Distributed architecture enterprise information management system

Abstract

The invention relates to the technical field of information management, in particular to a distributed architecture enterprise information management system which comprises an information system processing unit and an enterprise system monitoring unit. The information system processing unit is used for upgrading and maintaining the enterprise management system, so that enterprise system information is transmitted to the enterprise system monitoring unit; old data in the system is upgraded and replaced through the information upgrading module, the data in the old system is imported into the new system, the data in the new system is managed in a unified mode through the data management module, the integration of the data is improved, public data, hardware and business processes in an enterprise are integrated through the system integration module, and the system integration efficiency is improved. The enterprise business processing and sharing are facilitated, the data sharing module can reduce the similar data reported repeatedly, so that an enterprise manager can find the data accurately, and the maintenance detection module can sort the uploaded data flow to realize partial data sharing and partial data encryption.

Description

Technical Field

[0001] The present invention relates to the technical field of information management, and in particular to a distributed architecture enterprise information management system. Background Art

[0002] Enterprise Information Management (EIM) under distributed architecture refers to the strategies and practices of managing and integrating enterprise data and information in a decentralized, multi-node IT environment. This architecture allows multiple systems and databases to run in different locations, communicate and share data through the network, thereby providing flexibility, scalability and fault tolerance.

[0003] However, there are still some shortcomings in its actual use. Since many systems are not functionally related to each other, information is not shared, and they are disconnected from business processes, it often leads to information island problems in the enterprise. The enterprise system cannot be managed collaboratively, and when a failure occurs, it is impossible to quickly discover the system's potential failures or quickly locate the cause of the failure.

[0004] In summary, developing a distributed architecture enterprise information management system is still a key issue that needs to be urgently addressed in the field of information management technology. Summary of the invention

[0005] In view of the above shortcomings of the prior art, the present invention provides a distributed architecture enterprise information management system. The present invention upgrades and replaces the old data in the system through the information upgrade module, and imports the data in the old system into the new system. The data management module uniformly manages the data in the new system to improve the integration of the data. The public data, hardware and business outflows in the enterprise are integrated through the system integration module to facilitate the processing and sharing of enterprise business. The data sharing module can reduce the repeated reporting of similar data, automatically classify and process the information data imported by the enterprise, and solve some mechanical and cumbersome affairs. Before the next step of deep processing of data, the information data that has been preliminarily processed is replaced. The enterprise personnel can freely choose according to the current situation, so that the enterprise manager can accurately find the data. The maintenance and detection module can sort out the uploaded data stream to realize partial data sharing and partial data encryption. The data information monitoring module can supervise the data and set a security baseline. The security baseline can timely discover data vulnerabilities and perform timely automatic repairs to improve data security and prevent data leakage. The system virus monitoring module can protect enterprise data information, intercept system viruses, and prevent the loss of enterprise commercial secrets.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The present invention provides a distributed architecture enterprise information management system, comprising the following steps: an information system processing unit and an enterprise system monitoring unit;

[0008] The information system processing unit is used to upgrade and maintain the enterprise management system, so that the enterprise system information is transmitted to the enterprise system monitoring unit;

[0009] The enterprise system monitoring unit is used to receive enterprise system information and perform information system maintenance on the enterprise information. The information system maintenance includes software maintenance and hardware maintenance. The enterprise system monitoring unit is connected to the information system processing unit.

[0010] The present invention is further configured as follows: the information system processing unit includes an information upgrade module, a data management module, a system integration module, a data sharing module and a maintenance detection module.

[0011] The present invention is further configured as follows: the information upgrade module is used to upgrade the data of the new and old systems; the inconsistent business data in the business system is standardized with reference to the industry data standard specification requirements, a data standard center is formed, and the standard data is centrally and standardizedly managed;

[0012] The data management module is used to maintain and integrate the upgraded system data, and the data management module is connected to the information upgrade module.

[0013] The present invention is further configured as follows: the system integration module is used to integrate the public data, hardware and business processes in the enterprise, and extract the data inside the system data integration module. During the extraction process, the number of key information items is G, multiple G items are selected, and the two data items with the largest difference are used as vector data, and the difference is used as the data space distance. The calculation formula is: Among them U 1 Represents vector data 1, U 2 represents vector data 2, δ represents a vector, and |U 1 -U 2 |As a reference, calculate the correlation dimension of key information. The calculation formula is: Wherein L represents the key dimension of key information, n represents the vector logarithm, Y represents the correlation integral, and i represents the number of crawlers. After completing the above calculation, data extraction is performed according to the correlation between data information, and the master data is standardized, centralized, and normalized to promote the master data to maintain a unified name and unified coding between business systems. The system integration module is connected to the data management module;

[0014] The data sharing module is used to reduce repeated reporting of similar data. The repetition rate calculation formula is: This formula can be used to calculate the proportion of repeated data in a data set, where C represents the repetition rate, c represents the number of repeated data, and z represents the total number of data.

[0015] The accuracy calculation formula is: This formula can be used to calculate the proportion of non-repeated data in a data set, where J represents precision and c represents 1 Indicates the number of repeated data, z 1 Indicates the total amount of data;

[0016] The data sharing module is connected to the system integration module. The data sharing module automatically classifies and processes the information data imported by the enterprise to solve some mechanical and tedious tasks. Before proceeding to the next step of deep data processing, the module replaces the preliminarily processed information data, and the enterprise personnel can freely choose according to the current situation.

[0017] The present invention is further configured as follows: the maintenance detection module is used to sort out the shared data and classify the shared data into branch node blocks;

[0018] The formula for calculating data content complexity is: Among them, Fzd(A 1 ,A 2 ) represents the complexity, |H| represents the number of matching pairs of child nodes, A 1 ,A 2 Represents the child nodes in the branch, according to Fzd(A 1 ,A 2 ) Calculate the results or number of child nodes to understand the complexity of the data content;

[0019] The weight calculation formula is: Where Q represents the feature information weight, Q 0 represents the initialization node, s represents the number of samples, P represents the minimum feature, J represents the matrix equation, J 0 It represents the matrix initialization parameter value. According to the above method, the weights of different feature information are mastered to realize big data feature recognition, unified registration, configuration and security management of shared data, and data sharing and intercommunication between business systems are realized to solve the current situation of numerous smoke pipes between business systems. The maintenance detection module is connected to the data sharing module.

[0020] The present invention is further configured as follows: the enterprise system monitoring unit includes data information monitoring and system virus monitoring.

[0021] The present invention is further configured as follows: the data information monitoring is used to supervise the environment for data release and set a security baseline.

[0022] The present invention is further configured as follows: the system virus monitoring is used to intercept network viruses, and the system virus monitoring is connected with data information monitoring.

[0023] Beneficial Effects

[0024] Compared with the known public technology, the technical solution provided by the present invention has the following advantages:

[0025] Beneficial effects:

[0026] The present invention upgrades and replaces the old data in the system through the information upgrade module, and imports the data in the old system into the new system. The data management module uniformly manages the data in the new system to improve the integration of the data. The public data, hardware and business processes in the enterprise are integrated through the system integration module to facilitate the processing and sharing of enterprise business. The data sharing module can reduce the repeated reporting of similar data, automatically classify and process the information data imported by the enterprise, and solve some mechanical and cumbersome affairs. Before the next step of deep processing of data, the preliminarily processed information data is replaced. Enterprise personnel can freely choose according to the current situation, so that enterprise managers can find data accurately. The maintenance and detection module can sort out the uploaded data stream to realize partial data sharing and partial data encryption. The data information monitoring module can supervise the data and set a security baseline. The security baseline can timely discover data vulnerabilities and perform timely automatic repairs to improve data security and prevent data leakage. The system virus monitoring module can protect enterprise data information, intercept system viruses, and prevent the loss of enterprise business secrets. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A system diagram of a distributed architecture enterprise information management system of the present invention;

[0028] Figure 2 This is a system diagram of an information system processing unit in a distributed architecture enterprise information management system of the present invention;

[0029] Figure 3 This is a system diagram of an enterprise system monitoring unit in a distributed architecture enterprise information management system of the present invention;

[0030] Figure 4 The present invention is a flow chart of a distributed architecture enterprise information management system.

[0031] Description of the numbers in the figure:

[0032] 1. Information system processing unit; 101. Information upgrade module; 102. Data management module; 103. System integration module; 104. Data sharing module; 105. Maintenance and detection module; 2. Enterprise system monitoring unit; 201. Data information monitoring module; 202. System virus monitoring module. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] The present invention will be further described below in conjunction with the embodiments.

[0035] Embodiment 1:

[0036] The present invention provides a distributed architecture enterprise information management system, comprising the following steps: an information system processing unit 1 and an enterprise system monitoring unit 2; the information system processing unit 1 is used to upgrade and maintain the enterprise management system, so that the enterprise system information is transmitted to the enterprise system monitoring unit 2; the enterprise system monitoring unit 2 is used to receive the enterprise system information and perform information system maintenance on the enterprise information, the information system maintenance includes software maintenance and hardware maintenance, and the enterprise system monitoring unit 2 is connected to the information system processing unit 1.

[0037] In this embodiment, the information system processing unit 1 and the enterprise system monitoring unit 2 are connected to monitor the data of the information management system in real time. Through the enterprise system monitoring unit, the data can be protected in time to prevent viruses in the system from causing confidential information leakage and affecting enterprise information management.

[0038] Further: the information system processing unit 1 includes an information upgrade module 101, a data management module 102, a system integration module 103, a data sharing module 104 and a maintenance detection module 105; the information upgrade module 101 is used to upgrade the old and new system data, standardize the inconsistent business data in the business system with reference to the industry data standard specification requirements, form a data standard center, and centrally and standardizedly manage the standard data; the data management module 102 is used to maintain and integrate the upgraded system data, and the data management module 102 is connected to the information upgrade module 101; the system integration module 103 is used to integrate the public data, hardware and business processes in the enterprise, and extract the data inside the system data integration module 103. During the extraction process, the number of key information items is G, multiple G items are selected, and the two data with the largest difference are used as vector data, and the difference is used as the data space distance. The calculation formula is: Among them U 1 Represents vector data 1, U 2 represents vector data 2, δ represents a vector, and |U 1 -U 2 |As a reference, calculate the correlation dimension of key information. The calculation formula is: Wherein L represents the key dimension of key information, n represents the vector logarithm, Y represents the correlation integral, and i represents the number of crawlers. After completing the above calculation, data extraction is performed according to the correlation between data information, and the master data is standardized, centralized, and normalized to promote the master data to maintain a unified name and unified coding between business systems. The system integration module 103 is connected to the data management module 102; the data sharing module 104 is used to reduce the repeated reporting of the same type of data, and the repetition rate calculation formula is: This formula can be used to calculate the proportion of repeated data in a data set, where C represents the repetition rate, c represents the number of repeated data, and z represents the total number of data.

[0039] The accuracy calculation formula is: This formula can be used to calculate the proportion of non-repeated data in a data set, where J represents precision and c represents 1 Indicates the number of repeated data, z 1 Indicates the total amount of data, the data sharing module 104 is connected to the system integration module 103; the maintenance detection module 105 is used to sort out the shared data and classify the shared data into branch node blocks;

[0040] The formula for calculating data content complexity is: Among them, Fzd(A 1 ,A 2 ) represents the complexity, |H| represents the number of matching pairs of child nodes, A 1 ,A 2 Represents the child nodes in the branch, according to Fzd(A 1 ,A 2 ) Calculate the results or number of child nodes to understand the complexity of the data content;

[0041] The weight calculation formula is: Where Q represents the feature information weight, Q 0 represents the initialization node, s represents the number of samples, P represents the minimum feature, J represents the matrix equation, J 0 It represents the matrix initialization parameter value. According to the above method, the weights of different feature information are mastered to realize big data feature recognition, unified registration, configuration and security management of shared data, data sharing and intercommunication between business systems are realized, the current situation of numerous smoke pipes between business systems is solved, and the connection between the maintenance detection module 105 and the data sharing module 104 is maintained.

[0042] In this embodiment, the old data in the system is upgraded and replaced through the information upgrade module, and the data in the old system is imported into the new system. The data management module uniformly manages the data in the new system to improve the integration of the data. The public data, hardware and business processes in the enterprise are integrated through the system integration module to facilitate the processing and sharing of enterprise business. The data sharing module can reduce the repeated reporting of similar data, automatically classify and process the information data imported by the enterprise, and solve some mechanical and cumbersome affairs. Before the next step of deep processing of the data, the preliminarily processed information data is replaced. The enterprise personnel can freely choose according to the current situation, so that the enterprise managers can accurately find the data. The maintenance and detection module can sort out the uploaded data stream to realize partial data sharing and partial data encryption.

[0043] Further: the enterprise system monitoring unit 2 includes a data monitoring module 201 and a system virus monitoring module 202; the data monitoring module 201 is used to supervise the data publishing environment and set a security baseline; the system virus monitoring module 202 is used to intercept network viruses, and the system virus monitoring module 202 is connected to the data monitoring module 201.

[0044] In this embodiment, the data information monitoring module can supervise the data and set a security baseline. The security baseline can promptly discover data loopholes and perform timely automatic repairs instead of manual repairs. It can promptly prevent and handle information security, improve data security and prevent data leakage. The system virus monitoring module can protect enterprise data information, intercept system viruses, and prevent the loss of enterprise business secrets.

[0045] The method to solve the information island problem of information management system is to first upgrade the data in the existing system that has lost the ability to maintain continuous maintenance and has no maintenance significance, or replace the old system with a new system, and then transfer the data generated by the old system to the new system. This can ensure that the data in the old and new systems are preserved intact and not easily lost. Then formulate the basic data specifications of the enterprise, establish a unified database management system and implement maintenance; at the same time, carry out data integration, integrate the business data that can be integrated, maximize data sharing, and combine the enterprise's public data, application software, business processes and other information data through integration technology, and achieve seamless integration between different enterprise application systems, so that they can process business and share information as a whole. Establish a data sharing system. In enterprises, the same type of data is often reported repeatedly. When summarizing data, superior users often have multiple sources of data, resulting in inconsistent statistical results. As a result, enterprise managers are unable to obtain accurate data. Therefore, refer to the industry data standards and specifications to standardize the inconsistent business data in the business system, form a data standard center, centrally and standardize the management of standard data, and formulate effective prevention strategies to avoid information islands. When formulating information plans, information islands should be avoided as much as possible, and the data flow of the enterprise should be straightened out to ensure that some data needs to be shared between departments, and some data needs to be reported to the leaders of each enterprise, etc., and then sort out and optimize the original business processes from a business perspective, and determine the key business nodes.

[0046] To solve the problem of enterprise information data security, when enterprises exchange information, they should use the Internet to transmit data in a timely manner. The existing local networks of many enterprises are relatively complete, and they need to rent dedicated DDN lines to access the Internet via optical fiber. This type of server is located in the local network and is protected by the enterprise network firewall that acts as an anti-virus and IP filter. The enterprise installs anti-virus software on the client to prevent viruses from entering. In this process, even if the enterprise intercepts the communication information, the use of keys to encrypt the transmitted data will not lead to the loss of corporate business secrets. At this time, the system can grant different permissions to different users, different functions and different data, thereby effectively improving the security performance of the system and effectively preventing unauthorized operations and corporate data loss.

[0047] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A distributed architecture enterprise information management system, It is characterized in that include: An information system processing unit (1) and an enterprise system monitoring unit (2); The information system processing unit (1) is used to upgrade and maintain the enterprise management system, so that the enterprise system information is transmitted to the enterprise system monitoring unit (2); The enterprise system monitoring unit (2) is used to receive enterprise system information and perform information system maintenance on the enterprise information. The information system maintenance includes software maintenance and hardware maintenance. The enterprise system monitoring unit (2) is connected to the information system processing unit (1).

2. A distributed architecture enterprise information management system according to claim 1, It is characterized in that The information system processing unit (1) comprises an information upgrading module (101), a data management module (102), a system integration module (103), a data sharing module (104) and a maintenance detection module (105).

3. A distributed architecture enterprise information management system according to claim 1, It is characterized in that The information upgrade module (101) is used to upgrade the new and old system data; The data management module (102) is used to maintain and integrate the upgraded system data, and the data management module (102) is connected to the information upgrade module (101).

4. A distributed architecture enterprise information management system according to claim 1, It is characterized in that The system integration module (103) is used to integrate the public data, hardware and business processes in the enterprise, and extract the data inside the system data integration module (103). During the extraction process, the number of key information items is G, and multiple G items are selected. The two data items with the largest difference are used as vector data, and the difference is used as the data space distance. The calculation formula is: Among them U 1 Represents vector data 1, U 2 represents vector data 2, δ represents a vector, and |U 1 -U 2 |As a reference, calculate the correlation dimension of key information. The calculation formula is: Where L represents the key dimension of key information, n represents the vector logarithm, Y represents the correlation integral, and i represents the number of crawlers. After completing the above calculations, data extraction is performed based on the correlation between data information; The system integration module (103) is connected to the data management module (102); The data sharing module (104) is used to reduce repeated reporting of the same type of data, and the repetition rate calculation formula is: This formula can be used to calculate the proportion of repeated data in a data set, where C represents the repetition rate, c represents the number of repeated data, and z represents the total number of data. The accuracy calculation formula is: This formula can be used to calculate the proportion of non-repeated data in a data set, where J represents precision and c represents 1 Indicates the number of repeated data, z 1 Indicates the total amount of data; The data sharing module (104) is connected to the system integration module (103).

5. A distributed architecture enterprise information management system according to claim 1, It is characterized in that The maintenance detection module (105) is used to sort out the shared data and classify the shared data into branch node blocks; The formula for calculating data content complexity is: Among them, Fzd(A 1 ,A 2 ) represents the complexity, |H| represents the number of matching pairs of child nodes, A 1 ,A 2 Represents the child nodes in the branch, according to Fzd(A 1 ,A 2 ) Calculate the results or number of child nodes to understand the complexity of the data content; The weight calculation formula is: Where Q represents the feature information weight, Q 0 represents the initialization node, s represents the number of samples, P represents the minimum feature, J represents the matrix equation, J 0 Indicates the matrix initialization parameter value. According to the above method, the weights of different feature information are mastered to realize big data feature recognition; The maintenance detection module (105) is connected to the data sharing module (104).

6. A distributed architecture enterprise information management system according to claim 1, It is characterized in that The enterprise system monitoring unit (2) comprises a data information monitoring module (201) and a system virus monitoring module (202).

7. A distributed architecture enterprise information management system according to claim 1, It is characterized in that The data information monitoring module (201) is used to monitor the environment for data release and set a security baseline.

8. A distributed architecture enterprise information management system according to claim 1, It is characterized in that The system virus monitoring module (202) is used to intercept network viruses, and the system virus monitoring module (202) is connected to the data information monitoring module (201).

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