Telecommunication operator MBO data automatic calibration method, system, device and medium

Abstract

The invention relates to the technical field of multi-source data calibration, in particular to a telecom operator MBO data automatic calibration method, system and device and a medium. According to the method, metadata FTP server information is configured in a plurality of field systems, and multi-source data is standardized; configuring auditing data SQL fields of the corresponding systems through an SQL injection mode, and comparing and correcting data among the systems to generate an auditing exception table; according to the data in the auditing exception table, configuring an order dispatching SQL script, and generating exceptional order dispatching data; according to the method, latest abnormal data is generated according to a set calibration rule, the latest abnormal data and abnormal order sending data are checked, auditing data SQL fields and SQL order sending scripts are configured in an SQL injection mode to adapt the data, the difference between the data is shielded, and the complexity of data calibration is reduced; closed-loop management of automatic order sending is realized according to a set calibration rule; the order sending strategy adjustment in the data management process is facilitated, and the response efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-source data calibration, and in particular to a method, system, device and medium for automatic calibration of MBO data of a telecommunications operator. Background Art

[0002] The rapid development of big data technology in recent years has brought opportunities for the integration of data in the three domains of MSS, BSS and OSS for operators. Because of the information islands in the early stage, there are differences in the data in the three domains of MSS, BSS and OSS, which affects the quality of the data, reduces the value of data use, and is not conducive to the subsequent value mining of the data.

[0003] Traditional data calibration is usually done manually or with customized software according to one or more calibration rules, which consumes a lot of human resources and has a long R&D cycle. When the source data or calibration rules change, the program needs to be readjusted and iterative development needs to be carried out. The communication and iterative development costs of the entire process are high, and the agility is relatively low. The data calibration software currently provided to operators is still in the customized development stage and cannot support customers' agile needs for rapid response. Summary of the invention

[0004] In view of the problems that the existing data calibration methods consume a lot of human resources, have a long research and development cycle, and cannot support the agile needs of rapid response, the present invention proposes a telecommunications operator MBO data automatic calibration method, system, equipment and medium; the method configures the audit data SQL field and SQL dispatch script through SQL injection to adapt the data, shields the differences between data, and reduces the complexity of data calibration; realizes closed-loop management of automatic dispatch according to the set calibration rules; facilitates the adjustment of dispatch strategy in the data governance process, and improves response efficiency.

[0005] The specific implementation contents of the present invention are as follows:

[0006] A method for automatically calibrating MBO data of a telecommunications operator, comprising the following steps:

[0007] Step S1: configure metadata FTP server information in multiple domain systems and standardize MBO data;

[0008] Step S2: Based on the standardized MBO data, configure the audit data SQL field of the corresponding system through SQL injection, compare and verify the data between the systems, and generate an audit exception table;

[0009] Step S3: According to the data in the audit exception table, configure the dispatch SQL script to generate abnormal dispatch data;

[0010] Step S4: Generate tasks and the latest abnormal data according to the set calibration rules, check the latest abnormal data with the abnormal dispatch data, if the abnormal dispatch data is not in the latest abnormal data, change the status of the abnormal dispatch data; if the abnormal dispatch data is in the latest abnormal data, automatically dispatch the order.

[0011] In order to better implement the present invention, further, the step S1 specifically includes the following steps:

[0012] Step S11: Configure the metadata FTP server information of the network management system, CRM system, and AAA system.

[0013] Step S12: calling the scheduled task manager to configure the automatic collection task according to the data file of the corresponding system, and periodically reading the data file of the corresponding system through the cron expression;

[0014] Step S13: Aggregate the acquired underlying network equipment basic data, resource management system data, user order data, and user AAA data to the data processing platform and perform standardized processing.

[0015] In order to better implement the present invention, further, the specific operation of the standardization processing in step S13 is: first call the Groovy script to configure the corresponding system's parsing regular expression to parse it into a standard dotted decimal IP address list to obtain standardized multi-source data, and then clean the standardized multi-source data.

[0016] In order to better implement the present invention, further, the specific operation of configuring the audit SQL script is: first configure the where condition of the audit SQL script, then configure the output result field of the SQL script, and finally store the status identification information to be compared and audited into the audit exception table.

[0017] In order to better implement the present invention, further, the where condition of the O domain audit sql script is network management table.${audit field}=resource table.${audit field}; the where condition of the B domain audit sql script is CRM table.${audit field}=AAA table.${audit field}; the where condition of the BO domain audit sql script is network management.${audit field}=resource.${audit field}AND resource.${audit field}=CRM.${audit field}.

[0018] In order to better implement the present invention, further, the specific operation of step S3 is: first configure the where condition of the dispatching SQL script, and then configure the as query result field of the dispatching SQL script; the as query result field is consistent with the dispatching interface field of the comprehensive coordination system; the where condition of the dispatching SQL script is audit exception table.Indicator name = ${indicator name} AND audit exception table.Comparison result status = exception.

[0019] In order to better implement the present invention, further, the step S4 specifically includes the following steps:

[0020] Step S41: Obtain the outsql_content field from the dispatch SQL script and read the abnormal dispatch data to be dispatched;

[0021] Step S42: Obtain and analyze the delay rules of the current audit scenario. If the abnormal dispatch data matches the delay rule, call the dispatch capability interface of the integrated dispatch system to delay to the specified time point before dispatching the audit work order. If it does not match, call the dispatch capability interface of the integrated dispatch system to dispatch the audit work order.

[0022] Step S43: If the in-transit work order analysis capability interface of the integrated coordination system indicates that new work orders are not allowed to be received, the remaining audit work orders are entered into the next dispatch cycle;

[0023] Step S44: merging the same business number and the same abnormal dispatch data entity into one audit work order and adding the abnormal scenario to the audit work order being processed;

[0024] Step S45: After the abnormal dispatch data is calibrated by calling the set calibration rules, the abnormal dispatch data is compared again according to the calibration rules. After verifying that the abnormal dispatch data is consistent, the data status is updated, and the comprehensive coordination system is called to archive the audit work order to form a closed-loop control.

[0025] Based on the above-mentioned automatic calibration method for MBO data of telecom operators, in order to better realize the present invention, further, a system for automatic calibration of MBO data of telecom operators is proposed, which is used to execute the above-mentioned automatic calibration method for MBO data of telecom operators; it includes a standardization unit, an audit unit, a dispatching unit, and a calibration unit;

[0026] The standardization unit is used to configure metadata FTP server information in multiple domain systems and standardize multi-source data;

[0027] The audit unit is used to configure the audit data SQL field of the corresponding system by SQL injection according to the standardized multi-source data, and compare and verify the data between the systems to generate an audit exception table;

[0028] The dispatch unit is used to configure the dispatch SQL script according to the data in the audit exception table to generate abnormal dispatch data;

[0029] The calibration unit is used to generate tasks and the latest exception data according to the set calibration rules, check the latest exception data with the exception dispatch data, and if the exception dispatch data does not appear in the latest exception data, change the state of the exception dispatch data; if the exception dispatch data appears in the latest exception data, automatically dispatch the order.

[0030] Based on the above-mentioned method for automatic calibration of telecom operator MBO data, in order to better realize the present invention, further, an electronic device is proposed, including a memory and a processor; a computer program is stored on the memory; when the computer program is executed on the processor, the above-mentioned method for automatic calibration of telecom operator MBO data is realized.

[0031] Based on the above-mentioned method for automatic calibration of telecom operator MBO data, in order to better realize the present invention, further, a computer-readable storage medium is proposed, on which computer instructions are stored; when the computer instructions are executed on the above-mentioned electronic device, the above-mentioned method for automatic calibration of telecom operator MBO data is implemented.

[0032] The present invention has the following beneficial effects:

[0033] (1) The present invention shields data differences by autonomous SQL injection, thereby reducing the complexity of data calibration.

[0034] (2) The present invention encapsulates the calibration rule engine, reduces hard coding and repeated custom development, and shortens the demand delivery cycle and process.

[0035] (3) The present invention encapsulates parameters such as the number of dispatch orders and delay time, which facilitates the adjustment of dispatch strategies during data management and improves response efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 The present invention provides a schematic block diagram of the overall process.

[0037] Figure 2 A schematic block diagram of the order dispatching process provided in an embodiment of the present invention.

[0038] Figure 3 This is a schematic diagram of the calibration rule provided by the present invention.

[0039] Figure 4 A schematic diagram for comparing the O-domain network management and resource data of the Internet dedicated line product provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to more clearly illustrate the technical solutions of the embodiments 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. It should be understood that the described embodiments are only part of the embodiments of the present invention, not all of the embodiments, and therefore should not be regarded as limiting the scope of protection. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technical personnel in this field without making creative work are within the scope of protection of the present invention.

[0041] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "disposed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0042] Embodiment 1:

[0043] This embodiment provides a method for automatically calibrating MBO data of a telecommunications operator, which specifically includes the following steps:

[0044] Step S1: Configure metadata FTP server information in multiple domain systems and standardize multi-source data.

[0045] Furthermore, the step S1 specifically includes the following steps:

[0046] Step S11: Configure the metadata FTP server information of the network management system, CRM system, and AAA system.

[0047] Step S12: calling the scheduled task manager to configure the automatic collection task according to the data file of the corresponding system, and periodically reading the data file of the corresponding system through the cron expression;

[0048] Step S13: Aggregate the acquired underlying network equipment basic data, resource management system data, user order data, and user AAA data to the data processing platform and perform standardized processing.

[0049] Furthermore, the specific operation of the standardization processing in step S13 is: first, calling the Groovy script to configure the corresponding system's parsing regular expression to parse into a standard dotted decimal IP address list to obtain standardized multi-source data, and then cleaning the standardized multi-source data.

[0050] Step S2: Based on the standardized multi-source data, configure the audit data SQL field of the corresponding system through SQL injection, compare and verify the data between the systems, and generate an audit exception table.

[0051] The specific operations for configuring the audit SQL script are: first configure the where condition of the audit SQL script, then configure the output result field of the SQL script, and finally store the status identification information to be compared and audited into the audit exception table.

[0052] The where condition of the O domain audit sql script is network management table.${audit field} = resource table.${audit field}; the where condition of the B domain audit sql script is CRM table.${audit field} = telecommunications operator MBO data automatic calibration method A table.${audit field}; the where condition of the BO domain audit sql script is network management.${audit field} = resource.${audit field} AND resource.${audit field} = CRM.${audit field}.

[0053] Step S3: According to the data in the audit exception table, configure the dispatch SQL script to generate abnormal dispatch data.

[0054] Furthermore, the specific operation of step S3 is: first configure the where condition of the dispatch SQL script, and then configure the as query result field of the dispatch SQL script; the as query result field is consistent with the dispatch interface field of the comprehensive coordination system; the where condition of the dispatch SQL script is audit exception table.Indicator name = ${indicator name} AND audit exception table.Comparison result status = abnormal.

[0055] Step S4: Generate tasks and the latest abnormal data according to the set calibration rules, check the latest abnormal data with the abnormal dispatch data, if the abnormal dispatch data is not in the latest abnormal data, change the status of the abnormal dispatch data; if the abnormal dispatch data is in the latest abnormal data, automatically dispatch the order.

[0056] The step S4 specifically comprises the following steps:

[0057] Step S41: Obtain the outsql_content field from the dispatch SQL script and read the abnormal dispatch data to be dispatched;

[0058] Step S42: Obtain and analyze the delay rules of the current audit scenario. If the abnormal dispatch data matches the delay rule, call the dispatch capability interface of the integrated dispatch system to delay to the specified time point before dispatching the audit work order. If it does not match, call the dispatch capability interface of the integrated dispatch system to dispatch the audit work order.

[0059] Step S43: If the in-transit work order analysis capability interface of the integrated coordination system indicates that new work orders are not allowed to be received, the remaining audit work orders are entered into the next dispatch cycle;

[0060] Step S44: merging the same business number and the same abnormal dispatch data entity into one audit work order and adding the abnormal scenario to the audit work order being processed;

[0061] Step S45: After the abnormal dispatch data is calibrated by calling the set calibration rules, the abnormal dispatch data is compared again according to the calibration rules. After verifying that the abnormal dispatch data is consistent, the data status is updated, and the comprehensive coordination system is called to archive the audit work order to form a closed-loop control.

[0062] Working principle:

[0063] Embodiment 2:

[0064] This embodiment is based on the above embodiment 1. Figure 1 , Figure 2 , Figure 3 , Figure 4 As shown, a specific embodiment is described in detail.

[0065] This embodiment standardizes and adapts the source data through SQL injection, shields the differences between the data, and configures the calibration standards and dispatching rules specifically for the business scenario.

[0066] Before creating a new data audit scenario, insert a configuration record in the following product data audit scenario configuration table based on the characteristics of the audit data, and enter key attributes: audit product, scenario type, data source FTP server. The ftp_ prefix field is used for subsequent scheduled tasks to automatically download the original data file from FTP for parsing and storage, generate audit data SQL, and generate dispatch data SQL.

[0067]

[0068]

[0069] The injection SQL convention is as follows:

[0070] select-product code,

[0071] - ... product name,

[0072] - ...calibrated scene encoding,

[0073] --Calibration scene description,

[0074] -area,

[0075] - Keywords,

[0076] - ...keyword value,

[0077] --Exception code,

[0078] --Exception name,

[0079] --Calibration time,

[0080] From the source data table,

[0081] where condition;

[0082] Step S1: Aggregation of data in various fields, by configuring the metadata FTP server information of the network management system, resource system, CRM system, and AAA system, and associating the configuration table fields: ftp_ip, ftp_port, ftp_username, ftp_password, ftp_path, the scheduled task manager configures an automatic collection task according to each data file, and reads the data files of the corresponding system periodically on a daily basis through cron expressions, so that the basic data of the underlying network equipment, resource management system data, user order data, and user AAA data are aggregated on the same data processing platform.

[0083] Standardized data format and business IP address: The original data of the network management system, resource system, and CRM system all have ip_address fields, but the storage formats are inconsistent, such as the CIDR representation of IP addresses, IP address segments manually marked with "-", and multiple IP addresses separated by custom characters. By embedding Groovy scripts, the corresponding parsing regular expressions configured according to different business ip_address field formats are parsed into a standard dotted decimal IP address list to solve the expression differences of the same attribute resources in different systems.

[0084] Data cleaning is done to ensure the accuracy and validity of data, remove erroneous, duplicated and inconsistent data, and thus improve the overall quality of data. The following processing strategies are used:

[0085] Select a subset: Select the data columns in the data set that need to be analyzed and hide other data columns that do not participate in the analysis.

[0086] Delete duplicate values: only keep the first one of the duplicate data.

[0087] Handling missing values: Handling missing values ​​by methods such as deletion, filling, or interpolation.

[0088] Consistency processing: Use the split column function to process inconsistent data in the data column.

[0089] Outlier processing: remove outliers that are too large or too small.

[0090] Data type conversion: Make sure each variable has the correct data type.

[0091] Step S2: Comparison and verification of data between systems.

[0092] O domain configures data verification, generates audit data SQL field, i.e. insql_content, through configuration, and configures audit SQL script method as follows:

[0093] Configure the where condition of the SQL script, network management table.${audit field} = resource table.${audit field};

[0094] Configure the output result field of the SQL script and store the indicator name and comparison result status identification information of the comparison audit into the audit exception table.

[0095] B domain business information data verification, generate audit data SQL field insql_content through configuration, and configure the audit SQL script method as follows:

[0096] Configure the where condition of the SQL script, CRM table.${audit field} = AAA table.${audit field};

[0097] Configure the output result field of the SQL script and store the indicator name and comparison result status identification information of the comparison audit into the audit exception table.

[0098] BO domain data verification, generate audit data SQL field insql_content through configuration, and configure the audit SQL script method as follows:

[0099] Configure the where condition of the SQL script: NM.${Audit Field} = Resource.${Audit Field} AND Resource.${Audit Field} = CRM.${Audit Field};

[0100] Configure the output result field of the SQL script and store the indicator name and comparison result status identification information of the comparison audit into the audit exception table.

[0101] Step S3: Generate dispatch SQL script.

[0102] According to the data in the audit exception table, configure the SQL script outsql_content to generate the dispatch data. The method for configuring the dispatch SQL script is as follows:

[0103] Configure the where condition of the SQL script: Audit exception table.Indicator name = ${indicator name} AND Audit exception table.Comparison result status = abnormal;

[0104] The as query result field of the configured SQL script is consistent with the dispatch interface field of the integrated dispatching system.

[0105] The comprehensive coordination system provided in this embodiment is a comprehensive service guarantee system established by telecommunications operators to ensure service quality and improve customer satisfaction; the system mainly includes functional modules such as work order management, fault handling, and customer feedback, and aims to solve problems encountered by users in the process of using services through efficient management processes and timely response mechanisms.

[0106] Step S4: The calibration rule engine automatically generates tasks and the latest exception data according to the audit SQL script in step S2. The initial value of the work order flag position is 0, and the data exception flag position is 1. The latest exception data is automatically checked with the existing exception data: if the existing exception data does not appear in the latest exception data, the status of the existing exception data is changed, and an automatic return notification is performed; if the existing exception data still appears in the latest exception data, the data status remains unchanged, and an automatic order is dispatched; the newly added exception data is judged whether to be dispatched according to the dispatch rules such as the dispatch quantity and dispatch delay conditions.

[0107] The dispatch flag settings are shown in Table 1 below.

[0108] Table 1 Dispatch flag position correspondence table

[0109] Work order flag meaning Abnormal data flag meaning 0 No order dispatched 0 Data verification is consistent 1 The order has been dispatched and is being processed. 1 Abnormal data, order pending 2 Archived 2 Data is abnormal, order has been dispatched

[0110] The abnormal data dispatch service is triggered. The calibration rule engine detects abnormal data based on the outsql_content field script SQL of the dispatch data, reads all abnormal data to be dispatched, and calls the dispatch capability interface of the integrated dispatch system, which is an external capability API used to generate an agency work order to notify the operation and maintenance personnel to dispatch the audit work order, and updates the work order flag from 0 to 1, and the data abnormal flag from 1 to 2;

[0111] Before dispatching a work order, the delay rules of the audit scenario are analyzed. If the delay rules are matched, the work order is delayed to the specified time point before dispatching the work order.

[0112] The dispatched work order quantity control calls the in-transit work order analysis capability interface of the integrated dispatching system, which is a service that checks and monitors the work orders being processed. It can monitor their progress in real time and promptly discover potential problems or delays so that appropriate measures can be taken to ensure that the task is completed smoothly as planned. When feedback does not allow the acceptance of new work orders, the remaining work orders will be entered into the next dispatch cycle to avoid work order storms.

[0113] Audit work order merging: merge work orders with the same business number and the same abnormal data entity into one work order and distribute it. You can also add abnormal scenarios to the work orders being processed to reduce the number of orders that maintenance personnel need to accept.

[0114] The work order is automatically returned for verification. After the maintenance personnel complete the calibration of the abnormal data, the calibration rule engine automatically completes the re-comparison of the abnormal data. After verifying the data consistency, the data status is updated, the work order flag is updated from 1 to 2, and the data abnormality flag is updated from 2 to 0, and the integrated dispatching system is notified to archive the work order to form a closed-loop control.

[0115] Working principle: This embodiment ignores the differences in source data, adapts the data through SQL injection, shields the differences between data, and based on engine technology, realizes automatic calibration of data according to calibration rules and closed-loop control of automatic dispatch according to dispatch rules.

[0116] The other parts of this embodiment are the same as those of the above-mentioned embodiment 1, and thus will not be described in detail.

[0117] Embodiment 3:

[0118] Based on any one of the above-mentioned embodiments 1-2, this embodiment proposes a telecommunications operator MBO data automatic calibration system, which is used to execute the above-mentioned telecommunications operator MBO data automatic calibration method; it includes a standardization unit, an audit unit, a dispatch unit, and a calibration unit;

[0119] The standardization unit is used to configure metadata FTP server information in multiple domain systems and standardize multi-source data;

[0120] The audit unit is used to configure the audit data SQL field of the corresponding system by SQL injection according to the standardized multi-source data, and compare and verify the data between the systems to generate an audit exception table;

[0121] The dispatch unit is used to configure the dispatch SQL script according to the data in the audit exception table to generate abnormal dispatch data;

[0122] The calibration unit is used to generate tasks and the latest exception data according to the set calibration rules, check the latest exception data with the exception dispatch data, and if the exception dispatch data does not appear in the latest exception data, change the state of the exception dispatch data; if the exception dispatch data appears in the latest exception data, automatically dispatch the order.

[0123] This embodiment further proposes an electronic device, including a memory and a processor; the memory stores a computer program; when the computer program is executed on the processor, the above-mentioned telecom operator MBO data automatic calibration method is implemented.

[0124] This embodiment further proposes a computer-readable storage medium, on which computer instructions are stored; when the computer instructions are executed on the above-mentioned electronic device, the above-mentioned telecom operator MBO data automatic calibration method is implemented.

[0125] The other parts of this embodiment are the same as any one of the above-mentioned embodiments 1-2, so they will not be repeated here.

[0126] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any simple modification or equivalent change made to the above embodiment based on the technical essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for automatically calibrating MBO data of a telecommunications operator, characterized in that: The specific steps include: Step S1: configuring metadata FTP server information in the telecom operator system and standardizing MBO data; Step S2: Based on the standardized MBO data, configure the audit data SQL field of the corresponding system through SQL injection, compare and verify the data between the systems, and generate an audit exception table; Step S3: According to the data in the audit exception table, configure the dispatch SQL script to generate abnormal dispatch data; Step S4: Generate tasks and the latest abnormal data according to the set calibration rules, check the latest abnormal data with the abnormal dispatch data, if the abnormal dispatch data is not in the latest abnormal data, change the status of the abnormal dispatch data; if the abnormal dispatch data is in the latest abnormal data, automatically dispatch the order.

2. A method for automatically calibrating MBO data of a telecommunications operator according to claim 1, characterized in that: The step S1 specifically includes the following steps: Step S11: Configure the metadata FTP server information of the network management system, CRM system, and AAA system. Step S12: calling the scheduled task manager to configure the automatic collection task according to the data file of the corresponding system, and periodically reading the data file of the corresponding system through the cron expression; Step S13: Aggregate the acquired underlying network equipment basic data, resource management system data, user order data, and user AAA data to the data processing platform and perform standardized processing.

3. A method for automatically calibrating MBO data of a telecommunications operator according to claim 2, characterized in that: The specific operation of the standardization processing in step S13 is: firstly, calling the Groovy script to configure the corresponding system's parsing regular expression to parse into a standard dotted decimal IP address list to obtain standardized multi-source data, and then cleaning the standardized multi-source data.

4. A method for automatically calibrating MBO data of a telecommunications operator according to claim 3, characterized in that: The specific operations for configuring the audit SQL script are: first configure the where condition of the audit SQL script, then configure the output result field of the SQL script, and finally store the status identification information to be compared and audited into the audit exception table.

5. A method for automatically calibrating MBO data of a telecommunications operator according to claim 4, characterized in that: The where condition of the O domain audit sql script is network management table.${audit field}=resource table.${audit field}; the where condition of the B domain audit sql script is CRM table.${audit field}=AAA table.${audit field}; the where condition of the BO domain audit sql script is network management.${audit field}=resource.${audit field}AND resource.${audit field}=CRM.${audit field}.

6. A method for automatically calibrating MBO data of a telecommunications operator according to claim 5, characterized in that: The specific operation of step S3 is: first configure the where condition of the dispatch SQL script, and then configure the as query result field of the dispatch SQL script; the as query result field is consistent with the dispatch interface field of the comprehensive coordination system; the where condition of the dispatch SQL script is audit exception table.Indicator name=${indicator name}AND audit exception table.Comparison result status=abnormal.

7. The method for automatically calibrating MBO data of a telecommunications operator according to claim 1, characterized in that: The step S4 specifically comprises the following steps: Step S41: Obtain the outsql_content field from the dispatch SQL script and read the abnormal dispatch data to be dispatched; Step S42: Obtain and analyze the delay rules of the current audit scenario. If the abnormal dispatch data matches the delay rule, call the dispatch capability interface of the integrated dispatch system to delay to the specified time point before dispatching the audit work order. If it does not match, call the dispatch capability interface of the integrated dispatch system to dispatch the audit work order. Step S43: If the in-transit work order analysis capability interface of the integrated coordination system indicates that new work orders are not allowed to be received, the remaining audit work orders are entered into the next dispatch cycle; Step S44: merging the same business number and the same abnormal dispatch data entity into one audit work order and adding the abnormal scenario to the audit work order being processed; Step S45: After the abnormal dispatch data is calibrated by calling the set calibration rules, the abnormal dispatch data is compared again according to the calibration rules. After verifying that the abnormal dispatch data is consistent, the data status is updated, and the comprehensive coordination system is called to archive the audit work order to form a closed-loop control.

8. A telecommunications operator MBO data automatic calibration system, used to execute the telecommunications operator MBO data automatic calibration method as claimed in claim 1; characterized in that: Including standardization unit, audit unit, dispatch unit and calibration unit; The standardization unit is used to configure metadata FTP server information in multiple domain systems and standardize multi-source data; The audit unit is used to configure the audit data SQL field of the corresponding system by SQL injection according to the standardized multi-source data, and compare and verify the data between the systems to generate an audit exception table; The dispatch unit is used to configure the dispatch SQL script according to the data in the audit exception table to generate abnormal dispatch data; The calibration unit is used to generate tasks and the latest exception data according to the set calibration rules, check the latest exception data with the exception dispatch data, and if the exception dispatch data does not appear in the latest exception data, change the state of the exception dispatch data; if the exception dispatch data appears in the latest exception data, automatically dispatch the order.

9. An electronic device, characterized in that: It comprises a memory and a processor; the memory stores a computer program; when the computer program is executed on the processor, the automatic calibration method for MBO data of telecommunications operators as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions; when the computer instructions are executed on the electronic device as claimed in claim 9, the method for automatic calibration of MBO data of telecommunications operators as claimed in any one of claims 1-7 is implemented.

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