, an optional data verification rule may be "the flight price does not exceed 1,000 yuan."

[0040] Optionally, the target processing system may determine at least one target verification rule that matches the business data from multiple data verification rules based on the data content of the business data. For example, for verifying airfares, at least one target verification rule that matches the business data may be determined from multiple data verification rules based on factors such as airline information (i.e., airline agency information), route, and date in the business data.

[0041] Optionally, when adding new data risk warning functions in the future, you only need to configure the corresponding data verification rules without modifying the underlying code, which can simplify the operation and management process, reduce the complexity and labor costs of the system, and enhance the adaptability of this application to different business scenarios.

[0042] Step S103 , performing data verification on the business data based on at least one target verification rule to obtain a verification result, wherein the verification result is used to indicate whether there is an anomaly in the business data.

[0043] Optionally, for each target verification rule, the target processing system may perform data verification on the business data based on the target verification rule to obtain a verification sub-result corresponding to the target verification rule, where the verification sub-result indicates whether the data verification of the business data by the target verification rule has passed.

[0044] Optionally, after obtaining the syndrome results corresponding to all target verification rules, a verification result is determined based on the syndrome results corresponding to all target verification rules, and the verification result is used to indicate whether there is an anomaly in the business data.

[0045] Based on the scheme defined in steps S101 to S103 above, it can be seen that in this embodiment of the present invention, a method of detecting whether the business data to be published contains anomalies is adopted based on data verification rules that match the business data to be published. By obtaining a target business message, and then, based on the business data in the target business message, determining at least one target verification rule that matches the business data from multiple data verification rules, the business data is verified based on the at least one target verification rule to obtain a verification result. The target business message includes aviation business data to be published by an aviation organization, and the verification result is used to indicate whether the business data contains anomalies.

[0046] It is easy to note that in the above process, by determining at least one target verification rule that matches the business data from multiple data verification rules based on the business data in the target business message, the appropriate data verification rule is selected based on the aviation business data to be released, thereby improving the accuracy of the determined target verification rule. By performing data verification on the business data based on at least one target verification rule and obtaining a verification result, the business data is verified according to the targeted data verification rule, thereby effectively improving detection accuracy.

[0047] It can be seen from this that the solution provided by this application achieves the purpose of detecting whether the business data to be published has anomalies based on the data verification rules that match the business data to be published, thereby achieving the technical effect of improving the detection accuracy, and further solving the technical problem of relying on manual detection of whether the business data to be published has anomalies, resulting in low detection accuracy in related technologies.

[0048] In an optional embodiment, based on the business data in the target business message, at least one target verification rule that matches the business data is determined from multiple data verification rules, including: extracting target information from the business data, wherein the target information includes at least one of the following: organizational information of the aviation agency, data source channels associated with the business data; obtaining associations between multiple data verification rules and organizational information of multiple aviation agencies and multiple data source channels; based on the associations and the target information, determining at least one target verification rule that matches the business data from multiple data verification rules.

[0049] Optionally, the aviation agency's organizational information may be the aviation agency's code, name, etc. This information is used to determine the airline to which the data to be published belongs, and then select data verification rules applicable to the airline.

[0050] Optionally, the data source channel associated with business data refers to the method by which the business data is generated or collected. For example, the data source channel can be an airline's internal fare management system or a fare management system of a third-party partner. Different data source channels may correspond to different data verification requirements.

[0051] Optionally, the target processing system may be pre-configured to include associations between multiple data validation rules and the organizational information of multiple aviation agencies and multiple data source channels. For example, a database may maintain an association list, where each data item in the association list represents an association relationship, and each data item records an association relationship between a data validation rule and the organizational information of an aviation agency and a data source channel.

[0052] Alternatively, the target processing system can find data validation rules that match the target information from the association relationship, and thereby determine the target validation rule based on the data validation rules that match the target information. For example, the data validation rule that matches the target information can be directly determined as the target validation rule. In another example, the data validation rules that match the target information can be filtered based on the data content of the business data to obtain the target validation rule.

[0053] Optionally, if the target information includes organization information and data source channels, the data verification rules associated with the organization information and data source channels are determined as the data verification rules that match the target information.

[0054] Optionally, if the target information only includes organization information (or only includes data source channels), the data verification rules associated with the organization information (or data source channels) are determined as data verification rules that match the target information.

[0055] It should be noted that, through the above method, data verification rules are matched based on at least one of the organization information in the business data and the data source channel, thereby improving the accuracy of the determined target verification rules.

[0056] In an optional embodiment, based on the association relationship and target information, at least one target verification rule that matches the business data is determined from multiple data verification rules, including: based on the association relationship, determining the data verification rule that matches the target information from multiple data verification rules to obtain at least one candidate verification rule; extracting multiple business fields from the business data, and for each candidate verification rule, if all business condition fields in the candidate verification rule belong to multiple business fields, determining the candidate verification rule as the target verification rule.

[0057] Optionally, if the target information includes organization information and data source channels, the data verification rules associated with the organization information and data source channels are determined as data verification rules that match the target information, that is, determined as candidate verification rules.

[0058] Optionally, if the target information only includes institutional information (or only includes data source channels), the data verification rules associated with the institutional information (or data source channels) are determined as data verification rules that match the target information, that is, determined as candidate verification rules.

[0059] Optionally, the data verification rules include a business condition field, a business comparison field, and a target threshold. The business condition field is used to limit the scope of application of the data verification rule, that is, under what specific conditions the rule takes effect. For example, the business condition field can be a specific flight number, date, cabin, passenger type (adult, infant, etc.), etc. The business comparison field is a specific business indicator that needs to be verified. For example, the business comparison field can be a fare, and its value will be compared with the target threshold to determine whether the business data exceeds the normal range. The target threshold represents the boundary condition for business data to be considered normal data. If the value of the business comparison field exceeds this limit, it is determined that the data verification rule has failed the data verification of the business data.

[0060] Optionally, the target processing system can extract multiple business fields from the business data. Business fields include, but are not limited to, specific flight numbers, dates, cabins, passenger types (adults, infants, etc.), fares, etc. Then, for each candidate verification rule, if all business condition fields in the candidate verification rule belong to multiple business fields in the business data, the candidate verification rule is determined as the target verification rule. Conversely, if there are business condition fields in the candidate verification rule that do not belong to multiple business fields in the business data, the candidate verification rule is not determined as the target verification rule.

[0061] For example, if the business condition field in the candidate verification rule is the "adult" passenger type, and multiple business fields in the business data are the "infant" passenger type, it is determined that the candidate verification rule is not the target verification rule.

[0062] For another example, if the business condition fields in the candidate verification rule are class A and passenger type "adult", and the multiple business fields in the business data are class A, passenger type "adult" and flight number XY123, then the candidate verification rule is determined to be the target verification rule.

[0063] In some embodiments, if the service comparison field is unique, that is, it is the fare, then the service data must include the fare by default. In this case, there is no need to determine the target verification rule in conjunction with the service comparison field.

[0064] In some embodiments, if the business comparison field is not unique, that is, it can be a ticket price or a ticket discount (i.e., a discount, such as 20% off), the target verification rule can be determined in combination with the business comparison field. For example, for each candidate verification rule, if all business condition fields and business comparison fields in the candidate verification rule belong to multiple business fields, the candidate verification rule is determined as the target verification rule. Conversely, if there is a business condition field or a business comparison field in the candidate verification rule that does not belong to multiple business fields in the business data, the candidate verification rule is not determined as the target verification rule.

[0065] It should be noted that by determining the target verification rule in combination with the business field, the accuracy of the determined target verification rule can be further improved, and the situation of invalid data verification due to lack of comparison conditions can be avoided.

[0066] In an optional embodiment, before determining at least one target verification rule that matches the business data from multiple data verification rules based on the business data in the target business message, the method also includes: obtaining multiple initial data verification rules, wherein the target threshold in the initial data verification rule is a null value; for each initial data verification rule, when the verification threshold input by the target object is received, updating the target threshold in the initial data verification rule based on the verification threshold to obtain the data verification rule; when the verification threshold is not received, updating the target threshold in the initial data verification rule based on the published historical business data to obtain the data verification rule.

[0067] Optionally, the initial data validation rules include a business condition field, a business comparison field, and a target threshold. The business condition field and the business comparison field in the initial data validation rules are pre-populated, but the target threshold is left blank. For example, the initial data validation rules may be pre-entered into the target processing system by personnel of the relevant aviation agency.

[0068] Optionally, the target processing system is provided with a check trigger time, which can be understood as a time point used to determine whether it is necessary to determine the target threshold based on the published historical business data. For example, the check trigger time may be 1 a.m. every day. Figure 2 is a schematic diagram of an optional method for determining data verification rules according to an embodiment of the present invention, such as Figure 2As shown, the target processing system can obtain initial data verification rules from the database. After obtaining the initial data verification rules, if a verification threshold is received from the target subject (e.g., staff or administrators of various aviation agencies), the target threshold in the initial data verification rules is updated based on the verification threshold. In other words, the target threshold in the initial data verification rules is set as the verification threshold to obtain the data verification rules. If the verification threshold is not received when the current time point reaches the check trigger time, the target threshold in the initial data verification rules can be updated based on the published historical business data to obtain the data verification rules.

[0069] After obtaining the data verification rules, such as Figure 2 As shown, data validation rules can be stored in a specified data table in the database and written to the cache to reduce the frequency of interaction between the target processing system and the database, providing fast and efficient access support for subsequent data processing and early warning triggering. In addition, the target processing system can also implement a clustered deployment strategy, fully leveraging the rich resources and multi-threaded operation advantages of the cluster to achieve efficient parallel execution of validation tasks, thereby optimizing resource utilization and validation task execution efficiency.

[0070] It should be noted that, through the above method, even in the absence of human intervention, the target processing system can automatically determine the target threshold, thereby improving the reliability of determining data verification rules and improving the applicability of this application.

[0071] In an optional embodiment, the target threshold in the initial data verification rule is updated based on the published historical business data to obtain the data verification rule, including: determining the target historical business data that matches the initial data verification rule from the published historical business data; based on the threshold type in the initial data verification rule, determining the maximum value or minimum value corresponding to the threshold type from the target historical business data; updating the target threshold in the initial data verification rule based on the maximum value or minimum value corresponding to the threshold type to obtain the data verification rule.

[0072] Optionally, the target processing system can determine target historical business data that matches the initial data verification rules from the published historical business data based on the organization information, data source channels, and business fields in the published historical business data. For example, the target processing system can preset multiple initial data verification rules and target association relationships between the organization information of multiple aviation organizations and multiple data source channels. The target processing system can determine candidate historical business data that matches the initial data verification rules from the published historical business data based on the target association relationship and the initial data verification rules. The method of determining whether the initial data verification rules and historical business data match based on the target association relationship is the same as the method of determining whether the data verification rules and business data match based on the association relationship, so it will not be repeated here.

[0073] In an optional embodiment, after the candidate historical business data is determined, for each candidate historical business data, if the candidate historical business data includes all the business condition fields in the current initial data verification rules, the candidate historical business data is determined to be the target historical business data; otherwise, the candidate historical business data is determined not to be the target historical business data.

[0074] In an optional embodiment, for each candidate historical business data, if the candidate historical business data includes all business condition fields and business comparison fields in the current initial data verification rules, the candidate historical business data is determined to be the target historical business data; otherwise, the candidate historical business data is determined not to be the target historical business data.

[0075] After the target historical business data is determined, the maximum or minimum value corresponding to the threshold type is determined from the target historical business data based on the threshold type in the initial data verification rule. For example, the threshold type can be the air ticket price, the air ticket discount strength (i.e., discount, such as 20% off, 70% off, etc.). Optionally, the initial data verification rule can also include a comparison operator (such as greater than the target threshold, less than the target threshold, etc.). Therefore, the target processing system can determine the maximum or minimum value corresponding to the threshold type from the target historical business data based on the threshold type and comparison method in the initial data verification rule.

[0076] For example, assuming that the threshold type is air ticket price and the comparison operator is "greater than target threshold", the minimum value of the air ticket price is determined from the target historical business data, and the minimum value of the air ticket price is determined as the target threshold in the initial data verification rule to obtain the data verification rule.

[0077] For another example, assuming that the threshold type is the air ticket discount strength and the comparison operator is "less than the target threshold", the maximum value of the air ticket discount is determined from the target historical business data, and the maximum value of the air ticket discount is determined as the target threshold in the initial data verification rule to obtain the data verification rule.

[0078] It should be noted that, through the above method, the target threshold is determined based on historical business data that matches the initial data verification rules, thereby improving the accuracy of the determined target threshold and avoiding the problem of low accuracy of the verification results due to improper threshold setting.

[0079] In an optional embodiment, data verification is performed on business data based on at least one target verification rule to obtain a verification result, including: when all target verification rules pass the data verification of the business data, determining that the verification result indicates that there is no abnormality in the business data; when there is a target verification rule that fails the data verification of the business data, determining that the verification result indicates that there is an abnormality in the business data.

[0080] Optionally, for each target verification rule, the target processing system may compare the business comparison field in the business data with the target threshold in the target verification rule. If the corresponding data in the business data falls within the threshold range defined by the target threshold, the data verification is determined to have passed. Otherwise, the data verification is determined to have failed.

[0081] For example, assuming that a target verification rule is "adult air tickets do not exceed 1,500 yuan", and the business data is "adult air tickets from City A to City B are 1,600 yuan", then the business comparison field in the business data is "1600", the target threshold in the target verification rule is 1,500, the comparison operator is "does not exceed", and the threshold range divided by the target threshold is [0, 1500]. Therefore, the air ticket price in the business data does not fall within the threshold range divided by the target threshold, and the business data verification fails.

[0082] Optionally, after determining the verification results, you can record relevant log information for all target verification rules and their execution steps, and archive this log information for subsequent query and analysis needs, thereby improving the traceability of the data verification process. When a risk event (i.e., a data anomaly event) occurs, users can review these logs and data to trace the triggering cause, processing process, and results of the warning, thereby better understanding the ins and outs of the risk event and providing strong support for future risk management and decision-making.

[0083] It should be noted that the above method ensures that business data is considered normal only when all preset verification rules are met, otherwise the business data is determined to be abnormal, thereby improving the accuracy of the determined verification results.

[0084] In an optional embodiment, after obtaining the verification result, the target processing system may generate warning information based on the verification result if the verification result indicates that the business data is abnormal, and send the warning information to the target object based on at least one information push channel.

[0085] Optionally, if the verification result indicates that there is no abnormality in the business data, no warning information is generated based on the verification result.

[0086] Optionally, if the verification result indicates that the business data is abnormal, a warning message is generated based on the verification result, and the warning message is sent to the target object based on at least one information push channel.

[0087] Optionally, the warning information includes at least the verification result and may also include the business data that caused the data verification to fail and the corresponding target verification rules. For example, the target processing system may enter the verification result, the business data that caused the data verification to fail, and the corresponding target verification rules into a preset warning prompt template to generate the warning information.

[0088] Optionally, the at least one information push channel includes at least one of the following: email, text message, and phone call.

[0089] Optionally, the target object is a staff member for processing abnormal data, for example, the target object may be an administrator, etc.

[0090] It should be noted that through the above method, users can be notified in a timely manner when business data is abnormal, thereby improving the response capability of data risk warning, reducing operational terminals caused by data anomalies, and improving business stability.

[0091] In an optional embodiment, the system architecture of the target processing system can be as follows Figure 3 As shown, Figure 3 FIG. 1 is a schematic diagram of an optional target processing system according to an embodiment of the present invention. Figure 3As shown, the target processing system includes an application layer, a business layer, and a data storage layer. The target processing system can obtain target business messages, initial data verification rules, historical business data and other data content through the application layer. The target processing system can obtain initial data verification rules and historical business data through the early warning data construction interface, and determine data verification rules, cache preprocessing, etc. based on this. The target processing system can obtain target business messages through the early warning data verification interface, and match data verification rules and perform data verification based on this. The generated data verification rules, verification results and other information can be stored in the database of the data storage layer for subsequent tracing. Optionally, the target processing system can also perform tasks such as cache management, context management, email / SMS management, application monitoring, log visualization, impact analysis management, and scheduled task management during the application process.

[0092] In an optional embodiment, the data verification rules include target thresholds, business condition fields, business comparison fields, and comparison operators. The target thresholds in the data verification rules can be determined based on manual operations or historical business data, and the historical business data can be matched based on information such as organization information, business condition fields, and business comparison fields. The data verification rules can be recorded in a rule table. In addition to the data verification rules, the rule table can also include rule names, rule descriptions, rule status (such as enabled, not enabled), aviation agencies associated with the rules, associated data source channels, data types, etc. A data verification rule can correspond to an early warning information display configuration. The early warning information display configuration includes but is not limited to the aviation agency's organization information, early warning information templates, and applicable scenarios. The early warning information template can be filled with relevant information about business data that failed the verification, such as the aviation agency's organization information, the business data that caused the verification to fail, information attributes, and data verification rules that triggered the early warning.

[0093] In an optional embodiment, according to Figure 4 An optional application process of this embodiment is described. Figure 4 is a flow chart of an optional data processing method according to an embodiment of the present invention. Figure 4 As shown, the target processing system first obtains the target business message, and then determines whether the business data in the target processing message has been processed (that is, whether it has been verified). If not, it matches at least one target verification rule from multiple data verification rules based on the business data, and then performs data verification on the business data based on the target verification rule, thereby determining whether an early warning is required based on the verification result. If an early warning is required, an early warning sub-information is generated based on the early warning reminder template. At this time, it is again determined whether the business data in the target processing message has been processed. If not, the business data is further verified. If so, the early warning information is determined based on all the generated early warning sub-information, and then the early warning information is sent to the target object and recorded in the log.

[0094] It can be seen from this that the solution provided by this application achieves the purpose of detecting whether the business data to be published has anomalies based on the data verification rules that match the business data to be published, thereby achieving the technical effect of improving the detection accuracy, and further solving the technical problem of relying on manual detection of whether the business data to be published has anomalies, resulting in low detection accuracy in related technologies.

[0095] Example 2

[0096] According to an embodiment of the present invention, an embodiment of a data processing device is provided, wherein: Figure 5 is a schematic diagram of an optional data processing device according to an embodiment of the present invention, such as Figure 5 As shown, the device includes:

[0097] A first acquisition module 501 is configured to acquire a target business message, wherein the target business message includes aviation business data to be released by an aviation agency;

[0098] A determination module 502 is configured to determine, based on the service data in the target service message, at least one target verification rule that matches the service data from a plurality of data verification rules;

[0099] The verification module 503 is used to perform data verification on the business data based on at least one target verification rule to obtain a verification result, wherein the verification result is used to indicate whether there is any abnormality in the business data.

[0100] It should be noted that the above-mentioned first acquisition module 501, determination module 502 and verification module 503 correspond to steps S101 to S103 in the above-mentioned embodiment. The examples and application scenarios implemented by the three modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above-mentioned embodiment 1.

[0101] Optionally, the determination module also includes: an extraction submodule, used to extract target information from the business data, wherein the target information includes at least one of the following: organizational information of the aviation agency, and data source channels associated with the business data; an acquisition submodule, used to obtain the association relationship between multiple data verification rules and organizational information of multiple aviation agencies and multiple data source channels; a first determination submodule, used to determine at least one target verification rule that matches the business data from multiple data verification rules based on the association relationship and target information.

[0102] Optionally, the first determination submodule also includes: a first determination unit, used to determine a data verification rule that matches the target information from multiple data verification rules based on the association relationship, and obtain at least one candidate verification rule; a second determination unit, used to extract multiple business fields from the business data, and for each candidate verification rule, if all business condition fields in the candidate verification rule belong to multiple business fields, determine the candidate verification rule as the target verification rule.

[0103] Optionally, the data processing device also includes: a second acquisition module, used to obtain multiple initial data verification rules, wherein the target threshold in the initial data verification rule is a null value; a first update module, used to update the target threshold in the initial data verification rule based on the verification threshold when receiving the verification threshold input by the target object for each initial data verification rule, so as to obtain the data verification rule; a second update module, used to update the target threshold in the initial data verification rule based on the published historical business data when not receiving the verification threshold, so as to obtain the data verification rule.

[0104] Optionally, the second update module also includes: a second determination sub-module, used to determine the target historical business data that matches the initial data verification rule from the published historical business data; a third determination sub-module, used to determine the maximum value or minimum value corresponding to the threshold type from the target historical business data based on the threshold type in the initial data verification rule; an update sub-module, used to update the target threshold in the initial data verification rule based on the maximum value or minimum value corresponding to the threshold type to obtain the data verification rule.

[0105] Optionally, the verification module also includes: a fourth determination submodule, which is used to determine that the verification result indicates that there is no abnormality in the business data when all target verification rules pass the data verification of the business data; and a fifth determination submodule, which is used to determine that the verification result indicates that there is an abnormality in the business data when there is a target verification rule that fails the data verification of the business data.

[0106] Optionally, the data processing device further includes: a processing module configured to generate warning information based on the verification result when the verification result indicates that the business data is abnormal, and send the warning information to the target object based on at least one information push channel.

[0107] Example 3

[0108] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is further provided, in which a computer program is stored. The computer program is configured to execute the above-mentioned data processing method when running.

[0109] Example 4

[0110] According to another aspect of an embodiment of the present invention, an electronic device is provided, wherein: Figure 6 is a schematic diagram of an optional electronic device according to an embodiment of the present invention, such as Figure 6 As shown, the electronic device includes one or more processors; a memory for storing one or more programs, which, when the one or more programs are executed by the one or more processors, enables the one or more processors to run the programs, wherein the programs are configured to execute the above-mentioned data processing method when running.

[0111] Example 5

[0112] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program / instruction, which implements the above-mentioned data processing method when the computer program / instruction is executed by a processor.

[0113] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0114] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0115] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of units can be a logical function division. In actual implementation, there may be other division methods, such as 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0116] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected to achieve the purpose of the present embodiment according to actual needs.

[0117] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0118] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0119] The above are only preferred embodiments of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A data processing method, characterized in that: The method comprises: Acquiring a target business message, wherein the target business message includes aviation business data to be released by an aviation agency; Determining, based on the service data in the target service message, at least one target verification rule that matches the service data from a plurality of data verification rules; The business data is verified based on the at least one target verification rule to obtain a verification result, wherein the verification result is used to indicate whether there is an anomaly in the business data.

2. The method according to claim 1, characterized in that Determining, based on the service data in the target service message, at least one target verification rule that matches the service data from a plurality of data verification rules, including: Extracting target information from the business data, wherein the target information includes at least one of the following: information about an aviation organization, and a data source channel associated with the business data; Obtain the relationship between multiple data validation rules and the organizational information of multiple aviation agencies and multiple data source channels; Based on the association relationship and the target information, at least one target verification rule that matches the business data is determined from a plurality of data verification rules.

3. The method according to claim 2, characterized in that Determining at least one target verification rule that matches the business data from a plurality of data verification rules based on the association relationship and the target information includes: Based on the association relationship, determining a data verification rule that matches the target information from the multiple data verification rules to obtain at least one candidate verification rule; A plurality of business fields are extracted from the business data, and for each candidate verification rule, if all business condition fields in the candidate verification rule belong to the plurality of business fields, the candidate verification rule is determined as the target verification rule.

4. The method according to claim 1, wherein Before determining, based on the service data in the target service message, at least one target verification rule that matches the service data from a plurality of data verification rules, the method further includes: Acquire multiple initial data verification rules, wherein the target threshold in the initial data verification rules is a null value; For each initial data verification rule, upon receiving a verification threshold input by a target object, updating a target threshold in the initial data verification rule based on the verification threshold to obtain a data verification rule; In the case where the verification threshold is not received, the target threshold in the initial data verification rule is updated based on the published historical business data to obtain the data verification rule.

5. The method according to claim 4, characterized in that The target threshold in the initial data verification rule is updated based on the published historical business data to obtain the data verification rule, including: Determining target historical business data that matches the initial data verification rule from the published historical business data; Based on the threshold type in the initial data verification rule, determining the maximum value or minimum value corresponding to the threshold type from the target historical business data; The target threshold in the initial data verification rule is updated based on the maximum value or minimum value corresponding to the threshold type to obtain a data verification rule.

6. The method according to claim 1, wherein Performing data verification on the business data based on the at least one target verification rule to obtain a verification result includes: If all target verification rules pass data verification of the business data, determining that the verification result indicates that there is no abnormality in the business data; In the case that the target verification rule fails the data verification of the business data, it is determined that the verification result indicates that an abnormality exists in the business data.

7. The method according to claim 1, characterized in that After obtaining the verification result, the method further includes: When the verification result indicates that the business data is abnormal, a warning message is generated based on the verification result, and the warning message is sent to a target object based on at least one information push channel.

8. A data processing device, characterized in that: The device comprises: A first acquisition module is configured to acquire a target business message, wherein the target business message includes aviation business data to be released by an aviation agency; a determination module, configured to determine, based on the business data in the target business message, at least one target verification rule that matches the business data from a plurality of data verification rules; The verification module is used to perform data verification on the business data based on the at least one target verification rule to obtain a verification result, wherein the verification result is used to indicate whether there is any abnormality in the business data.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein the computer program is configured to execute the data processing method according to any one of claims 1 to 7 when run.

10. An electronic device, characterized in that: The electronic device includes one or more processors; A memory for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to run the programs, wherein the programs are configured to execute the data processing method described in any one of claims 1 to 7 when run.

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