A cross-system data synchronization method, system and electronic device

Abstract

The application discloses a cross-system data synchronization method and system and electronic equipment, and relates to the field of company data management and control, and comprises the following steps: S1, based on a preset standard data model, performing structural analysis on to-be-synchronized data by an AI model to generate a mapping table from a source system data structure to the standard data model; S2, according to the mapping table, converting real-time monitored to-be-synchronized data into standard format data, and performing data consistency verification when synchronization is completed; the standard format data is a standard model format based on a data standard model. The AI model identifies data fields and coding rules of the source business system, matches the data fields and the coding rules with standard fields of the standard data model, generates a mapping table from the source system to the standard model, and supports real-time adjustment of the mapping relationship and adaptation of custom fields; wherein the source business system comprises various organization problem management platforms.

Description

Technical Field

[0001] This invention relates to the field of corporate data management, and more particularly to cross-system data synchronization methods, cross-system data synchronization systems, and electronic devices. Background Technology

[0002] As groups expand, they typically divide themselves into multiple independent organizations (such as subsidiaries, business units, and functional departments). Each organization, to meet its own problem management needs, often deploys an independent problem management platform, which has become the mainstream model for problem management in group enterprises. Currently, there are several publicly available data synchronization solutions in the industry. Among these, the solutions closest to this patent fall into three main categories: first, a general cross-platform data fusion solution represented by publication number CN121705271A (Method and System for Cross-Platform Data Access, Fusion and Sharing Based on Metadata Driven); second, a specific system data synchronization solution represented by publication number CN119691044A (Method, System and Electronic Device for Seamless Cross-Platform Data Synchronization in HarmonyOS App Development); and third, a data synchronization solution related to instant messaging office platforms represented by publication number CN115665171A (Data Synchronization Method and Data Synchronization System).

[0003] The aforementioned existing technologies have several shortcomings when applied to multi-organizational problem management scenarios within a group, as detailed below:

[0004] 1. The problem of data silos is prominent: Existing technologies have not designed dedicated data alignment solutions for multi-organizational scenarios within a group. Due to differences in technical architecture and data structure, the problem management platforms deployed independently by each organization cannot achieve automatic interoperability. When collaborating across organizations, problem data needs to be manually entered and transmitted, which not only consumes a lot of manpower but also easily leads to problems such as data entry errors, untimely synchronization, and information omissions, seriously affecting the efficiency of cross-organizational problem handling.

[0005] 2. Poor adaptability: The field mapping relationship of the existing data synchronization solution is fixed and cannot adapt to the personalized fields and business differences of various organizations' issue management platforms. When the platform is upgraded or the fields are changed, secondary development and adjustment are required, resulting in high operation and maintenance costs. At the same time, it cannot adapt to the data storage differences of different organizational platforms (such as big-endian / little-endian storage methods), and manual intervention is required to complete data alignment.

[0006] 3. Fixed and inefficient synchronization strategies: Existing solutions mostly use a single synchronization mode and frequency, which cannot dynamically adjust the synchronization logic according to the priority of the problem and the urgency of the business; although some solutions use incremental synchronization algorithms, they are not optimized in combination with the group's problem management scenario, the synchronization efficiency is greatly affected by network bandwidth, and there is a lack of offline synchronization mechanism, which makes data loss easy.

[0007] 4. Data synchronization is disconnected from office notifications: Existing instant messaging office platform synchronization solutions only focus on the synchronization of the instant messaging office platform's own database or memory, without combining the group's problem management scenario to achieve deep integration of data synchronization and notification to responsible persons. Synchronized data cannot reach the corresponding responsible persons in a timely manner, resulting in delayed problem response and failure to form a closed loop of "synchronization-notification-handling".

[0008] 5. Lack of data security: Existing solutions lack comprehensive hierarchical access control and data encryption mechanisms, which can easily lead to risks such as data leakage and accidental modification during cross-organizational data synchronization, failing to meet the compliance requirements of multi-organizational data management within a group; at the same time, the lack of sensitive data anonymization processing poses a risk of privacy leakage.

[0009] 6. Weak anomaly handling and optimization capabilities: Existing solutions rely heavily on manual anomaly detection, which cannot automatically identify problems such as synchronization failure and data inconsistency, resulting in low anomaly response efficiency; moreover, they lack intelligent optimization mechanisms and cannot automatically optimize synchronization strategies based on synchronization data statistics, requiring frequent manual adjustments and high operation and maintenance costs.

[0010] The core reason for the above problems is that existing data synchronization solutions are mostly general-purpose or designed for specific single scenarios, and do not fully consider the core needs of multi-organizational hierarchical management, multi-platform heterogeneity, business differentiation, and data security compliance within a group. They cannot balance adaptability, security, intelligence, and practicality, resulting in poor application effects in multi-organizational problem management scenarios within a group. Summary of the Invention

[0011] The purpose of this invention is to provide a cross-system data synchronization method, a cross-system data synchronization system, and an electronic device, thereby solving at least one of a number of technical problems.

[0012] Core technical issues include: the "data silo" problem in the group's multi-organization problem management platform; the poor adaptability of existing solutions; the rigidity and inefficiency of synchronization strategies; the disconnect between data synchronization and office notifications; the lack of data security; and the weak ability to handle and optimize anomalies.

[0013] This invention provides the following solution:

[0014] According to a first aspect of the present invention, a cross-system data synchronization method is provided, the cross-system data synchronization method comprising:

[0015] Step S1: Based on the preset standard data model, the AI ​​model is used to perform structural analysis on the data to be synchronized, and a mapping table from the source system data structure to the standard data model is generated.

[0016] Step S2: Based on the mapping table, convert the real-time monitored data to be synchronized into standard format data, and perform data consistency verification synchronously upon completion.

[0017] Standard format data is a standard model format based on the data standard model.

[0018] Furthermore, the AI ​​model is used to perform structural analysis on the data to be synchronized, including:

[0019] The AI ​​model identifies the data fields and encoding rules of the source business system, matches them with the standard fields of the standard data model, generates a mapping table from the source system to the standard model, and supports real-time adjustment of the mapping relationship and adaptation of custom fields.

[0020] The source business systems include the problem management platforms of each organization;

[0021] The data to be synchronized includes: the original data structure obtained by parsing the issue management platforms of various organizations, extracting the field information, data types and business logic of each platform, and the data to be synchronized.

[0022] Furthermore, this includes: hierarchical control of access permissions based on a pre-defined multi-level permission control architecture;

[0023] Based on a pre-defined multi-level permission control architecture, access permissions to the data to be synchronized are controlled hierarchically.

[0024] This includes configuring access and control permissions for all business data across the entire group for group-level users;

[0025] Configure access permissions for subsidiary-level users to access the internal business data of that subsidiary.

[0026] Configure access permissions for department-level users to the corresponding internal business data of that department;

[0027] Configure data read and write permissions for users at the role level, corresponding to their current position.

[0028] Furthermore, this includes: sending notification messages to the relevant task leaders through instant messaging office platforms;

[0029] Based on the ownership information of the synchronization task, match the corresponding operation and maintenance manager and business manager;

[0030] Based on the consistency verification results of the synchronization, generate the corresponding standardized notification template;

[0031] Call the open interface of the office platform to push notification messages to the office platform client of the corresponding person in charge, including pushing notification messages through one-on-one chat or group chat channels.

[0032] Furthermore, it also includes:

[0033] Based on the verification results, a notification message is pushed to the corresponding task manager through the instant messaging office platform, and a second reminder is given if the notification message is not read within the time limit.

[0034] Among them, the read / unread receipt status of notification messages can be queried through the open interface of the office platform;

[0035] When it is detected that the person in charge has not read the notification message within the preset timeout period, a secondary reminder operation will be automatically triggered.

[0036] Furthermore, it also includes:

[0037] Record the operation logs for the entire data synchronization process;

[0038] Operation logs include data access operations, synchronization processing operations, and permission change operations, which are used for compliance auditing and traceability.

[0039] Among these features, real-time monitoring of data changes on the issue management platforms of various organizations is used to capture every data operation and record the data.

[0040] When a data change is detected, the changed data is converted into a standard model format according to the dynamic field mapping table, and the converted data is validated a second time to filter out invalid data.

[0041] The valid data is synchronized to the target organization's issue management platform. After the synchronization is completed, the synchronization log unit automatically records the synchronization log.

[0042] It also includes deploying an offline synchronization queue to cache changed data in offline scenarios.

[0043] Furthermore, it also includes synchronous monitoring and intelligent anomaly handling:

[0044] Real-time monitoring of the entire data synchronization process, automatic identification of synchronization failure, data inconsistency, field mapping anomalies, and network interruptions, and real-time recording of anomaly information;

[0045] Trigger tiered alerts based on the anomaly level and push an anomaly notification to the administrator;

[0046] Among them, when pushing abnormal notifications to administrators, detailed abnormal investigation guidelines are provided;

[0047] It also includes the introduction of a data rollback mechanism, which, when a serious anomaly causes data corruption, performs a data rollback based on the synchronization log to restore the data to its pre-synchronization state.

[0048] It also includes establishing periodic full reconciliation tasks, using Merkle trees to verify the consistency of data across platforms, and generating reconciliation reports to push to administrators.

[0049] Furthermore, this includes AI-powered intelligent optimization and iteration:

[0050] Regularly collect key indicators such as data synchronization efficiency, anomaly rate, and notification reach rate;

[0051] Analyze the bottlenecks in the data synchronization process and provide optimization suggestions;

[0052] Based on the optimization suggestions, intelligent iterative optimization of the synchronization strategy and field mapping relationship is implemented;

[0053] Optimize notification content using AI semantic analysis technology;

[0054] It also includes connecting to the intellectual property management system to automatically synchronize patent-related data, assisting in patent management and plagiarism detection.

[0055] According to a second aspect of the present invention, a cross-system data synchronization system is provided, comprising:

[0056] The data acquisition module is used to acquire data to be synchronized from multiple source business systems;

[0057] The AI ​​alignment module is used to perform structural analysis on the data to be synchronized based on a preset standard data model, and generate a mapping table from the source system data structure to the standard data model.

[0058] The access control module is used to hierarchically control access permissions to data to be synchronized based on a multi-level access control architecture.

[0059] The data synchronization module is used to convert the data to be synchronized into standard format data according to the mapping table, and to perform data consistency verification synchronously upon completion.

[0060] The operations and maintenance notification module is used to push notification messages to the corresponding task managers through an instant messaging office platform based on the verification results, and to provide a second reminder if the notification message is not read within the time limit.

[0061] According to a third aspect of the present invention, an electronic device is provided, comprising: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0062] The memory stores computer programs, which, when executed by the processor, cause the processor to perform steps such as cross-system data synchronization methods.

[0063] The above solution achieves the following beneficial technical effects:

[0064] This invention replaces manual operation with automatic data synchronization, reducing labor costs, lowering data synchronization latency, and significantly improving data synchronization accuracy. It avoids manual input errors and information omissions, and significantly improves the efficiency of cross-organizational problem handling.

[0065] This invention supports custom field adaptation, dynamic adjustment of mapping relationships, and adaptation to different data storage methods. It can adapt to platform upgrades and field changes of various organizations without secondary development, and adapt to the multi-organizational collaboration needs of groups of different sizes, making it more practical.

[0066] This invention reduces network bandwidth usage by combining an optimized incremental synchronization algorithm with multi-level adaptive compression transmission technology; the offline synchronization mechanism avoids data loss; and the AI ​​intelligent optimization module enables automatic iteration of the synchronization strategy, reducing manual intervention and lowering operation and maintenance costs.

[0067] This invention enables precise delivery of notifications to responsible personnel through the multi-dimensional notification function of an instant messaging office platform, significantly improving the notification reach rate. The emergency issue secondary reminder mechanism ensures that the response delay is ≤15 minutes, forming a complete closed loop of "data synchronization - notification reminder - anomaly handling - intelligent optimization", thereby improving the speed of problem response and processing.

[0068] This invention achieves logical isolation of data among different organizations through mechanisms such as TLS 1.3 encrypted transmission, four-level access control, and sensitive data anonymization, thereby preventing data leakage and misoperation. The access operation log supports compliance auditing and meets the group's data management compliance requirements.

[0069] This invention enhances the system's intelligence level through AI field parsing, AI anomaly detection, and AI intelligent optimization. It also supports integration with the group's existing identity authentication system and intellectual property management system, adapting to more group management scenarios and expanding its application scope. Attached Figure Description

[0070] Figure 1 This is a schematic diagram of a data synchronization method flow provided in a specific embodiment of the present invention.

[0071] Figure 2 This is a schematic diagram of the system module structure provided in a specific embodiment of the present invention.

[0072] Figure 3 This is a schematic diagram of an AI data structure alignment process provided in a specific embodiment of the present invention.

[0073] Figure 4 This is a schematic diagram of a multi-dimensional notification process for an instant messaging office platform provided in a specific embodiment of the present invention.

[0074] Figure 5This is a schematic diagram of a hierarchical permission control structure for a four-level architecture of "group-subsidiary-department-role" and the permission scope of each level, provided in a specific embodiment of the present invention.

[0075] Figure 6 This is a flowchart of a cross-system data synchronization method provided by one or more embodiments of the present invention.

[0076] Figure 7 This is a structural diagram of a cross-system data synchronization system provided by one or more embodiments of the present invention.

[0077] Figure 8 This is a block diagram of an electronic device structure for a cross-system data synchronization method provided in one or more embodiments of the present invention. Detailed Implementation

[0078] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0079] Figure 6 This is a flowchart of a cross-system data synchronization method provided by one or more embodiments of the present invention.

[0080] Example 1 Figure 6 The cross-system data synchronization methods shown include:

[0081] The process involves acquiring data to be synchronized from multiple source business systems and then synchronizing this data to the target system. This enables data synchronization between multiple business systems. The specific steps are as follows:

[0082] Step S1: Based on the preset standard data model, the AI ​​model is used to perform structural analysis on the data to be synchronized, and a mapping table from the source system data structure to the standard data model is generated.

[0083] Step S2: Based on the four-level permission control architecture of "Group-Subsidiary-Department-Role", hierarchical control is implemented on the access permissions of the data to be synchronized.

[0084] Step S3: Based on the mapping table, convert the data to be synchronized into standard format data, and perform data consistency verification synchronously upon completion.

[0085] Step S4: Based on the verification results, push notification messages to the corresponding task manager through the instant messaging office platform, and issue a second reminder if the notification message is not read within the time limit.

[0086] Among them, multiple source business systems include the problem management platforms of various organizations;

[0087] The data to be synchronized includes the original data structure obtained by parsing the issue management platforms of various organizations, extracting the field information, data types and business logic of each platform, and the data to be synchronized.

[0088] In this embodiment, the AI ​​model is used to perform structural analysis on the data to be synchronized, including:

[0089] The AI ​​model identifies the data fields and encoding rules of the source business system, matches them with the standard fields of the standard data model, and generates a mapping table from the source system to the standard model. The data fields and encoding rules include field information, data type, and business logic.

[0090] In this embodiment, access permissions are hierarchically controlled based on a four-level permission management architecture of "Group-Subsidiary-Department-Role," including:

[0091] Configure access and control permissions for all business data across the entire group for users at the group level;

[0092] Configure access permissions for subsidiary-level users to access the internal business data of that subsidiary.

[0093] Configure access permissions for department-level users to the corresponding internal business data of that department;

[0094] Configure data read and write permissions for users at the role level, corresponding to their current position.

[0095] In this embodiment, a notification message is pushed to the corresponding task manager through an instant messaging office platform, including:

[0096] Based on the ownership information of the synchronization task, match the corresponding operation and maintenance manager and business manager;

[0097] Based on the consistency verification results of the synchronization, generate the corresponding standardized notification template;

[0098] Call the open interface of the office platform to push notification messages to the office platform client of the corresponding person in charge, including pushing notification messages through one-on-one chat or group chat channels.

[0099] In this embodiment, it also includes:

[0100] By using the open interface of the office platform, query the read / unread receipt status of notification messages;

[0101] When it is detected that the person in charge has not read the notification message within the preset timeout period, a secondary reminder operation will be automatically triggered.

[0102] In this embodiment, it also includes:

[0103] Record the operation logs for the entire data synchronization process;

[0104] The operation log includes data access operations, synchronization processing operations, and permission change operations, which are used for compliance auditing and traceability.

[0105] Figure 7 This is a structural diagram of a cross-system data synchronization system provided by one or more embodiments of the present invention.

[0106] Example 2 Figure 7 The cross-system data synchronization system shown includes:

[0107] The data acquisition module is used to acquire data to be synchronized from multiple source business systems;

[0108] The AI ​​alignment module is used to perform structural analysis on the data to be synchronized based on a preset standard data model, and generate a mapping table from the source system data structure to the standard data model.

[0109] The access control module is used to hierarchically control access permissions to data to be synchronized based on a four-level access control architecture of "group-subsidiary-department-role".

[0110] The data synchronization module is used to convert the data to be synchronized into standard format data according to the mapping table, and to perform data consistency verification synchronously upon completion.

[0111] The operations and maintenance notification module is used to push notification messages to the corresponding task managers through an instant messaging office platform based on the verification results, and to provide a second reminder if the notification message is not read within the time limit.

[0112] Specifically, in this embodiment, the AI ​​alignment module is used for:

[0113] The AI ​​model identifies the data fields and encoding rules of the source business system, automatically matches them with the standard fields of the standard data model, and generates a mapping table from the source system to the standard model.

[0114] In this embodiment, the access control module is specifically used for:

[0115] Configure access and control permissions for all business data across the entire group for users at the group level;

[0116] Configure access permissions for subsidiary-level users to access the internal business data of that subsidiary.

[0117] Configure access permissions for department-level users to the corresponding internal business data of that department;

[0118] Configure data read and write permissions for users at the role level, corresponding to their current position.

[0119] In this embodiment, the operation and maintenance notification module is specifically used for:

[0120] Based on the ownership information of the synchronization task, the corresponding operation and maintenance manager and business manager are automatically matched.

[0121] Based on the consistency verification results of the synchronization, generate the corresponding standardized notification template;

[0122] Call the open interface of the office platform to push notification messages to the office platform client of the corresponding person in charge, including pushing notification messages through one-on-one chat or group chat channels.

[0123] In this embodiment, the operation and maintenance notification module is also used for:

[0124] Query the read / unread receipt status of notification messages through the open interface of the office platform;

[0125] When it is detected that the person in charge has not read the notification message within the preset timeout period, a secondary reminder operation will be automatically triggered.

[0126] In this embodiment, it also includes:

[0127] The audit log module is used to record operation logs throughout the entire data synchronization process;

[0128] The operation log includes data access operations, synchronization processing operations, and permission change operations, which are used for compliance auditing and traceability.

[0129] It is worth noting that although this system / device only discloses the above-mentioned modules / units, it does not mean that this system / device is limited to the above-mentioned basic functional modules. On the contrary, what this invention intends to express is that, based on the above-mentioned basic functional modules, those skilled in the art can add one or more functional modules in combination with the prior art to form an infinite number of embodiments or technical solutions. That is to say, this system is open rather than closed. It cannot be assumed that the scope of protection of the claims of this invention is limited to the above-disclosed basic functional modules just because this embodiment only discloses a few basic functional modules.

[0130] Example 3, in one specific embodiment, discloses a solution for achieving a closed-loop process of data synchronization across multiple organizational problem management platforms within a group by establishing a group-level intelligent data synchronization center and integrating technologies such as AI intelligent optimization, data security isolation, hierarchical access control, and multi-dimensional notifications from instant messaging office platforms. The specific technical solution includes:

[0131] In this embodiment, the technical solution is divided into two parts: a method and a system. The system includes eight core modules, such as... Figure 2As shown: the communication connection and encryption module, the AI ​​data structure alignment module, the intelligent synchronization strategy configuration module, the data synchronization execution module, the multi-dimensional notification module of the instant messaging office platform, the monitoring and intelligent anomaly handling module, the permission hierarchical management module, and the AI ​​intelligent optimization module work together to achieve intelligent, secure, and efficient data synchronization throughout the entire process.

[0132] Example 4, as Figure 1 As shown, the method flow includes:

[0133] Step 1: Establish a group-level intelligent data synchronization center (corresponding to communication connection and encryption modules)

[0134] Deployed in a distributed architecture on the group's private cloud, it establishes encrypted communication connections with the issue management platforms and instant messaging office platform open platforms of various organizations within the group, and obtains interface permissions (data query, change push, write) for each issue management platform and interface permissions (message push, receipt query, session marking) for the instant messaging office platform open platform; it uses the TLS1.3 protocol to achieve end-to-end encryption of data transmission, deploys a link monitoring unit to detect the status of the communication link in real time, and automatically repairs it when interruption occurs.

[0135] The beneficial effects of this step are: the distributed architecture ensures the stability and scalability of the synchronization center, adapting to the concurrent synchronization needs of multiple organizations and platforms within the group; TLS 1.3 encrypted transmission ensures the security of data transmission and avoids data leakage; and the link monitoring and automatic repair mechanism ensures the stability of the communication link, reduces the risk of synchronization interruption, and improves synchronization reliability.

[0136] Step 2: Intelligent alignment configuration of data structures, such as... Figure 3 As shown (corresponding to the AI ​​data structure alignment module)

[0137] 1. Establish a unified group problem data standard model, including core fields such as basic problem information, processing status information, responsible person information, related organization information, priority information, and processing time limit information, while setting up an extended field area to adapt to the personalized needs of each organization;

[0138] 2. Through the AI ​​field parsing module, the original data structure of each organization's issue management platform is automatically parsed, and the field information, data type and business logic of each platform are extracted to generate a dynamic field mapping table. It supports real-time adjustment of mapping relationships and custom field adaptation. Combined with the characteristics of low-code platforms, it supports administrators to manually adjust mapping relationships by dragging and dropping, automatically saves adjustment records and supports rollback viewing.

[0139] 3. A Merkle tree hierarchical structure is used to verify the consistency of data alignment, ensuring the accuracy of the aligned data; the data alignment method is automatically adapted to the differences in data storage on different organizational platforms (such as big-endian / little-endian storage methods) without manual intervention.

[0140] The beneficial effects of this step are: a unified standard model solves the problem of inconsistent data structures across organizational platforms, laying the foundation for data synchronization; AI-powered automatic parsing and dynamic mapping reduce manual intervention and improve data alignment efficiency; custom field adaptation and low-code adjustment methods allow for adaptation to platform upgrades and field changes without secondary development, reducing operational costs; Merkle tree consistency verification ensures accurate data alignment and avoids data format errors; and automatic adaptation to different data storage methods improves system adaptability.

[0141] Step 3: Intelligent configuration of multi-dimensional synchronization strategy (corresponding to the intelligent synchronization strategy configuration module)

[0142] Based on the group's cross-organizational collaboration needs, it configures multi-dimensional synchronization strategies, including synchronization mode (one-way / two-way), synchronization frequency (real-time / timed), synchronization scope (full / incremental), and sets data synchronization conflict resolution rules (timestamp priority / priority priority / manual intervention); it has a built-in AI intelligent recommendation unit that automatically recommends the optimal synchronization strategy based on the group's cross-organizational collaboration scenarios and historical synchronization data, and supports saving, editing and batch application of strategies.

[0143] Incremental synchronization employs a timestamp-based incremental synchronization algorithm optimized based on the characteristics of group problem management data, combined with problem priority weights, to prioritize the synchronization of incremental data for high-priority problems; full synchronization is used for initial synchronization or data anomaly repair scenarios.

[0144] The beneficial effects of this step are: multi-dimensional configurable synchronization strategies adapt to different cross-organizational collaboration scenarios within the group; AI-powered intelligent recommendations reduce administrator configuration costs; and the optimized incremental synchronization algorithm, combined with priority weights, reduces network bandwidth usage while ensuring the timeliness of data synchronization for urgent issues, thus improving synchronization efficiency and usability.

[0145] Step 4: Intelligent execution of data synchronization (corresponding to the data synchronization execution module)

[0146] 1. Through the AI ​​data monitoring module, monitor data changes (additions, modifications, deletions) on the issue management platforms of various organizations in real time, accurately capturing every data operation;

[0147] 2. When a data change is detected, the data conversion unit converts the changed data into the group's standard model format according to the dynamic field mapping table. The format verification unit performs secondary verification on the converted data (including data type, format and business rule verification) and filters out invalid data.

[0148] 3. Based on the configured synchronization strategy, the effective data is synchronized to the target organization's issue management platform. After synchronization is completed, the synchronization log unit automatically records the synchronization log (including synchronization time, content, status, exception information, operator, etc.). The log retention period can be customized, and multi-dimensional queries and Excel export are supported.

[0149] 4. Deploy an offline synchronization queue to cache changed data in offline scenarios. Synchronization will be automatically triggered once the network is restored to avoid data loss. Multi-level adaptive compression transmission technology is adopted to optimize synchronization efficiency and reduce network overhead.

[0150] The beneficial effects of this step are: AI data monitoring ensures that no data changes are missed, secondary verification ensures the accuracy and usability of synchronized data; synchronization logs support traceability and compliance auditing, offline synchronization queues prevent data loss, multi-level compression transmission technology reduces network bandwidth usage, improves synchronization efficiency, and synchronization latency is controlled within 3 seconds.

[0151] Step 5: Instant messaging and office platform pushes multi-dimensional and precise notifications, such as... Figure 4 As shown (corresponding to the multi-dimensional notification module of the instant messaging office platform).

[0152] 1. Extract the person in charge information from the synchronized data and associate it with the person in charge's instant messaging office platform account to ensure accurate matching of notifications;

[0153] 2. Based on the data change type (addition, modification, deletion) and issue priority, the system calls a preset differentiated notification template to generate standardized notification content (including issue ID, name, change content, associated organization, processing time limit, details link, etc.); the notification template supports administrator customization and batch configuration.

[0154] 3. Through the message push interface of the instant messaging office platform open platform, the notification is pushed to the instant messaging office platform account of the corresponding person in charge. At the same time, the conversation is automatically marked by the conversation marking unit, so that the person in charge can quickly locate it.

[0155] 4. The receipt query unit monitors the notification status in real time and provides tiered reminders for unread notifications (a second push is sent after 1 hour for ordinary issues and after 15 minutes for urgent issues); complex cross-organizational issues are automatically copied to relevant supervisory personnel to ensure collaborative processing.

[0156] The beneficial effects of this step are: differentiated templates and precise matching ensure the targeting of notifications; session tagging and detail links improve the efficiency of responsible persons in viewing and processing; tiered secondary reminders ensure that the notification reach rate is ≥99%, avoid delays in problem response, form a seamless connection of "synchronization-notification", and improve the timeliness of cross-organizational problem handling.

[0157] Step 6: Synchronous monitoring and intelligent anomaly handling (corresponding to the monitoring and intelligent anomaly handling module)

[0158] 1. Real-time monitoring of the entire data synchronization process. Through the AI ​​anomaly detection module, it automatically identifies problems such as synchronization failure, data inconsistency, field mapping anomalies, and network interruptions, and records anomaly information (anomaly type, time, content, and platform involved) in real time.

[0159] 2. Trigger tiered alerts based on the severity of the anomaly: Minor anomalies (such as synchronization delays on a single platform) will trigger a notification to the administrator's instant messaging platform; severe anomalies (such as data corruption) will trigger a dual alert of telephone reminder and instant messaging platform notification.

[0160] 3. When pushing anomaly notifications to administrators, provide detailed anomaly troubleshooting guidelines and support manual retry of synchronization operations; introduce a data rollback mechanism so that when a serious anomaly causes data corruption, data rollback can be performed based on the synchronization log to restore the state before synchronization.

[0161] 4. Establish a periodic full reconciliation task (once a month), use Merkle trees to verify the consistency of data across platforms, generate a reconciliation report and push it to the administrator.

[0162] The beneficial effects of this step are: AI anomaly detection enables rapid identification of anomalies, tiered alerts ensure timely response from administrators, anomaly troubleshooting guidance and manual retry function reduce the difficulty of anomaly handling, data rollback and periodic reconciliation ensure data consistency, anomaly handling response time is ≤5 minutes, and system reliability is improved.

[0163] Step 7: Group-level hierarchical access control, such as... Figure 5 As shown (corresponding to the access control module).

[0164] Based on a four-level permission control model of "Group-Subsidiary-Department-Role", the operation permissions and data access permissions of the data synchronization center are configured in a refined manner: the group administrator has full permissions, the administrators of each organization can only manage the synchronization matters of their own organization, the department heads can only view the relevant data of their own department, and ordinary employees can only view the data of the issues they are responsible for; it is integrated with the group's existing identity authentication system to support single sign-on; all permission operation logs are recorded to support compliance auditing; sensitive data is anonymized, and different anonymization rules are configured according to the data type.

[0165] At the same time, the system automatically verifies the rationality of permission configurations periodically, and automatically reminds the administrator to make adjustments when abnormal permission allocation is detected (such as unauthorized access).

[0166] The beneficial effects of this step are: four-level access control achieves logical isolation of data across organizations, preventing data leaks and misoperations; sensitive data is de-identified to protect data privacy; access operation logs and compliance audits meet the group's data management compliance requirements; single sign-on improves operational convenience; and automatic access verification reduces administrator maintenance costs.

[0167] Step 8: AI Intelligent Optimization Iteration (corresponding to the AI ​​Intelligent Optimization module)

[0168] 1. Built-in AI analysis module regularly (once a month) compiles key metrics such as data synchronization efficiency, anomaly rate, and notification reach rate;

[0169] 2. Analyze bottlenecks in the data synchronization process using AI algorithms (such as synchronization delays and abnormal field mappings) and automatically provide optimization suggestions (such as adjusting the synchronization frequency and optimizing field mapping relationships).

[0170] 3. The strategy optimization unit intelligently iterates and optimizes the synchronization strategy and field mapping relationship based on optimization suggestions, without the need for manual adjustment; at the same time, it uses AI semantic analysis technology to optimize the accuracy of notification content, remove redundant information, and improve the response efficiency of the person in charge.

[0171] 4. Connect to the group's intellectual property management system to automatically synchronize patent-related data and assist in patent management and plagiarism detection.

[0172] The beneficial effects of this step are: AI-powered intelligent optimization enables the system to self-iterate, continuously improving synchronization efficiency and adaptability, and reducing operation and maintenance costs; AI semantic analysis optimizes notification content, further improving problem response speed; and it connects to the intellectual property management system, expanding system application scenarios and assisting in patent management.

[0173] The core functions of this embodiment are all implemented through computer software. A distributed synchronization center is built using the Spring Cloud framework, connecting to the API interfaces of various organizational issue management platforms and the open platform SDK of instant messaging office platforms. AI-related functions (field parsing, anomaly detection, and intelligent optimization) are developed using Python, and algorithm training and deployment are implemented based on the TensorFlow framework. Data storage uses a MySQL database, with synchronization logs and permission operation logs stored separately, supporting multi-dimensional querying and export. The front end uses Vue.js to develop a visual configuration interface for administrators to perform operations such as synchronization strategy configuration, permission management, and anomaly handling.

[0174] In this embodiment, the key points are:

[0175] 1. AI Intelligent Data Structure Alignment Technology: Automatically extracts data structures from various platforms through AI field parsing, generates dynamic field mapping tables, supports custom field adaptation, dynamic adjustment of mapping relationships, and automatic adaptation to different data storage methods. Combined with Merkle trees, it realizes data consistency verification, solving the pain point of inconsistent data structures across multiple organizational platforms.

[0176] 2. Multi-dimensional intelligent synchronization strategy: Combined with the group's problem management scenario, the incremental synchronization algorithm is optimized (in combination with priority weights), providing bidirectional / unidirectional, real-time / timed, and full / incremental configurable synchronization modes, with a built-in AI intelligent recommendation unit to adapt to different collaboration scenarios.

[0177] 3. Multi-dimensional and precise closed-loop notification for instant messaging office platforms: Deeply integrate data synchronization with instant messaging office platform notifications to achieve functions such as differentiated templates, tiered secondary reminders, conversation marking, and detailed link jumps, forming a closed loop of "synchronization-notification-receipt-processing" to solve the problems of inaccurate notifications and delayed responses.

[0178] 4. Group-level four-level access control and data security mechanism: Based on the four-level model of "group-subsidiary-department-role", combined with TLS1.3 encrypted transmission, sensitive data anonymization, and access operation logs, data logic isolation and security control are achieved to meet the group's compliance requirements.

[0179] 5. AI Intelligent Optimization and Anomaly Handling: AI anomaly detection enables automatic identification and tiered alarms for synchronous anomalies, a data rollback mechanism ensures data consistency, and AI intelligent optimization enables automatic iteration of synchronous strategies, reducing operation and maintenance costs.

[0180] In this embodiment, the point to be protected is:

[0181] 1. The construction method of the group-level intelligent data synchronization center, including distributed architecture, encrypted communication connection, interface permission acquisition and link monitoring mechanism.

[0182] 2. Implementation methods for AI data structure alignment, including the establishment of a unified standard model, AI field parsing, dynamic mapping table generation, Merkle tree consistency verification, custom field adaptation, and low-code adjustment methods.

[0183] 3. Configuration methods for multi-dimensional synchronization strategies, including the configuration of synchronization mode, frequency, range, conflict resolution rules, and optimized incremental synchronization algorithm (combined with priority weights).

[0184] 4. Methods for implementing multi-dimensional notifications on instant messaging office platforms, including responsible person matching, differentiated template generation, conversation marking, hierarchical secondary reminders, receipt query and details link jump.

[0185] 5. Synchronous monitoring and intelligent anomaly handling methods, including AI anomaly detection, tiered alarms, anomaly troubleshooting guidance, manual retries, data rollback, and periodic reconciliation.

[0186] 6. Implementation of a four-level access control model, including access configuration, single sign-on integration, sensitive data anonymization, access operation logs, and automatic access verification.

[0187] 7. AI-powered intelligent optimization methods, including indicator statistics, bottleneck analysis, automatic strategy iteration, and integration with the group's intellectual property management system.

[0188] In this implementation, the alternative is:

[0189] 1. Alternative for encrypted data transmission: The AES-256 encryption algorithm can be used to replace the TLS1.3 protocol to achieve encrypted data transmission. The same goal of secure data transmission can be achieved. The difference lies in the encryption efficiency and compatibility. The TLS1.3 protocol is more suitable for cross-platform communication in distributed architecture.

[0190] 2. Alternative solution for data consistency verification: A hash check algorithm can be used to replace the Merkle tree hierarchy to achieve consistency verification after data alignment. This can also ensure data accuracy. The difference is that the Merkle tree is more suitable for hierarchical verification of large-scale data and is more efficient.

[0191] 3. Alternative solution for incremental synchronization algorithm: The optimized timestamp incremental synchronization algorithm can be replaced by a log-based incremental synchronization algorithm. Both can achieve incremental data synchronization. The difference is that the log-based algorithm is more suitable for scenarios with frequent data changes, while the timestamp algorithm is more suitable for the synchronization needs of group problem management data.

[0192] 4. Alternative Access Control Solution: A three-level access control model of "Group-Organization-Role" can be used to replace the four-level model. It can also achieve data logic isolation. The difference is that the four-level model is more refined and adapts to the multi-level management needs of the group, while the three-level model is simpler and suitable for small and medium-sized groups.

[0193] 5. AI optimization algorithm alternative: The decision tree algorithm can be used to replace the existing AI analysis algorithm. It can also achieve simultaneous bottleneck analysis and strategy optimization. The difference is that the existing algorithm is more suitable for comprehensive analysis of multi-dimensional indicators and has higher optimization accuracy.

[0194] Figure 8 This is a block diagram of an electronic device structure for a cross-system data synchronization method provided in one or more embodiments of the present invention.

[0195] Example 5, as Figure 8As shown, the present invention provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0196] The memory stores a computer program, which, when executed by a processor, causes the processor to perform steps of a cross-system data synchronization method.

[0197] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not indicate that there is only one bus or one type of bus.

[0198] The electronic device comprises a hardware layer, an operating system layer running on top of the hardware layer, and an application layer running on the operating system. The hardware layer includes hardware such as a central processing unit (CPU), a memory management unit (MMU), and memory. The operating system can be any one or more computer operating systems that control the electronic device through processes, such as Linux, Unix, Android, iOS, or Windows. Furthermore, in this embodiment of the invention, the electronic device can be a smartphone, tablet computer, or other handheld device, or a desktop computer, portable computer, or other electronic device; there is no particular limitation in this embodiment.

[0199] In this embodiment of the invention, the executing entity for electronic device control can be an electronic device itself, or a functional module within an electronic device capable of calling and executing a program. The electronic device can obtain the firmware corresponding to the storage medium. This firmware is provided by the supplier, and different storage media may have the same or different firmware; no limitation is made here. After obtaining the firmware corresponding to the storage medium, the electronic device can write this firmware into the storage medium; specifically, it burns the firmware corresponding to the storage medium into the storage medium. The process of burning the firmware into the storage medium can be implemented using existing technology, and will not be elaborated upon in this embodiment of the invention.

[0200] Electronic devices can also obtain reset commands corresponding to the storage media. The reset commands corresponding to the storage media are provided by the supplier. The reset commands corresponding to different storage media can be the same or different, and no restrictions are imposed here.

[0201] At this time, the storage medium of the electronic device is a storage medium on which the corresponding firmware has been written. The electronic device can respond to the reset command corresponding to the storage medium on which the corresponding firmware has been written, thereby resetting the storage medium on which the corresponding firmware has been written according to the reset command. The process of resetting the storage medium according to the reset command can be implemented by existing technology and will not be described in detail in this embodiment of the invention.

[0202] For ease of description, the above devices are described separately according to their functions, divided into various units and modules. Of course, in implementing this invention, the functions of each unit and module can be implemented in one or more software and / or hardware.

[0203] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined.

[0204] For the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0205] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of the present invention.

[0206] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A cross-system data synchronization method, characterized in that, The cross-system data synchronization method includes: Step S1: Based on the preset standard data model, the AI ​​model is used to perform structural analysis on the data to be synchronized, and a mapping table from the source system data structure to the standard data model is generated. Step S2: According to the mapping table, the real-time monitored data to be synchronized is converted into standard format data, and data consistency verification is performed synchronously upon completion. Standard format data is a standard model format based on the data standard model.

2. The cross-system data synchronization method according to claim 1, characterized in that, The process of using an AI model to perform structural analysis of the data to be synchronized includes: The AI ​​model identifies the data fields and encoding rules of the source business system, matches them with the standard fields of the standard data model, generates a mapping table from the source system to the standard model, and supports real-time adjustment of the mapping relationship and adaptation of custom fields. The source business systems include the problem management platforms of each organization; The data to be synchronized includes: the original data structure obtained by parsing the issue management platforms of various organizations, extracting the field information, data types and business logic of each platform, and the data to be synchronized.

3. The cross-system data synchronization method according to claim 1, characterized in that, include: Access permissions are controlled hierarchically based on a pre-defined multi-level permission management architecture; Based on a preset multi-level permission control architecture, the access permissions of the data to be synchronized are controlled hierarchically. This includes configuring access and control permissions for all business data across the entire group for group-level users; Configure access permissions for subsidiary-level users to access the internal business data of that subsidiary. Configure access permissions for department-level users to the corresponding internal business data of that department; Configure data read and write permissions for users at the role level, corresponding to their current position.

4. The cross-system data synchronization method according to claim 1, characterized in that, include: Send notification messages to the relevant task manager through an instant messaging office platform; Based on the ownership information of the synchronization task, match the corresponding operation and maintenance manager and business manager; Based on the consistency verification results of the synchronization, generate the corresponding standardized notification template; Call the open interface of the office platform to push notification messages to the office platform client of the corresponding person in charge, including pushing notification messages through one-on-one chat or group chat channels.

5. The cross-system data synchronization method according to claim 4, characterized in that, Also includes: Based on the verification results, a notification message is pushed to the corresponding task manager through the instant messaging office platform, and a second reminder is given if the notification message is not read within the time limit. Among these features, the read / unread receipt status of the notification message can be queried through the open interface of the office platform; When it is detected that the person in charge has not read the notification message within the preset timeout period, a secondary reminder operation will be automatically triggered.

6. The cross-system data synchronization method according to claim 1, characterized in that, Also includes: Record the operation logs for the entire data synchronization process; The operation log includes data access operations, synchronization processing operations, and permission change operations, which are used for compliance auditing and tracing. Among these features, real-time monitoring of data changes on the issue management platforms of various organizations is used to capture every data operation and record the data. When a data change is detected, the changed data is converted into a standard model format according to the dynamic field mapping table, and the converted data is validated a second time to filter out invalid data. The valid data is synchronized to the target organization's issue management platform. After the synchronization is completed, the synchronization log unit automatically records the synchronization log. It also includes deploying an offline synchronization queue to cache changed data in offline scenarios.

7. The cross-system data synchronization method according to claim 1, characterized in that, It also includes synchronous monitoring and intelligent anomaly handling: Real-time monitoring of the entire data synchronization process, automatic identification of synchronization failure, data inconsistency, field mapping anomalies, and network interruptions, and real-time recording of anomaly information; Trigger tiered alerts based on the anomaly level and push an anomaly notification to the administrator; Among them, when pushing abnormal notifications to administrators, detailed abnormal investigation guidelines are provided; It also includes the introduction of a data rollback mechanism, which, when a serious anomaly causes data corruption, performs a data rollback based on the synchronization log to restore the data to its pre-synchronization state. It also includes establishing periodic full reconciliation tasks, using Merkle trees to verify the consistency of data across platforms, and generating reconciliation reports to push to administrators.

8. The cross-system data synchronization method according to claim 1, characterized in that, It also includes AI-powered intelligent optimization and iteration: Regularly collect key indicators such as data synchronization efficiency, anomaly rate, and notification reach rate; Analyze the bottlenecks in the data synchronization process and provide optimization suggestions; Based on the optimization suggestions, intelligent iterative optimization of the synchronization strategy and field mapping relationship is implemented; Optimize notification content using AI semantic analysis technology; It also includes connecting to the intellectual property management system to automatically synchronize patent-related data, assisting in patent management and plagiarism detection.

9. A cross-system data synchronization system, characterized in that, The cross-system data synchronization system includes: The data acquisition module is used to acquire data to be synchronized from multiple source business systems; The AI ​​alignment module is used to perform structural analysis on the data to be synchronized based on a preset standard data model and generate a mapping table from the source system data structure to the standard data model. The access control module is used to hierarchically control the access permissions of the data to be synchronized based on a multi-level access control architecture. The data synchronization module is used to convert the data to be synchronized into standard format data according to the mapping table, and to perform data consistency verification synchronously upon completion. The operations and maintenance notification module is used to push notification messages to the corresponding task managers through an instant messaging office platform based on the verification results, and to provide a second reminder if the notification message is not read within the time limit.

10. An electronic device, characterized in that, include: The processor, communication interface, memory, and communication bus are connected, with the processor, communication interface, and memory communicating with each other via the communication bus. The memory stores a computer program that, when executed by a processor, causes the processor to perform the steps of the cross-system data synchronization method as described in any one of claims 1 to 8.

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