Business data monitoring method and device, computer equipment and storage medium

Abstract

The invention belongs to the technical field of data processing, and relates to a service data monitoring method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining a service verification rule corresponding to the to-be-submitted data of a target submitted service; performing statement generation processing on the business verification rule based on the called verification rule engine to obtain an executable statement; constructing a scheduling task corresponding to the to-be-submitted data based on the executable statement; executing the scheduling task to query error data existing in the to-be-submitted data; and writing the error data into the verification result table to obtain a target verification result table, and displaying the target verification result table. In addition, error data may be stored in the blockchain. The submitted data verification method and device can be applied to service scenes of submitted data verification in the financial insurance field, can automatically and accurately monitor and verify the to-be-submitted data of the target submitted service in real time, further can effectively identify wrong data in the to-be-submitted data, and are beneficial to ensuring that the quality of the to-be-submitted data meets supervision requirements.

Description

Technical Field

[0001] The present application relates to the field of data processing technology and can be applied to the field of financial technology, and in particular to methods, devices, computer equipment and storage media for monitoring business data. Background Art

[0002] In the current financial regulatory landscape, regulatory reporting platforms play a crucial role. These platforms integrate multiple reporting systems, each responsible for specific reporting tasks and following its own batch reporting process. These processes require processing massive amounts of detailed data to ensure the timely and accurate delivery of regulatory information. However, in practice, a significant problem has emerged: the lack of a comprehensive data verification process for the data required for reporting.

[0003] Specifically, existing reporting systems often focus on process automation and efficiency during data collection, organization, and transmission, while neglecting data quality control. Due to a lack of data verification, the system is unable to effectively identify errors, omissions, or inconsistencies in reported data, resulting in inconsistent data quality. This uncertainty in data quality directly impacts the accuracy, completeness, and consistency of regulatory reporting, making it difficult for regulators to make effective regulatory decisions and conduct risk assessments based on this data.

[0004] For example, in the context of credit regulatory reporting in the financial sector, banks and other financial institutions are required to regularly submit detailed loan data to regulators, including key elements such as borrower information, loan amount, term, and interest rate. If the reported data contains errors in borrower identity information, discrepancies between loan amounts and contracts, or errors in interest rate calculations, and these issues are not effectively identified and corrected before submission, regulators will receive low-quality data reports. This could not only lead regulators to misjudge the credit risks of financial institutions, but could also trigger a series of misapplications or abuses of regulatory measures, posing a potential threat to the sound operation of financial institutions and the stability of financial markets.

[0005] Therefore, there is an urgent need to develop a data verification mechanism that can be integrated into the existing regulatory reporting platform to monitor and verify the data to be reported by each reporting system in real time to ensure that the quality of the reported data meets regulatory requirements. Summary of the Invention

[0006] The purpose of the embodiments of the present application is to propose a business data monitoring method, device, computer equipment and storage medium to solve the technical problem that the existing reporting system cannot effectively identify errors in the reported data, resulting in the inability to ensure data quality.

[0007] In a first aspect, a method for monitoring business data is provided, comprising:

[0008] Obtain the business verification rules corresponding to the data to be reported for the target reporting business;

[0009] Call the preset validation rule engine;

[0010] Perform statement generation processing on the business verification rule based on the verification rule engine to obtain corresponding executable statements;

[0011] Constructing a scheduling task corresponding to the data to be reported based on the executable statement;

[0012] Executing the scheduling task to query erroneous data in the data to be reported;

[0013] Writing the error data into a preset verification result table to obtain a corresponding target verification result table;

[0014] The target verification result table is displayed.

[0015] In a second aspect, a device for monitoring business data is provided, comprising:

[0016] The first acquisition module is used to obtain the business verification rules corresponding to the to-be-reported data of the target reporting business;

[0017] The first calling module is used to call the preset verification rule engine;

[0018] A generation module, configured to perform statement generation processing on the business verification rule based on the verification rule engine to obtain a corresponding executable statement;

[0019] A construction module, configured to construct a scheduling task corresponding to the data to be reported based on the executable statement;

[0020] A query module, configured to execute the scheduling task to query for erroneous data in the data to be reported;

[0021] A writing module, used for writing the error data into a preset verification result table to obtain a corresponding target verification result table;

[0022] A display module is used to display the target verification result table.

[0023] In a third aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for monitoring business data when executing the computer program.

[0024] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned method for monitoring business data are implemented.

[0025] In the scheme implemented by the above-mentioned business data monitoring method, device, computer equipment and storage medium, the business verification rules corresponding to the data to be reported of the target reporting business are first obtained; then the preset verification rule engine is called; and based on the verification rule engine, statement generation processing is performed on the business verification rules to obtain corresponding executable statements; then, a scheduling task corresponding to the data to be reported is constructed based on the executable statement; the scheduling task is subsequently executed to query the erroneous data existing in the data to be reported; the erroneous data is further written into a preset verification result table to obtain the corresponding target verification result table; finally, the target verification result table is displayed. This application obtains the business verification rules corresponding to the data to be reported of the target reporting business; then, based on the use of the verification rule engine, the business verification rules are processed by statement generation to obtain the corresponding executable statement; then, based on the executable statement, a scheduling task corresponding to the data to be reported is constructed; and the scheduling task is executed to query the erroneous data in the data to be reported; and then the erroneous data is written into the preset verification result table to obtain the target verification result table, and finally the target verification result table is displayed so that business personnel and management personnel can analyze and correct the target verification result table, thereby ensuring that the quality of the data to be reported meets regulatory requirements. Through the above-mentioned data monitoring process, this application, based on the combined use of business verification rules, verification rule engines, executable statements, scheduling tasks and verification result tables, can automatically and accurately monitor and verify the data to be reported of the target reporting business in real time, and can effectively identify erroneous data in the data to be reported, which is conducive to ensuring that the quality of the data to be reported meets regulatory requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the solutions in this application, a brief introduction will be given below to the drawings required for use in the description of the embodiments of this application. Obviously, the drawings described below are some embodiments of this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0027] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0028] Figure 2 is a flowchart of an embodiment of a method for monitoring business data according to the present application;

[0029] Figure 3is a structural diagram of an embodiment of a device for monitoring business data according to the present application;

[0030] Figure 4 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0031] Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art to which this application belongs. The terms used in the specification of the application are for the purpose of describing specific embodiments only and are not intended to limit this application. The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of this application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0032] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0033] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0034] like Figure 1 As shown, system architecture 100 may include a terminal device 101, a network 102, and a server 103. Terminal device 101 may be a laptop computer 1011, a tablet computer 1012, or a mobile phone 1013. Network 102 is a medium for providing a communication link between terminal device 101 and server 103. Network 102 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0035] The user can use the terminal device 101 to interact with the server 103 via the network 102 to receive or send messages, etc. Various communication client applications can be installed on the terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0036] The terminal device 101 can be various electronic devices with a display screen and supporting web browsing. In addition to the laptop computer 1011, tablet computer 1012 or mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop computer and a desktop computer, etc.

[0037] The server 103 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal device 101 .

[0038] It should be noted that the business data monitoring method provided in the embodiment of the present application is generally executed by a server / terminal device, and accordingly, the business data monitoring device is generally set in the server / terminal device.

[0039] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0040] Continue to refer Figure 2 , shows a flowchart of an embodiment of the method for monitoring business data according to the present application. According to different needs, the order of the steps in the flowchart can be changed, and some steps can be omitted. The method for monitoring business data provided in the embodiment of the present application can be applied to any scenario that requires verification of reported data, and the method for monitoring business data can be applied to products in these scenarios, for example, verification of reported data in the financial and insurance fields. The method for monitoring business data comprises the following steps:

[0041] Step S201: Acquire the business verification rules corresponding to the data to be reported of the target reporting business.

[0042] In this embodiment, the method for monitoring service data is executed on the electronic device (eg Figure 1The server / terminal device shown in the figure) can obtain the business verification rules corresponding to the data to be reported of the target reporting business through a wired connection or a wireless connection. It should be pointed out that the above-mentioned wireless connection method may include but is not limited to 3G / 4G / 5G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods currently known or to be developed in the future. The executive subject of the present application may specifically be a data monitoring system, or a verification system for reporting data, which may be referred to as a system for short. The present application can be applied to the processing scenario of reporting data monitoring of reporting business in the financial insurance field. Exemplarily, the present application can be applied to the data monitoring scenario where the unified supervision and reporting platform for life insurance needs to report policy information and claim information waiting to be reported. The above-mentioned target reporting business may refer to the business corresponding to the unified supervision and reporting platform for life insurance that needs to report policy information, claim information and other data. Based on actual business processing needs, business analysts can sort out verification types such as the policyholder's age must be between 18 and 65 years old (numeric range verification) and the claim amount cannot exceed the insured amount (data accuracy verification) in the policy information, and define corresponding secondary classifications and SQL templates to construct corresponding business verification rules. Among them, based on the use of the verification rule engine, a configuration template for business verification rules can be provided. Business personnel can configure the configuration template for business verification rules according to actual needs to build corresponding business verification rules. At the same time, they maintain communication with the rule engine developers regarding the rule classifications missing in the rule engine.

[0043] Step S202: calling a preset verification rule engine.

[0044] In this embodiment, the construction process of the above-mentioned verification rule engine will be further described in detail in subsequent specific embodiments of this application and will not be elaborated on here.

[0045] Step S203: performing statement generation processing on the business verification rule based on the verification rule engine to obtain corresponding executable statements.

[0046] In this embodiment, the above-mentioned specific implementation process of generating statements for the business verification rules based on the verification rule engine to obtain corresponding executable statements will be further described in detail in subsequent specific embodiments of this application and will not be elaborated on here.

[0047] Step S204: constructing a scheduling task corresponding to the data to be reported based on the executable statement.

[0048] In this embodiment, a scheduling task for data verification processing applicable to the above-mentioned data to be submitted can be constructed based on the above-mentioned executable statement, which includes fields such as verification group and data date. The above-mentioned verification group is used to specify the set of business verification rules to be executed, and the data date is used to determine the data range corresponding to the above-mentioned data to be submitted to be verified. In addition, the execution of the set scheduling task will be triggered according to the predetermined time plan. Different scheduling frequencies can be set according to business needs, such as daily, weekly, monthly, etc. In addition, the present application can realize the management and scheduling of business verification rules of different reporting systems in different processes through scheduling tasks. For example, in the reporting process of the insurance policy information reporting system in the financial insurance field, the scheduling task will automatically trigger the execution of relevant verification rules to ensure the quality of the reported data related to the insurance business.

[0049] The validation group, also known as the validation rule group, is a set of executable validation rule SQL statements. The default grouping is table-based (when the input parameter is tab_type). Task execution can also be scheduled by defining different groups, such as data governance groups and warehousing rule groups.

[0050] Step S205: executing the scheduling task to query the erroneous data in the data to be reported.

[0051] In this embodiment, the specific implementation process of executing the scheduling task to query the erroneous data in the data to be reported will be further described in detail in subsequent specific embodiments of the present application and will not be elaborated on here.

[0052] Step S206: writing the error data into a preset verification result table to obtain a corresponding target verification result table.

[0053] In this embodiment, the verification result table is a data table pre-built according to actual business needs for storing the execution results of all verification rules, so as to facilitate subsequent analysis and processing and provide a basis for subsequent result analysis and decision-making.

[0054] Step S207: display the target verification result table.

[0055] In this embodiment, the specific implementation process of displaying the target verification result table will be further described in detail in subsequent specific embodiments of this application and will not be elaborated on here.

[0056] To illustrate the business data monitoring process for this application in the financial insurance sector, consider a life insurance company whose unified regulatory reporting platform needs to submit policy and claim information pending submission. The specific processing flow includes: Rule Definition: Business analysts identify validation types within policy information, such as the policyholder age must be between 18 and 65 (value range validation) and the claim amount cannot exceed the insured sum (data accuracy validation), and define corresponding secondary classifications and SQL templates. Rule Engine Design: Developers develop the rule engine based on the defined rule types and templates, implementing parameter substitution and fault tolerance. Business Validation Rules: Business personnel configure policyholder age validation rules and claim amount validation rules based on regulatory requirements and business needs, and submit them to the rule engine. Rule Generation: The rule engine generates the corresponding executable SQL statements and inserts them into the validation rule table. Rule Execution: The scheduling system triggers a scheduled task to execute the policyholder age validation rules and claim amount validation rules, writing any erroneous data found in the query to the validation result table to ensure the quality of data submitted for regulatory submission. Result output: Generate a verification result report, displaying policy information and claims information that do not meet the verification rules for analysis and processing by business personnel and management personnel.

[0057] The present application first obtains the business verification rules corresponding to the data to be reported of the target reporting business; then calls the preset verification rule engine; and based on the verification rule engine, performs statement generation processing on the business verification rules to obtain the corresponding executable statement; then, based on the executable statement, constructs a scheduling task corresponding to the data to be reported; subsequently, executes the scheduling task to query the erroneous data in the data to be reported; further, writes the erroneous data into the preset verification result table to obtain the corresponding target verification result table; and finally, displays the target verification result table. The present application obtains the business verification rules corresponding to the data to be reported of the target reporting business; then, based on the use of the verification rule engine, performs statement generation processing on the business verification rules to obtain the corresponding executable statement; then, based on the executable statement, constructs a scheduling task corresponding to the data to be reported; and executes the scheduling task to query the erroneous data in the data to be reported; further, writes the erroneous data into the preset verification result table to obtain the target verification result table; and finally, displays the target verification result table so that business personnel and management personnel can analyze and correct the target verification result table, thereby ensuring that the quality of the data to be reported meets regulatory requirements. Through the above-mentioned data monitoring process, this application is based on the combined use of business verification rules, verification rule engine, executable statements, scheduling tasks and verification result tables, which can realize automatic and accurate real-time monitoring and verification of the data to be reported for the target reporting business, and thus can effectively identify erroneous data in the data to be reported, thereby ensuring that the quality of the data to be reported meets regulatory requirements.

[0058] In some optional implementations, step S203 includes the following steps:

[0059] The business verification rules are parsed based on the verification rule engine to obtain corresponding parsing results.

[0060] In this embodiment, the business verification rules are parsed by using a verification rule engine to understand the logic and requirements of the business verification rules and generate corresponding parsing results.

[0061] Call the specified engine template corresponding to the preset configuration information.

[0062] In this embodiment, the calling process of the above-mentioned designated engine template will be described in further detail in subsequent specific embodiments of this application and will not be elaborated on here.

[0063] Generate a corresponding SQL statement based on the parsing result and the specified engine template.

[0064] In this embodiment, the SQL statement is the output generated by the verification engine based on the business verification rules. It is an executable SQL statement that is executed by a data query engine and writes the error data query results to the verification result table. For example, the generated SQL statement is as follows: select system name, table name, field name, rule ID, rule description, error data primary key from table name where sql.

[0065] Among them, the specific implementation process of generating the corresponding SQL statement based on the parsing result and the specified engine template will be further described in detail in the subsequent specific embodiments of this application, and will not be elaborated on here.

[0066] The SQL statement is syntax-checked based on a preset syntax specification.

[0067] In this embodiment, the syntax specifications refer to the syntax specifications of the target database storing the data to be reported. A corresponding test result can be obtained by testing whether the generated SQL statement complies with the syntax specifications of the target database. The test result may include whether the SQL statement complies with the syntax specifications or whether the SQL statement does not comply with the syntax specifications. For example, if the target database is a MySQL database, the SQL statement is ensured to comply with the MySQL database syntax; if the target database is an Oracle database, the SQL statement is ensured to comply with the Oracle database syntax.

[0068] If the SQL statement passes the syntax check, the SQL statement is used as the executable statement.

[0069] In this embodiment, after detecting that the SQL statement passes the syntax check, the generated SQL statement is used as the required executable statement.

[0070] The present application parses the business verification rules based on the verification rule engine to obtain the corresponding parsing results; then calls the designated engine template corresponding to the preset configuration information; then generates the corresponding SQL statement based on the parsing results and the designated engine template; subsequently performs syntax verification on the SQL statement based on the preset syntax specification; if the SQL statement passes the syntax verification, the SQL statement is used as the executable statement. The present application parses the business verification rules based on the use of the verification rule engine to obtain the corresponding parsing results, then calls the designated engine template corresponding to the preset configuration information, and generates the corresponding SQL statement based on the combined use of the parsing results and the designated engine template, and when it is detected that the SQL statement passes the syntax verification based on the use of the syntax specification, the generated SQL statement is used as the required executable statement, thereby achieving efficient and accurate generation of executable statements that match the business verification rules, effectively improving the efficiency of generating executable statements, and ensuring the accuracy and standardization of the generated executable statements.

[0071] In some optional implementations of this embodiment, before the step of calling the designated engine template corresponding to the preset configuration information, the above S203 may further perform the following steps:

[0072] The configuration information corresponding to the business verification rule is obtained from a preset data source.

[0073] In this embodiment, the data source may include an external system or configuration file. Configuration information may be received from a selected data source. The configuration information may include information such as the validation rule type, database query engine type, system name (sys_name), table name (table_name), field name (col_name), rule ID (rule_id), rule description (rule_desc), error data primary key (key_id), and PARA1-PARA10. After receiving the configuration information, further verification may be performed to ensure parameter integrity and validity. For example, verification may be performed to check whether the rule type exists in the rule classification storage table and whether the database query engine type is supported.

[0074] The verification rule type and the database query engine type are obtained from the configuration information.

[0075] In this embodiment, the required verification rule type and database query engine type can be extracted by performing information extraction on the above configuration information.

[0076] Call the preset template database.

[0077] In this embodiment, the template database is a database pre-built based on actual business needs, storing mappings between validation rule types, database query engine types, and engine templates. The template database stores multiple engine templates, each of which has a one-to-one mapping between validation rule types and database query engine types.

[0078] A target engine template matching the verification rule type and the database query engine type is found from the template database.

[0079] In this embodiment, the obtained verification rule type and database query engine type may be used to perform a template query on the template database to find a target engine template that matches both the verification rule type and the database query engine type.

[0080] The target engine template is used as the designated engine template.

[0081] The present application obtains configuration information corresponding to the business verification rules from a preset data source; then obtains the verification rule type and the database query engine type from the configuration information; then calls a preset template database; and from the template database, finds a target engine template that matches the verification rule type and the database query engine type; and subsequently uses the target engine template as the designated engine template. The present application obtains configuration information corresponding to the business verification rules from a preset data source, and obtains the verification rule type and the database query engine type from the configuration information, and then based on the use of the template database, can quickly and accurately find the designated engine template that matches the verification rule type and the database query engine type, effectively improving the efficiency of obtaining the designated engine template and ensuring the accuracy of the obtained designated engine template.

[0082] In some optional implementations, generating a corresponding SQL statement based on the parsing result and the specified engine template includes the following steps:

[0083] Get the template parameters in the specified engine template.

[0084] In this embodiment, parameters of the designated engine template may be extracted to obtain template parameters included in the designated engine template, such as parameters such as ${COL_ID} and ${FI LTER_SQL}.

[0085] Based on the configuration information, corresponding parameter replacement processing is performed on the template parameters to obtain a corresponding first SQL statement.

[0086] In this embodiment, the obtained template parameters can be replaced with actual field names, filter conditions and other configuration information, and the accuracy and consistency of the parameter replacement can be ensured to avoid syntax errors or logical errors, thereby obtaining a replaced template and using the replaced template as the corresponding first SQL statement.

[0087] Get the preset optimization strategy.

[0088] In this embodiment, the optimization strategy includes optimizing SQL statements based on the characteristics of the target database (e.g., indexes and optimizer-supported functions). For example, this includes adding EXPLA IN analysis or adjusting query order to improve performance. The target database is the database storing the data to be reported.

[0089] The first SQL statement is optimized based on the optimization strategy to obtain an optimized second SQL statement.

[0090] In this embodiment, the first SQL statement may be optimized according to the policy content of the optimization policy, thereby obtaining an optimized second SQL statement.

[0091] The second SQL statement is used as the SQL statement.

[0092] The present application obtains the template parameters in the specified engine template; then performs corresponding parameter replacement processing on the template parameters based on the configuration information to obtain the corresponding first SQL statement; then obtains a preset optimization strategy; and optimizes the first SQL statement based on the optimization strategy to obtain an optimized second SQL statement; and subsequently uses the second SQL statement as the SQL statement. The present application obtains the template parameters in the specified engine template, and performs corresponding parameter replacement processing on the template parameters based on the use of configuration information to obtain the first SQL statement, and then intelligently optimizes the first SQL statement based on the use of the optimization strategy, thereby automatically and intelligently generating the required SQL statement, improving the intelligence and standardization of SQL statement generation.

[0093] In some optional implementations, step S205 includes the following steps:

[0094] Obtain the scheduling time corresponding to the scheduling task.

[0095] In this embodiment, the system pre-configures relevant information about scheduled tasks, including task name, execution time, and execution frequency, based on actual business needs. Furthermore, the scheduling system triggers scheduled tasks corresponding to business validation rules according to a predetermined schedule, with different scheduling frequencies set, such as daily, weekly, and monthly. When the scheduled time arrives, the scheduling system automatically triggers the scheduled task and performs the corresponding data processing based on the business validation rules.

[0096] Determine whether the current time reaches the scheduled time.

[0097] In this embodiment, the current time may be obtained by using a time function, and then compared with the obtained scheduling time corresponding to the above-mentioned scheduling task to determine whether the current time reaches the scheduling time.

[0098] If so, execute the scheduling task to verify the data to be reported and obtain the corresponding execution result.

[0099] In this embodiment, when executing the above-mentioned scheduling task, the generated executable statement corresponding to the above-mentioned business verification rule will be called, executed in a certain data query engine and the corresponding execution result, that is, the query result, will be written into the verification result table.

[0100] The execution results are analyzed to filter out abnormal data that does not comply with the business verification rules from the execution results.

[0101] In this embodiment, after executing the above executable statement, the generated specified result will be analyzed to generate the output result of the above business verification rule. The above execution result may include data that meets the business verification rules and abnormal data that does not meet the business verification rules.

[0102] The abnormal data is regarded as the error data.

[0103] The present application obtains the scheduling time corresponding to the scheduling task; then determines whether the current time reaches the scheduling time; if so, executes the scheduling task to verify the data to be reported and obtains the corresponding execution result; then analyzes the execution result to filter out abnormal data that does not comply with the business verification rules from the execution result; and subsequently uses the abnormal data as the error data. The present application obtains the scheduling time corresponding to the scheduling task, and when it detects that the current time reaches the scheduling time, it automatically executes the scheduling task to verify the data to be reported and obtains the corresponding execution result, and then analyzes the execution result to filter out abnormal data that does not comply with the business verification rules from the execution result and uses it as the required error data, thereby automatically and accurately querying the error data in the data to be reported in the manner of scheduling tasks, thereby improving the efficiency of obtaining error data and ensuring the accuracy of the error data obtained.

[0104] In some optional implementations of this embodiment, step S207 includes the following steps:

[0105] Perform information statistical processing on the target verification result table to obtain corresponding statistical information.

[0106] In this embodiment, the above-mentioned information statistical processing includes processing such as counting the number of error data, identifying the distribution of error types, and identifying the distribution of time trends. Specifically, counting the number of error data includes counting the number of error data for each business verification rule to understand which rules have a higher error rate. Identifying the distribution of error types includes classifying the error data and counting the distribution of different types of errors (such as format errors, range errors, and association errors). Identifying the distribution of time trends includes analyzing the changing trend of the number of error data over time and identifying the peak error periods.

[0107] A corresponding statistical report is constructed based on the statistical information.

[0108] In this embodiment, the above statistical information can be filled into the corresponding position in the custom report to generate the corresponding statistical report. Among them, the custom report can be generated according to actual business needs, such as filtering and summarizing by time range, data source, error type and other dimensions.

[0109] Get the preset visualization display strategy.

[0110] In this embodiment, the above-mentioned visualization display strategy can be set according to actual display needs, for example, a chart display or dashboard display strategy can be adopted. Specifically, chart display includes: using charts (such as bar charts, line charts, pie charts, etc.) to intuitively display statistical information, which facilitates quick understanding by business personnel and management personnel. Dashboard display includes: building a dashboard, integrating multiple reports and charts, and providing a one-stop monitoring and analysis interface.

[0111] Based on the visual display strategy, the target verification result table and the statistical report are displayed.

[0112] In this embodiment, the target verification result table and the statistical report may be visualized according to the policy content corresponding to the selected visualization display policy.

[0113] This application obtains corresponding statistical information by performing information statistical processing on the target verification result table; then constructs corresponding statistical reports based on the statistical information; then obtains a preset visual display strategy; and subsequently displays the target verification result table and the statistical reports based on the visual display strategy. This application obtains corresponding statistical information by performing information statistical processing on the target verification result table, and constructs corresponding statistical reports based on the statistical information, thereby improving the efficiency of generating statistical reports. In addition, the target verification result table and statistical reports will be displayed and processed intelligently based on the use of visual display strategies, thereby providing business personnel and management personnel with rich and valuable data support, which is conducive to improving the work efficiency and work experience of relevant personnel.

[0114] In some optional implementations of this embodiment, before step S202, the electronic device may further perform the following steps:

[0115] Call the preset rule engine.

[0116] In this embodiment, the rule engine may be a general rule engine.

[0117] Get the preset fault-tolerant handling strategy.

[0118] In this embodiment, the fault-tolerant processing strategy includes error detection, logging, and exception handling. Specifically, error detection includes real-time detection of missing parameters, type mismatches, syntax errors, and other errors during parameter substitution and SQL statement generation. Logging includes detailed logging of detected errors, including error type, location, and possible cause. Exception handling ensures that even in the event of an exception, the program continues to process other validation rules, ensuring system stability and reliability.

[0119] The rule engine is optimized and adjusted based on the fault-tolerant processing strategy to obtain an optimized rule engine.

[0120] In this embodiment, the rule engine can be optimized and adjusted according to the fault-tolerant processing strategy to construct a verification rule engine with fault-tolerant processing capabilities.

[0121] The optimized rule engine is used as the verification rule engine.

[0122] This application calls a preset rule engine, then obtains a preset fault-tolerant processing strategy, then optimizes and adjusts the rule engine based on the fault-tolerant processing strategy to obtain an optimized rule engine, and subsequently uses the optimized rule engine as the verification rule engine. This application calls a preset rule engine, then optimizes and adjusts the rule engine based on the obtained fault-tolerant processing strategy, thereby intelligently and efficiently completing the construction of a verification rule engine with fault-tolerant processing capabilities, improving the development intelligence of the verification rule engine and ensuring the processing intelligence and stability of data verification using the verification rule engine.

[0123] In some optional implementations, the user information obtained is obtained with the user's consent and complies with relevant laws and policies.

[0124] In addition, any software tools or components not provided by our company that appear in the embodiments of this application are merely examples and do not represent actual use.

[0125] In addition, this application also solves the problem that there is no unified management channel for local effectiveness of regulatory data verification rules, and they are scattered across various systems and difficult to manage; it also solves the problem that each new rule must be compiled and released separately, and the code cannot be reused. Ultimately, the verification rules of different reporting systems are managed and scheduled in different processes, and this is a unified, reusable, and extensible verification rule program that meets complex regulatory reporting scenarios and increasingly stringent regulatory data quality requirements. It has greatly improved the quality of data reporting for regulatory reporting, and at the same time can reduce labor input costs, reduce costs, and increase efficiency.

[0126] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0127] It should be emphasized that in order to further ensure the privacy and security of the above-mentioned erroneous data, the above-mentioned erroneous data can also be stored in a node of a blockchain.

[0128] The blockchain referred to in this application refers to a new application model for computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Blockchain is essentially a decentralized database, a series of data blocks generated using cryptographic methods. Each data block contains information about a batch of network transactions, which is used to verify the validity of the information (to prevent counterfeiting) and generate the next block. Blockchain can include the blockchain underlying platform, the platform product service layer, and the application service layer.

[0129] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0130] Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0131] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware via computer-readable instructions. The computer-readable instructions can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes in the above-described method embodiments. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0132] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0133] Further references Figure 3 , as a response to the above Figure 2 In order to realize the method shown in the figure, the present application provides an embodiment of a monitoring device for business data. Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0134] like Figure 3 As shown, the business data monitoring device 300 of this embodiment includes: a first acquisition module 301, a first calling module 302, a generation module 303, a construction module 304, a query module 305, a writing module 306 and a display module 307.

[0135] The first acquisition module 301 is used to obtain the business verification rules corresponding to the to-be-reported data of the target reporting business;

[0136] A first calling module 302 is used to call a preset verification rule engine;

[0137] A generation module 303 is configured to perform statement generation processing on the business verification rule based on the verification rule engine to obtain a corresponding executable statement;

[0138] A construction module 304 is configured to construct a scheduling task corresponding to the data to be reported based on the executable statement;

[0139] A query module 305 is used to execute the scheduling task to query the erroneous data in the data to be reported;

[0140] The writing module 306 is used to write the error data into a preset verification result table to obtain a corresponding target verification result table;

[0141] The display module 307 is used to display the target verification result table.

[0142] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the method for monitoring business data in the aforementioned embodiment, and are not described in detail here.

[0143] In some optional implementations of this embodiment, the generating module 303 includes:

[0144] A parsing submodule, configured to parse the business verification rules based on the verification rule engine to obtain corresponding parsing results;

[0145] A first calling submodule is used to call a specified engine template corresponding to preset configuration information;

[0146] A generation submodule, configured to generate a corresponding SQL statement based on the parsing result and the specified engine template;

[0147] A check submodule, configured to perform syntax check on the SQL statement based on a preset syntax specification;

[0148] The first determining submodule is configured to use the SQL statement as the executable statement if the SQL statement passes the syntax check.

[0149] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the method for monitoring business data in the aforementioned embodiment, and are not described in detail here.

[0150] In some optional implementations of this embodiment, the generation module 303 includes:

[0151] A first acquisition submodule is used to obtain configuration information corresponding to the business verification rule from a preset data source;

[0152] A second acquisition submodule is used to obtain the verification rule type and the database query engine type from the configuration information;

[0153] The second calling submodule is used to call a preset template database;

[0154] A search submodule, configured to search the template database for a target engine template that matches the verification rule type and the database query engine type;

[0155] The second determining submodule is configured to use the target engine template as the designated engine template.

[0156] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the method for monitoring business data in the aforementioned embodiment, and are not described in detail here.

[0157] In some optional implementations of this embodiment, the generating submodule includes:

[0158] A first acquiring unit, configured to acquire template parameters in the specified engine template;

[0159] a replacing unit, configured to perform corresponding parameter replacement processing on the template parameters based on the configuration information to obtain a corresponding first SQL statement;

[0160] A second acquiring unit is used to acquire a preset optimization strategy;

[0161] an optimization unit, configured to optimize the first SQL statement based on the optimization strategy to obtain an optimized second SQL statement;

[0162] The determining unit is configured to use the second SQL statement as the SQL statement.

[0163] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the method for monitoring business data in the aforementioned embodiment, and are not described in detail here.

[0164] In some optional implementations of this embodiment, the query module 305 includes:

[0165] A third acquisition submodule is used to obtain the scheduling time corresponding to the scheduling task;

[0166] A judgment submodule is used to judge whether the current time reaches the scheduled time;

[0167] An execution submodule, configured to execute the scheduling task if yes, to verify the data to be reported and obtain a corresponding execution result;

[0168] A screening submodule, configured to analyze the execution results to screen out abnormal data that does not conform to the business verification rules from the execution results;

[0169] The third determining submodule is configured to use the abnormal data as the error data.

[0170] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the method for monitoring business data in the aforementioned embodiment, and are not described in detail here.

[0171] In some optional implementations of this embodiment, the display module 307 includes:

[0172] A statistics submodule is used to perform information statistics processing on the target verification result table to obtain corresponding statistical information;

[0173] A construction submodule, configured to construct corresponding statistical reports based on the statistical information;

[0174] The fourth acquisition submodule is used to obtain a preset visualization display strategy;

[0175] The display submodule is used to display the target verification result table and the statistical report based on the visual display strategy.

[0176] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the method for monitoring business data in the aforementioned embodiment, and are not described in detail here.

[0177] In some optional implementations of this embodiment, the service data monitoring device further includes:

[0178] The second calling module is used to call the preset rule engine;

[0179] The second acquisition module is used to obtain a preset fault-tolerant processing strategy;

[0180] An optimization module, configured to optimize and adjust the rule engine based on the fault-tolerant processing strategy to obtain an optimized rule engine;

[0181] A determination module is used to use the optimized rule engine as the verification rule engine.

[0182] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the method for monitoring business data in the aforementioned embodiment, and are not described in detail here.

[0183] To solve the above technical problems, the present application also provides a computer device. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0184] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 4 with components 41-43, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0185] The computer device may be a desktop computer, notebook computer, PDA, cloud server, etc. The computer device may interact with the user via a keyboard, mouse, remote control, touchpad, or voice control device.

[0186] The memory 41 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk equipped on the computer device 4, a smart media card (SMC), a secure digital (SD) card, a flash memory card, etc. Of course, the memory 41 may also include both the internal storage unit of the computer device 4 and its external storage device. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions of the business data monitoring method. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or are to be output.

[0187] In some embodiments, the processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to execute computer-readable instructions or process data stored in the memory 41, such as computer-readable instructions for executing the method for monitoring business data.

[0188] The network interface 43 may include a wireless network interface or a wired network interface. The network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0189] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0190] In an embodiment of the present application, the present application first obtains the business verification rules corresponding to the data to be reported of the target reporting business; then calls a preset verification rule engine; and based on the verification rule engine, performs statement generation processing on the business verification rules to obtain corresponding executable statements; then constructs a scheduling task corresponding to the data to be reported based on the executable statement; subsequently executes the scheduling task to query out the erroneous data in the data to be reported; further writes the erroneous data into a preset verification result table to obtain the corresponding target verification result table; finally, displays the target verification result table. This application obtains the business verification rules corresponding to the data to be reported of the target reporting business; then, based on the use of the verification rule engine, the business verification rules are processed by statement generation to obtain the corresponding executable statement; then, based on the executable statement, a scheduling task corresponding to the data to be reported is constructed; and the scheduling task is executed to query the erroneous data in the data to be reported; and then the erroneous data is written into the preset verification result table to obtain the target verification result table, and finally the target verification result table is displayed so that business personnel and management personnel can analyze and correct the target verification result table, thereby ensuring that the quality of the data to be reported meets regulatory requirements. Through the above-mentioned data monitoring process, this application, based on the combined use of business verification rules, verification rule engines, executable statements, scheduling tasks and verification result tables, can automatically and accurately monitor and verify the data to be reported of the target reporting business in real time, and can effectively identify erroneous data in the data to be reported, which is conducive to ensuring that the quality of the data to be reported meets regulatory requirements.

[0191] The present application also provides another embodiment, namely, providing a computer-readable storage medium, which stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the business data monitoring method as described above.

[0192] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0193] In an embodiment of the present application, the present application first obtains the business verification rules corresponding to the data to be reported of the target reporting business; then calls a preset verification rule engine; and based on the verification rule engine, performs statement generation processing on the business verification rules to obtain corresponding executable statements; then constructs a scheduling task corresponding to the data to be reported based on the executable statement; subsequently executes the scheduling task to query out the erroneous data in the data to be reported; further writes the erroneous data into a preset verification result table to obtain the corresponding target verification result table; finally, displays the target verification result table. This application obtains the business verification rules corresponding to the data to be reported of the target reporting business; then, based on the use of the verification rule engine, the business verification rules are processed by statement generation to obtain the corresponding executable statement; then, based on the executable statement, a scheduling task corresponding to the data to be reported is constructed; and the scheduling task is executed to query the erroneous data in the data to be reported; and then the erroneous data is written into the preset verification result table to obtain the target verification result table, and finally the target verification result table is displayed so that business personnel and management personnel can analyze and correct the target verification result table, thereby ensuring that the quality of the data to be reported meets regulatory requirements. Through the above-mentioned data monitoring process, this application, based on the combined use of business verification rules, verification rule engines, executable statements, scheduling tasks and verification result tables, can automatically and accurately monitor and verify the data to be reported of the target reporting business in real time, and can effectively identify erroneous data in the data to be reported, which is conducive to ensuring that the quality of the data to be reported meets regulatory requirements.

[0194] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0195] Obviously, the embodiments described above are only some of the embodiments of the present application, rather than all of the embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application has been described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions described in the aforementioned specific embodiments, or to make equivalent replacements for some of the technical features therein. Any equivalent structure made using the contents of the present application specification and the accompanying drawings, directly or indirectly used in other related technical fields, is also within the scope of patent protection of the present application.

Claims

1. A method for monitoring business data, characterized in that: The steps include: Obtain the business verification rules corresponding to the data to be reported for the target reporting business; Call the preset validation rule engine; Perform statement generation processing on the business verification rule based on the verification rule engine to obtain corresponding executable statements; Constructing a scheduling task corresponding to the data to be reported based on the executable statement; Executing the scheduling task to query erroneous data in the data to be reported; Writing the error data into a preset verification result table to obtain a corresponding target verification result table; The target verification result table is displayed.

2. The method for monitoring business data according to claim 1, characterized in that: The step of performing statement generation processing on the business verification rule based on the verification rule engine to obtain a corresponding executable statement specifically includes: Parsing the business verification rules based on the verification rule engine to obtain corresponding parsing results; Call the specified engine template corresponding to the preset configuration information; Generate a corresponding SQL statement based on the parsing result and the specified engine template; Performing syntax checking on the SQL statement based on a preset syntax specification; If the SQL statement passes the syntax check, the SQL statement is used as the executable statement.

3. The method for monitoring business data according to claim 2, characterized in that: Before the step of calling the designated engine template corresponding to the preset configuration information, the method further includes: Obtaining configuration information corresponding to the business verification rule from a preset data source; Obtaining a verification rule type and a database query engine type from the configuration information; Call the preset template database; Searching the template database for a target engine template that matches the verification rule type and the database query engine type; The target engine template is used as the designated engine template.

4. The method for monitoring business data according to claim 2, characterized in that: The step of generating a corresponding SQL statement based on the parsing result and the specified engine template specifically includes: Obtain template parameters in the specified engine template; Perform corresponding parameter replacement processing on the template parameters based on the configuration information to obtain a corresponding first SQL statement; Get the preset optimization strategy; Optimize the first SQL statement based on the optimization strategy to obtain an optimized second SQL statement; The second SQL statement is used as the SQL statement.

5. The method for monitoring business data according to claim 1, characterized in that: The step of executing the scheduling task to query for erroneous data in the data to be reported specifically includes: Obtaining the scheduling time corresponding to the scheduling task; Determine whether the current time reaches the scheduled time; If yes, execute the scheduling task to verify the data to be reported and obtain the corresponding execution result; Analyzing the execution results to filter out abnormal data that does not comply with the business verification rules from the execution results; The abnormal data is regarded as the error data.

6. The method for monitoring business data according to claim 1, characterized in that: The step of displaying the target verification result table specifically includes: Performing information statistical processing on the target verification result table to obtain corresponding statistical information; Constructing corresponding statistical reports based on the statistical information; Get the preset visualization display strategy; Based on the visual display strategy, the target verification result table and the statistical report are displayed.

7. The method for monitoring business data according to claim 1, characterized in that: Before the step of calling the preset verification rule engine, the method further includes: Call the preset rule engine; Get the preset fault-tolerant processing strategy; Optimizing and adjusting the rule engine based on the fault-tolerant processing strategy to obtain an optimized rule engine; The optimized rule engine is used as the verification rule engine.

8. A device for monitoring business data, characterized in that: include: The first acquisition module is used to obtain the business verification rules corresponding to the to-be-reported data of the target reporting business; The first calling module is used to call the preset verification rule engine; A generation module, configured to perform statement generation processing on the business verification rule based on the verification rule engine to obtain a corresponding executable statement; A construction module, configured to construct a scheduling task corresponding to the data to be reported based on the executable statement; A query module, configured to execute the scheduling task to query for erroneous data in the data to be reported; A writing module, used for writing the error data into a preset verification result table to obtain a corresponding target verification result table; A display module is used to display the target verification result table.

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

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the method for monitoring business data according to any one of claims 1 to 7.

Images