Data processing method and device, electronic equipment and storage medium

Abstract

The invention discloses a data processing method and device, electronic equipment and a storage medium, through the data processing method and device, basic data containing an internet protocol address can be exported from a mobile equipment management system, and dirty data with institution affiliation information missing or error can be accurately screened out; carrying out network topology matching through a preset mapping table based on the internet protocol address characteristics of the dirty data, and generating correct mechanism affiliation information corresponding to the current equipment position; in combination with equipment hardware features, operating system types and matched mechanism affiliation information, user name and service type fields are repaired through a multi-dimensional rule engine, and finally standardized data are generated, so that data consistency is ensured; the technical effects of correcting dirty data, guaranteeing the accuracy and consistency of the basic data of the equipment, generating a standardized data format and improving the data management efficiency and data quality of the mobile equipment management system are achieved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of data processing, and particularly relates to a data processing method and device, electronic equipment and storage medium. BACKGROUND

[0002] The mobile device management system is widely used in the financial industry device management scene as an important support for enterprise digital transformation. In the related art, through the collaborative work of data collection, processing analysis and decision control, a technical system for device full life cycle management is constructed.

[0003] In the existing mobile device management system data governance method, when the physical location of the device changes, the IP field can be automatically updated, but the organization affiliation field still retains the static value of the first registration, resulting in inconsistent data. SUMMARY

[0004] The present disclosure provides a data processing method, device, electronic equipment and storage medium.

[0005] According to a first aspect of the present disclosure, a data processing method is provided, which comprises: Exporting basic data containing an Internet Protocol address field from a mobile device management system, and screening out dirty data with missing or incorrect organization affiliation information; Based on the Internet Protocol address features of the dirty data, network topology matching is performed through a preset Internet Protocol address segment and organization number mapping table to generate corresponding organization affiliation information; According to the device hardware features, operating system type and matched organization affiliation information, the username and business type fields of the dirty data are calculated through a multi-dimensional data repair rule engine; Based on the repaired basic data, a standardized data format is generated.

[0006] Optionally, the exporting of the basic data containing the Internet Protocol address field from the mobile device management system and the screening of the dirty data with missing or incorrect organization affiliation information comprise: Extracting the Internet Protocol address field in the basic data based on a regular expression; Determining whether the username field is empty and / or whether the business type field is a default value; If it is determined that the username field is empty and / or the business type field is a default value, the dirty data is determined.

[0007] Optionally, the network topology matching based on the Internet Protocol address features of the dirty data through the preset Internet Protocol address segment and organization number mapping table to generate corresponding organization affiliation information comprises: The minimum edit distance algorithm is used to calculate the similarity of the dirty data Internet protocol address and the Internet protocol address segment of the institution in the mapping table, and the institution number with a similarity greater than a preset threshold is selected as the matching result. When the similarity is less than the preset threshold, the network prefix of the Internet protocol address is matched with the preset prefix in the institution number database.

[0008] Optionally, the generating of the standardized data format based on the repaired basic data comprises: arranging the repaired data according to a preset template field order; wherein the fields include at least one of a device identifier, a device unique identification number, a user name, a service type, and an Internet protocol address; performing format verification on the generated standardized data.

[0009] Optionally, the method further comprises: receiving a single Internet protocol address query request input by a user; based on the single Internet protocol address query request, calling the Internet protocol address segment and institution number mapping table for real-time query, and showing the corresponding institution attribution information to the user.

[0010] According to a second aspect of the present disclosure, a data processing apparatus is provided, comprising: a screening unit configured to export basic data containing an Internet protocol address field from a mobile device management system, and screen out dirty data with missing or incorrect institution attribution information; a matching unit configured to perform network topology matching based on the Internet protocol address features of the dirty data through a preset Internet protocol address segment and institution number mapping table, and generate corresponding institution attribution information; a calculation unit configured to calculate the user name and service type fields of the dirty data through a multi-dimensional data repair rule engine according to device hardware features, operating system types, and the matched institution attribution information; a generating unit configured to generate a standardized data format based on the repaired basic data.

[0011] Optionally, the screening unit is further configured to: extract the Internet protocol address field in the basic data based on a regular expression; determine whether the user name field is empty and / or whether the service type field is a default value; if it is determined that the user name field is empty and / or the service type field is a default value, the dirty data is determined.

[0012] Optionally, the matching unit is further configured to: The minimum edit distance algorithm is used to calculate the similarity of the dirty data Internet protocol address and the Internet protocol address segment of the institution in the mapping table, and the institution number with a similarity greater than a preset threshold is selected as the matching result. When the similarity is less than the preset threshold, the network prefix of the Internet protocol address is matched with a preset prefix in the institution number database.

[0013] Optionally, the generating unit is further configured to: arrange the repaired data according to a preset template field order, wherein the fields include at least one of a device identifier, a device unique identification number, a username, a service type, and an Internet protocol address. perform format verification on the generated standardized data.

[0014] Optionally, the apparatus further includes: a receiving unit configured to receive a single Internet protocol address query request input by a user; a querying unit configured to perform real-time querying based on the single Internet protocol address query request, by calling an Internet protocol address segment and institution number mapping table, and show corresponding institution attribution information to the user.

[0015] According to a third aspect of the present disclosure, an electronic device is provided, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of the first aspect.

[0016] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to perform the method of the first aspect.

[0017] According to a fifth aspect of the present disclosure, a computer program product is provided, including a computer program which, when executed by a processor, implements the method of the first aspect.

[0018] The data processing method, apparatus, electronic device, and storage medium disclosed herein, through this application, can export basic data containing Internet Protocol addresses from a mobile device management system, accurately filter out dirty data with missing or incorrect organizational affiliation information; based on the Internet Protocol address characteristics of the dirty data, network topology matching is performed through a preset mapping table to generate correct organizational affiliation information corresponding to the current device location; then, combined with device hardware characteristics, operating system type, and the matched organizational affiliation information, a multi-dimensional rule engine is used to repair the username and business type fields, ultimately generating standardized data and ensuring data consistency. Therefore, it can solve the data inconsistency problem caused by the automatic updating of the IP field but the retention of the initial registration static value in the organizational affiliation field when the device's physical location changes in existing mobile device management system data governance methods, achieving the technical effects of correcting dirty data, ensuring the accuracy and consistency of basic device data, generating standardized data formats, and improving the data governance efficiency and data quality of mobile device management systems.

[0019] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0020] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1 A schematic flowchart illustrating a data processing method provided in an embodiment of this disclosure; Figure 2 This is a schematic diagram of the structure of a data processing apparatus provided in an embodiment of the present disclosure; Figure 3 A schematic diagram of the structure of another data processing apparatus provided in an embodiment of this disclosure; Figure 4 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0021] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0022] The following description, with reference to the accompanying drawings, outlines a data processing method, apparatus, electronic device, and storage medium according to embodiments of the present disclosure.

[0023] Figure 1 This is a schematic flowchart illustrating a data processing method provided in an embodiment of the present disclosure.

[0024] like Figure 1 As shown, the method includes the following steps: Step 101: Export basic data containing Internet Protocol address fields from the mobile device management system and filter out dirty data with missing or incorrect organization affiliation information. The Mobile Device Management System (MDM) has a management console for centralized management of mobile device data. Internet Protocol (IP) addresses are key fields in the basic data. Dirty data refers to data in the basic data that lacks or contains incorrect organizational affiliation information. In the China Construction Bank's (CCB) technology system, organizational affiliation corresponds to a unique 9-digit organizational number. Each device must be clearly assigned to a specific branch or department. If the basic data lacks this 9-digit organizational number, or if the organizational number does not match the actual branch or department to which the device belongs, the basic data is considered dirty data. During execution, the MDM system's management console is used to retrieve and export all basic data containing IP address fields. Leveraging the MDM system's centralized device data management capabilities, complete basic data for each device is ensured. Then, based on the 9-digit organizational number corresponding to the organizational affiliation and the actual organizational information of the device, the exported basic data is filtered to separate out dirty data with missing or incorrect organizational affiliation information. This prepares the data for subsequent dirty data processing, ensuring the smooth progress of subsequent device management operations.

[0025] Step 102: Based on the Internet Protocol address characteristics of the dirty data, perform network topology matching by matching the preset Internet Protocol address range with the organization number mapping table to generate the corresponding organization affiliation information; Internet Protocol address characteristics refer to the network segment and other characteristics of the IP address corresponding to dirty data. The preset Internet Protocol address segment and institution number mapping table is established in advance based on the CCB network topology, which records the correspondence between each IP segment and a unique 9-digit institution number. The institution affiliation information includes the 9-digit institution number and the corresponding specific branch or sub-branch department information. During execution, the IP address of each piece of dirty data is first extracted, and its network segment characteristics are analyzed, such as the network segment formed by the first few digits representing the network area in the IP address. Then, a preset mapping table is called. This mapping table is built based on the distribution pattern of internal equipment networks of China Construction Bank (CCB) and covers the IP segment range corresponding to all CCB subsidiaries, ensuring that each IP segment can be accurately matched with a unique 9-digit institution number. Subsequently, through network topology matching, the network segment of the IP address of the dirty data is compared with the IP segment in the mapping table to determine the preset IP segment to which the IP address belongs. Based on the 9-digit institution number corresponding to the IP segment in the mapping table, combined with the correspondence between the 9-digit institution number and the specific branch or sub-branch department in CCB's technical system, complete institution affiliation information is generated. This completes the institution affiliation field in the dirty data, laying the foundation for the subsequent dirty data to comply with the management requirements of the Mobile Device Management System (MDM system) and ensuring that subsequent batch operations can accurately locate the institution to which the device belongs.

[0026] Step 103: Based on the device hardware characteristics, operating system type, and matching organization affiliation information, calculate the username and business type fields of the dirty data using a multi-dimensional data repair rule engine; Equipment hardware characteristics refer to the inherent identification information of the equipment itself, such as the equipment serial number. This information reflects the equipment model, production batch, and usage attributes. The operating system type refers to the type of system that the equipment runs on, such as common mobile device operating systems. Different operating system types are often related to the business purpose of the equipment. The multi-dimensional data repair rule engine is a set of rules built in advance based on the CCB equipment management logic, business scenarios of various institutions, and data patterns. It integrates the correlation logic between hardware characteristics, operating system type, and institution affiliation information. The username is the UASS number, and the business type field is an identifier that distinguishes the business category carried by the equipment. Both are key fields for the automated management of the Mobile Device Management System (MDM system). During execution, the device hardware characteristics and operating system type are first extracted from the device information associated with the dirty data to clarify the basic attributes of the device. Then, the multi-dimensional data repair rule engine is called. This engine has preset the username format and business type distribution rules corresponding to different hardware characteristics and operating system types under the same organization. Subsequently, the extracted device hardware characteristics, operating system type, and organization affiliation information obtained in step 102 are input into the engine. The engine calculates according to preset rules to determine the username (UASS number) and business type fields that meet the requirements of the device attributes and the organization to which it belongs. This fills the gaps in these two key fields in the dirty data or corrects errors, ensuring that the dirty data meets the management standards of the MDM system.

[0027] Step 104: Generate a standardized data format based on the repaired basic data.

[0028] The repaired basic data includes complete information on organization affiliation, username (UASS number), and business type. All key fields are accurate and include essential device data such as device serial number, internet protocol address (IP address), organization affiliation corresponding to the 9-digit organization number, username (UASS number), and business type, which are required by the Mobile Device Management System (MDM system). The standardized data format is a unified data structure that meets the batch import requirements of the MDM system. This format is preset by the MDM system and clarifies the field arrangement order, data type specifications, and character length requirements of each key piece of information, ensuring that the data can be accurately recognized by the MDM system and used for subsequent management operations. During execution, the repaired basic data is first validated to confirm that fields such as device serial number, IP address, 9-digit institution number corresponding to the institution's affiliation, username (UASS number), and business type are complete and conform to data logic. For example, it checks whether the username (UASS number) conforms to the internal coding rules of China Construction Bank and whether the business type matches the business scenario of the institution to which the device belongs. Then, according to the format specifications for batch import in the MDM system, the field order of the repaired basic data is adjusted, arranging the key information in a preset order, while unifying the data type. For example, the institution number format is adjusted to a pure numeric type, and the IP address format is ensured to conform to the Internet Protocol standard. Finally, the data format is converted according to the specifications to generate a standardized data format, so that the data can be directly adapted to the batch import function of the MDM system, laying the foundation for importing the repaired data into the system and improving the management of basic device data.

[0029] In some embodiments, exporting basic data containing Internet Protocol address fields from the mobile device management system and filtering out dirty data with missing or incorrect organization affiliation information includes: Extracting Internet Protocol Address fields from basic data using regular expressions; Determine if the username field is empty and / or if the business type field is a default value; If the username field is determined to be empty and / or the business type field is set to a default value, then the data is identified as dirty data.

[0030] Regular expressions are matching rules customized based on the format characteristics of Internet Protocol addresses (IP addresses) (usually consisting of four segments of numbers in the range of 0-255 connected by periods). They are used to accurately identify and extract IP address fields from basic data, avoiding omissions or errors in IP address extraction due to mixed data formats. The username field is the UASS number required for automated management by the Mobile Device Management System (MDM system), which is a key identifier for associating devices with users. The default value of the service type field refers to the default value or fixed identifier initially presented by this field when it has not been manually configured or correctly updated in the MDM system, and cannot reflect the actual service scope carried by the device.

[0031] During execution, a custom regular expression is first invoked to traverse and scan the basic data exported from the MDM system. Based on the IP address format rules, the IP address field corresponding to each data entry is accurately extracted from the basic data containing multiple fields, ensuring reliable data support for subsequent IP address-based operations. Subsequently, the basic data with extracted IP address fields is further verified. On the one hand, it checks whether the username field is empty; on the other hand, it confirms whether the business type field is still at the system's initial default value. If a data entry meets either the condition that the username field is empty or the business type field is at its default value, it can be determined that the data is dirty data with missing or incorrect organizational affiliation information. This provides a clear target for subsequent targeted repair of dirty data, ensuring that subsequent data repair work can accurately focus on the problematic data.

[0032] In some embodiments, the generation of corresponding organization affiliation information based on the Internet Protocol address characteristics of the dirty data, through network topology matching between a preset Internet Protocol address range and an organization number mapping table, includes: The minimum edit distance algorithm is used to calculate the similarity between the Internet Protocol address of dirty data and the Internet Protocol address range of the organization in the mapping table, and the organization number with a similarity greater than a preset threshold is selected as the matching result; When the similarity is less than the preset threshold, the network prefix of the Internet Protocol address is matched with the preset prefix in the organization number database.

[0033] The minimum edit distance algorithm is used to calculate the degree of difference between two strings (here, the Internet Protocol address of dirty data, i.e., IP address and the institutional IP segment in the mapping table). It quantifies the similarity between the two by statistically analyzing the minimum number of insertion, deletion, or replacement operations required to convert one string into another. The preset threshold is a similarity threshold set in advance based on the CCB network topology and IP address allocation rules, used to determine the matching validity of IP addresses and institutional IP segments. The network prefix is ​​the first few digits in the IP address used to identify the network area, and different institutions correspond to fixed network prefixes. The institution number database is a database that stores the 9-digit institution number of all CCB institutions and their corresponding preset network prefixes.

[0034] During execution, the minimum edit distance algorithm is first invoked to calculate the similarity between each dirty data IP address and the IP segments of each institution in the preset IP segment and institution number mapping table. This algorithm precisely quantifies the degree of matching between the two. Next, the calculated similarity is compared with a preset threshold. If the similarity is greater than the preset threshold, it indicates a high degree of matching between the dirty data IP address and the corresponding institution IP segment, and the 9-digit institution number associated with that institution IP segment is directly used as the matching result. If the similarity is less than the preset threshold, it indicates that direct matching does not meet the requirements. In this case, the network prefix of the dirty data IP address is extracted and compared with the preset network prefixes corresponding to each institution in the institution number database. Once a matching preset network prefix is ​​found, the associated 9-digit institution number is determined as the matching result. Then, combined with the correspondence between the institution number and the specific branch or sub-branch department, complete institution affiliation information is generated, ensuring that even when direct similarity is insufficient, the institution affiliation of dirty data can still be accurately determined through network prefix matching.

[0035] In some embodiments, generating a standardized data format based on the repaired base data includes: The repaired data is arranged in the order of preset template fields; wherein the fields include at least one of device identifier, device unique identification number, username, service type, and Internet protocol address; Perform format validation on the generated standardized data.

[0036] The preset template is a pre-defined field arrangement rule template based on the batch import requirements of the mobile device management system, ensuring that the generated standardized data can be accurately identified by the MDM system; the device identifier is identification information used to distinguish device categories in the MDM system, which can be associated with the business domain or usage scenario to which the device belongs; the device unique identifier, i.e., the device serial number, is a unique identity identifier for each device, which can accurately locate a single device; the username, i.e., the UASS number, the business type is a field that distinguishes the type of business carried by the device, and the Internet Protocol address (IP address) is key information for device network positioning. These fields are all core data for the MDM system to manage devices.

[0037] During execution, a preset template is first retrieved. This template clearly specifies the fixed order of fields such as device identifier, unique device identification number, username, service type, and IP address. This order is consistent with the field reading order during batch import in the MDM system, preventing data import failure due to disordered field order. Then, the repaired basic data is arranged according to the template order, ensuring that the device identifier, unique device identification number (e.g., device serial number), username (UASS number), service type, and IP address fields for each piece of repaired data are filled into the designated positions in the template. If the repaired data includes some fields from the template, the existing core fields must also be arranged completely in the corresponding order. After arrangement, the generated standardized data undergoes format validation. The validation includes verifying whether the data type of each field meets the requirements (e.g., IP address must conform to the four-segment dotted-point format, username must follow the CCB UASS number encoding rules) and whether there are any empty values ​​(core fields such as unique device identification number and username cannot be empty). This validation ensures that the standardized data has no format errors and can directly adapt to the batch import function of the MDM system, providing a compliant data foundation for subsequent batch device management operations.

[0038] In some embodiments, the method further includes: Receive a single Internet Protocol address lookup request input by the user; Based on the single Internet Protocol address query request, the mapping table between Internet Protocol address ranges and organization numbers is invoked for real-time querying, and the corresponding organization affiliation information is displayed to the user.

[0039] A single Internet Protocol address query request entered by the user refers to a query command for a single Internet Protocol address (i.e., IP address) entered by the internal equipment management personnel of China Construction Bank through the graphical interface of the tool. This is used to obtain the organizational affiliation of the device corresponding to the IP address. The mapping table between Internet Protocol address segments and organizational numbers is still a preset table that is constructed in advance based on the network topology of China Construction Bank. It records the correspondence between each IP segment and a unique 9-digit organizational number. The organizational affiliation information includes the 9-digit organizational number and the name of the corresponding specific branch or sub-branch department.

[0040] During execution, the tool first receives a single IP address query request from the user. Simultaneously, it performs a preliminary validation of the input IP address format to ensure it conforms to the standard four-segment dotted-out IP format, preventing query failures due to format errors. After successful validation, the tool immediately calls a pre-defined IP address range-to-organization number mapping table, comparing the user-queried IP address with the various IP ranges in the table to determine the IP range to which the IP address belongs. Then, based on the 9-digit organization number corresponding to that IP range in the mapping table, and considering the association between the 9-digit organization number and specific branches / departments within the China Construction Bank's technical system, it generates attribution information including the specific organization name. Finally, the tool displays the retrieved organization attribution information to the user through a graphical interface, allowing users to quickly obtain the organization attribution information of a single device and providing efficient support for single-point query needs in daily device management.

[0041] Corresponding to the data processing method described above, the present invention also proposes a data processing apparatus. Since the apparatus embodiments of the present invention correspond to the method embodiments described above, details not disclosed in the apparatus embodiments can be referred to in the method embodiments described above, and will not be repeated here.

[0042] Figure 2 This is a schematic diagram of the structure of a data processing apparatus provided in an embodiment of the present disclosure, as shown below. Figure 2 As shown, it includes: The filtering unit 21 is used to export basic data containing Internet Protocol address fields from the mobile device management system and filter out dirty data with missing or incorrect organization affiliation information. The matching unit 22 is used to perform network topology matching with the organization number mapping table based on the Internet Protocol address characteristics of the dirty data, and generate corresponding organization affiliation information. The calculation unit 23 is used to calculate the username and business type fields of the dirty data through a multi-dimensional data repair rule engine based on the device hardware characteristics, operating system type and matching organization affiliation information; Generation unit 24 is used to generate a standardized data format based on the repaired base data.

[0043] Furthermore, in one possible implementation of this disclosure, the filtering unit 21 is further configured to: Extracting Internet Protocol Address fields from basic data using regular expressions; Determine if the username field is empty and / or if the business type field is a default value; If the username field is determined to be empty and / or the business type field is set to a default value, then the data is identified as dirty data.

[0044] Furthermore, in one possible implementation of this disclosure, the matching unit 22 is further configured to: The minimum edit distance algorithm is used to calculate the similarity between the Internet Protocol address of dirty data and the Internet Protocol address range of the organization in the mapping table, and the organization number with a similarity greater than a preset threshold is selected as the matching result; When the similarity is less than the preset threshold, the network prefix of the Internet Protocol address is matched with the preset prefix in the organization number database.

[0045] Furthermore, in one possible implementation of this disclosure embodiment, the generation unit 24 is further configured to: The repaired data is arranged in the order of preset template fields; wherein the fields include at least one of device identifier, device unique identification number, username, service type, and Internet protocol address; Perform format validation on the generated standardized data.

[0046] Furthermore, in one possible implementation of the embodiments of this disclosure, such as Figure 3 As shown, the device further includes: The receiving unit 25 is used to receive a single Internet Protocol address query request input by the user; The query unit 26 is used to perform a real-time query based on the single Internet Protocol address query request, by calling the Internet Protocol address range and organization number mapping table, and to display the corresponding organization affiliation information to the user.

[0047] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of the embodiments of this disclosure, and the principle is the same. Therefore, the embodiments of this disclosure are not limited thereto.

[0048] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0049] Figure 4 A schematic block diagram of an example electronic device 400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0050] like Figure 4As shown, device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 402 or a computer program loaded from storage unit 408 into RAM (Random Access Memory) 403. RAM 403 may also store various programs and data required for the operation of device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via bus 404. I / O (Input / Output) interface 405 is also connected to bus 404.

[0051] Multiple components in device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of monitors, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0052] The computing unit 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as data processing methods. For example, in some embodiments, the data processing methods may be implemented as computer software programs tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the methods described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the aforementioned data processing method by any other suitable means (e.g., by means of firmware).

[0053] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0054] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0055] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0056] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0057] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0058] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0059] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0060] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0061] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A data processing method, characterized in that, include: Export basic data containing Internet Protocol address fields from the mobile device management system and filter out dirty data with missing or incorrect organization affiliation information; Based on the Internet Protocol address characteristics of the dirty data, network topology matching is performed by matching the preset Internet Protocol address range with the organization number mapping table to generate the corresponding organization affiliation information; Based on the device hardware characteristics, operating system type, and matching organization affiliation information, the username and business type fields of the dirty data are calculated through a multi-dimensional data repair rule engine; A standardized data format is generated based on the repaired base data.

2. The method according to claim 1, characterized in that, The process of exporting basic data containing Internet Protocol address fields from the mobile device management system and filtering out dirty data with missing or incorrect organization affiliation information includes: Extracting Internet Protocol Address fields from basic data using regular expressions; Determine if the username field is empty and / or if the business type field is a default value; If the username field is determined to be empty and / or the business type field is set to a default value, then the data is identified as dirty data.

3. The method according to claim 1, characterized in that, The Internet Protocol address features based on the dirty data are used to perform network topology matching between a preset Internet Protocol address range and an organization number mapping table to generate corresponding organization affiliation information, including: The minimum edit distance algorithm is used to calculate the similarity between the Internet Protocol address of dirty data and the Internet Protocol address range of the organization in the mapping table, and the organization number with a similarity greater than a preset threshold is selected as the matching result; When the similarity is less than the preset threshold, the network prefix of the Internet Protocol address is matched with the preset prefix in the organization number database.

4. The method according to claim 1, characterized in that, The standardized data format generated based on the repaired basic data includes: The repaired data is arranged in the order of preset template fields; wherein the fields include at least one of device identifier, device unique identification number, username, service type, and Internet protocol address; Perform format validation on the generated standardized data.

5. The method according to claim 1, characterized in that, The method further includes: Receive a single Internet Protocol address lookup request input by the user; Based on the single Internet Protocol address query request, the mapping table between Internet Protocol address ranges and organization numbers is invoked for real-time querying, and the corresponding organization affiliation information is displayed to the user.

6. A data processing apparatus, characterized in that, include: The filtering unit is used to export basic data containing Internet Protocol address fields from the mobile device management system and filter out dirty data with missing or incorrect organization affiliation information. The matching unit is used to perform network topology matching between the Internet Protocol address characteristics of the dirty data and the organization number mapping table through a preset Internet Protocol address range to generate corresponding organization affiliation information. The calculation unit is used to calculate the username and business type fields of the dirty data through a multi-dimensional data repair rule engine based on the device hardware characteristics, operating system type and matching organization affiliation information; The generation unit is used to generate a standardized data format based on the repaired base data.

7. The apparatus according to claim 6, characterized in that, The filtering unit is also used for: Extracting Internet Protocol Address fields from basic data using regular expressions; Determine if the username field is empty and / or if the business type field is a default value; If the username field is determined to be empty and / or the business type field is set to a default value, then the data is identified as dirty data.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-5.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1-5.

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