Enterprise archive informatization intelligent management system based on big data

Abstract

The invention discloses an enterprise archive informatization intelligent management system based on big data. The system comprises a data acquisition module which is used for acquiring enterprise archive data from each business system in an enterprise and an external data source; relates to the technical field of archive management, complete enterprise archive data are split into multiple pieces of fragmented archive information data, and the fragmented archive information data are classified and stored by a fragmented archive information data classification storage module, so that the fragmented archive information data can be directly mined and processed subsequently, and the archive management efficiency is improved. During transmission, small data of a plurality of pieces of fragmented archive information data is beneficial to stable transmission; when a user initiates a request for generating enterprise archive data, a first-level authority user can directly retrieve all fragmented archive information data and generate a complete archive, and a second-level authority user can generate an archive independently or in a combined mode. Users with different permissions can conveniently obtain required archives, and enterprise archive data can be flexibly recovered.

Description

Technical Field

[0001] The present invention relates to the technical field of archive management, and in particular to an enterprise archive information intelligent management system based on big data. Background Art

[0002] With the rapid development of information technology and the advent of the big data era, the amount of data generated in the operation of enterprises has exploded. As a carrier of key information such as business activities, management decisions, and operating results of enterprises, the management of enterprise archives faces unprecedented challenges and opportunities.

[0003] Publication No. CN117453982B discloses an archive management file classification system. The archive management and audit module includes archive classification. Archive classification introduces natural language processing technology and machine learning technology to classify and catalog archives according to the attributes and contents of the archives.

[0004] However, the above application still has the following problems: its storage method is to store a complete corporate archive, which is also the current mainstream corporate archive storage method. Currently, a complete corporate archive is often kept and circulated as a whole. On the one hand, this method has a huge amount of data in the complete archive, and it is very easy to cause interruptions, jams, or even transmission failures during the transmission process due to factors such as network fluctuations and bandwidth limitations; on the other hand, due to the complex content of the complete archive, it is not conducive to subsequent data mining and analysis operations. Summary of the invention

[0005] In order to solve the problem that in the current enterprise archive management, a complete enterprise archive is kept and circulated as a whole, resulting in a huge amount of complete archive data that is difficult to transmit, and the complete archive content is complicated, which is not conducive to subsequent data mining and analysis operations, the present invention proposes an enterprise archive information intelligent management system based on big data.

[0006] The present invention proposes an enterprise archive information intelligent management system based on big data, comprising: Data collection module: used to collect enterprise archive data from various business systems within the enterprise and external data sources; Data transfer module: The data acquisition module transmits the enterprise archive data to the data transfer module through wireless transmission. The data transfer module is used to store the enterprise archive data collected by the data acquisition module; Archive information fragmentation and marking module: used to split each complete enterprise archive data in the data transfer module, split a complete enterprise archive data into multiple fragmented archive information data according to the preset fragmentation rules, and associate and mark each fragmented archive information data in a complete enterprise archive data; Fragmented archive information data classification storage module: used to classify and store multiple fragmented archive information data, and each fragmented archive information data of a complete enterprise archive data corresponds to a classification; User authority module: used to authorize user authority, which includes primary authority and secondary authority; Among them, a first-level permission is used to retrieve all fragmented archive information data of all categories in the fragmented archive information data classification storage module; A secondary permission is used to retrieve all fragmented archive information data of a category in the fragmented archive information data classification storage module; Archive information generation module: retrieves the fragmented archive information data in the fragmented archive information data classification storage module according to the user authority provided by the user authority module, and is used to retrieve one or more fragmented archive information data with associated tags to generate an enterprise archive.

[0007] Preferably, in the archive information generation module, when a user initiates a request to generate an enterprise archive data; If the user has the first-level authority, he can directly retrieve all the fragmented archival information data related to the enterprise archival data, and generate a complete enterprise archival data based on the association tags of the fragmented archival information data; If the user has the second-level authority, a fragmented archival information data related to the enterprise archival data is retrieved from the category in the fragmented archival information data classification storage module, and an enterprise archival data is directly generated from the related fragmented archival information data; When it is necessary to restore a more complete or complete archive information data through a combination of multiple secondary permissions, first, within a set time, multiple users with secondary permissions respectively initiate retrieval requests for fragmented archive information within their authority ranges, and respectively obtain corresponding fragmented archive information data, thereby obtaining multiple fragmented archive information data, and generating an enterprise archive data based on the association tags of the multiple fragmented archive information data; If some users with second-level permissions do not initiate a request to retrieve the fragmented archival information data within their authority within the set time, the generation of enterprise archival data this time will only generate the enterprise archival data of the fragmented archival information data for which a retrieval request was issued within the set time.

[0008] Preferably, it also includes: Relevance analysis module: used to analyze the relevance of fragmented archive information data in the fragmented archive information data classification storage module; Follow-up display module: In the enterprise archive data generated by the archive information generation module, according to the relevance of the fragmented archive information data in the association analysis module, the associated fragmented archive information data whose relevance meets the set threshold are displayed together in the generated enterprise archive data.

[0009] Preferably, in the association analysis module, the association analysis is as follows: Assume that each fragmented archive information data has several attributes for analyzing the association; Assume that the fragmented archive information data set is , where n is the total number of fragmented archive information data; For each fragmented archive information data , k=1,2,...,n, there are m attributes to describe it, Suppose the vector composed of m attributes is ; For any two fragmented archive information data and , i ≠ j, their attribute vectors and The Euclidean distance is: ; Their attribute similarity for: .

[0010] Preferably, in the follow-up display module, the set threshold of the correlation is 0.8, that is, the attribute similarity of the two fragmented archive information data is greater than or equal to 0.8.

[0011] Preferably, in the data collection module, the enterprise archives include: employee personnel archives, sales archives, administrative management archives, financial archives, production archives, and R&D archives.

[0012] Preferably, in the archive information fragmentation and marking module, the associated marking content includes: enterprise basic information identifier, archive subject classification code, project number or contract number, department code or department name, and sequential number.

[0013] A method for intelligent management of enterprise archives information based on big data, comprising the following steps: S1, the data collection module is used to collect enterprise archive data from various business systems within the enterprise and external data sources, and transmit the collected enterprise archive data to the data transfer module in real time through wireless transmission. The data transfer module centrally stores the data to form a data cache pool; S2, the archive information fragmentation and marking module extracts the complete enterprise archive data from the data transfer module, and splits a complete archive into multiple fragmented archive information data according to the preset fragmentation rules; S3, associate and mark each fragmented archival information data in a complete enterprise archival data, wherein the associated mark content includes the enterprise basic information identifier, archival subject classification code, project number or contract number, department code or department name, and sequence number; S4, the fragmented archive information data classification storage module classifies and stores the fragmented archive information data; S5. The user authority module grants the user a first-level authority or a second-level authority, wherein a first-level authority is used to retrieve all fragmented archival information data of all categories in the fragmented archival information data classification storage module; a second-level authority is used to retrieve all fragmented archival information data of one category in the fragmented archival information data classification storage module; S6. When a user initiates a request to generate enterprise archive data: If the user has the first-level authority, he can directly retrieve all the fragmented archival information data related to the enterprise archival data, and generate a complete enterprise archival data based on the association tags of the fragmented archival information data; If the user has the second-level authority, a fragmented archival information data related to the enterprise archival data is retrieved from the category in the fragmented archival information data classification storage module, and an enterprise archival data is directly generated from the related fragmented archival information data; When it is necessary to restore a more complete or complete archive information data through a combination of multiple secondary permissions, first, within a set time, multiple users with secondary permissions respectively initiate retrieval requests for fragmented archive information within their authority ranges, and respectively obtain corresponding fragmented archive information data, thereby obtaining multiple fragmented archive information data, and generating an enterprise archive data based on the association tags of the multiple fragmented archive information data; If some users with second-level permissions do not initiate a request to retrieve the fragmented archival information data within their authority within the set time, the generation of enterprise archival data this time will only generate the enterprise archival data of the fragmented archival information data that issued the retrieval request within the set time; S7, the association analysis module is used to analyze the association of the fragmented archive information data in the fragmented archive information data classification storage module; S8. In the follow-up display module, in the enterprise archive data generated by the archive information generation module, according to the relevance of the fragmented archive information data in the association analysis module, the associated fragmented archive information data whose relevance meets the set threshold is displayed together in the generated enterprise archive data.

[0014] In the present invention, the proposed enterprise archives information intelligent management system based on big data has the following beneficial technical effects: 1. By splitting a complete enterprise archive data into fragmented archive information data one by one and storing them in a fragmented archive information data classification storage module, the fragmented archive information data classification storage module classifies and stores multiple fragmented archive information data, which is conducive to the subsequent direct mining and processing of the fragmented archive information data, and during transmission, the big data of a complete enterprise archive data is dispersed into multiple small data of fragmented archive information data, which is conducive to the stable transmission; 2. When a user initiates a request to generate enterprise archive data, there are different ways to generate it according to different user permissions. Level 1 users can directly retrieve all fragmented archive information data and generate a complete archive, and level 2 users can generate archives individually or in combination. This method not only facilitates users with different permissions to obtain the required archives, but also allows for the flexibility to restore complete archives while ensuring data security.

[0015] 3. When a user initiates a request to generate enterprise archive data, if some users with second-level permissions do not initiate a request to retrieve the fragmented archive information data within their authority within the set time, the generation of the enterprise archive data this time will only generate the enterprise archive data of the fragmented archive information data for which the retrieval request was issued within the set time. This is beneficial when personnel from different business units need to integrate and restore the entire picture of the same project and business archives, prompting all parties to contribute fragmented information within a limited time, strengthening the linkage and cooperation between departments, and even if some personnel do not respond, they can generate partially available archives based on the existing data, reducing work delays due to missing archives and improving the efficiency of collaborative office work within the enterprise.

[0016] 4. The correlation analysis module analyzes the correlation of the fragmented archive information data, and the follow-up display module displays the related fragmented archive information data that meets the set threshold in the generated enterprise archive according to the correlation. This helps users obtain more comprehensive and valuable archive information, not limited to the acquisition of permissions.

[0017] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a principle block diagram of the system of the present invention; Figure 2 Flow chart of the method of the present invention. DETAILED DESCRIPTION

[0019] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar symbols throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0020] like Figure 1 The enterprise archives information intelligent management system based on big data shown in the figure includes: Data collection module: used to collect enterprise archives from various business systems within the enterprise and external data sources; The various business systems within the enterprise include office automation systems, customer relationship management systems, and financial systems; External data sources include industry databases and government public data; In an optional embodiment, the enterprise archives include: employee personnel archives, sales archives, administrative archives, financial archives, production archives, and research and development archives; Data transfer module: The data acquisition module transmits the enterprise archive data to the data transfer module through wireless transmission. The data transfer module is used to store the enterprise archive data collected by the data acquisition module; Archive information fragmentation and marking module: used to split each complete enterprise archive data in the data transfer module, split a complete enterprise archive data into multiple fragmented archive information data according to the preset fragmentation rules, and associate and mark each fragmented archive information data; By splitting a complete enterprise archive data into fragmented archive information data, and storing them in a fragmented archive information data classification storage module, the fragmented archive information data classification storage module classifies and stores multiple fragmented archive information data, which is conducive to the subsequent direct mining and processing of the fragmented archive information data. During transmission, the big data of a complete enterprise archive data is dispersed into multiple small data of fragmented archive information data, which is conducive to the stable transmission.

[0021] In an optional embodiment, in the archive information fragmentation and marking module, the preset fragmentation rule is a fragmentation rule pre-established manually; Fragmentation rules can be formulated based on the content structure, business logic, or data type of archival information; For example, for a contract file, it can be fragmented according to basic contract information, contract terms, and contract attachments; for a personnel file, it can be fragmented according to basic personal information, education experience, work experience, and training records; In an optional embodiment, the associated tag content includes an enterprise basic information identifier, an archive subject classification code, a project number or a contract number, a department code or a department name, and a sequence number; The association mark indicates that multiple fragmented archive information data belong to the same enterprise archive data, and can be restored to a complete enterprise archive data based on these association marks when needed.

[0022] Fragmented archive information data classification storage module: used to classify and store multiple fragmented archive information data, and each fragmented archive information data of a complete enterprise archive data corresponds to a classification; User authority module: used to authorize user authority, which includes primary authority and secondary authority; Among them, a first-level permission is used to retrieve all the fragmented archive information data of all categories in the fragmented archive information data classification storage module. A secondary permission is used to retrieve all fragmented archive information data of a category in the fragmented archive information data classification storage module; The archive information generation module: retrieves the fragmented archive information data in the fragmented archive information data classification storage module according to the user authority provided by the user authority module, and is used to retrieve one or more fragmented archive information data with associated tags to generate an enterprise archive. In an optional embodiment, in the archive information generation module, when a user initiates a request to generate an enterprise archive data; If the user has the first-level authority, he can directly retrieve all the fragmented archival information data related to the enterprise archival data, and according to the association mark of the fragmented archival information data and the sequence number in the association mark, he can extract the corresponding fragmented archival information data in sequence to generate a complete enterprise archival data; If the user has the second-level authority, a fragmented archival information data related to the enterprise archival data is retrieved from the category in the fragmented archival information data classification storage module, and an enterprise archival data is directly generated from the related fragmented archival information data; When it is necessary to restore a more complete or complete archive information data through a combination of multiple secondary permissions, first, within a set time, multiple users with secondary permissions respectively initiate retrieval requests for fragmented archive information within their authority ranges, and respectively obtain corresponding fragmented archive information data, thereby obtaining multiple fragmented archive information data, and generating an enterprise archive data based on the association tags of the multiple fragmented archive information data; If some users with second-level permissions do not initiate a request to retrieve the fragmented archival information data within their authority within the set time, the generation of enterprise archival data this time will only generate the enterprise archival data of the fragmented archival information data that issued the retrieval request within the set time; As an example, if the time is set to 5 minutes, for a piece of enterprise archive data containing 10 fragmented archive information data, corresponding to 10 secondary permissions, the holders of these 10 secondary permissions need to initiate a retrieval request to retrieve the fragmented archive information data they are responsible for within the specified 5 minutes, so as to obtain the 10 fragmented archive information data. At this time, a complete archive information data is generated. If 2 of the holders of the secondary permissions do not initiate a retrieval request to retrieve the fragmented archive information data they are responsible for within the specified 5 minutes, then a piece of enterprise archive data containing another 8 fragmented archive information data is generated. According to the above process, these fragmented information can be pieced together and integrated into complete enterprise archive data and displayed to users with corresponding viewing permissions or provided to related business systems for use.

[0023] When a user initiates a request to generate enterprise archive data, there are different ways to generate it according to different user permissions. Level 1 users can directly retrieve all fragmented archive information data and generate a complete archive, and level 2 users can generate archives individually or in combination. This method not only facilitates users with different permissions to obtain the required archives, but also allows for the flexibility to restore complete archives while ensuring data security.

[0024] When a user initiates a request to generate enterprise archive data, if some users with second-level permissions do not initiate a request to retrieve fragmented archive information data within their authority within the set time, the generation of enterprise archive data this time will only generate enterprise archive data for the fragmented archive information data for which a retrieval request was issued within the set time. This is beneficial when personnel from different business units need to integrate and restore the entire picture of the same project and business archives, prompting all parties to contribute fragmented information within a limited time and strengthening inter-departmental coordination and cooperation. Even if some personnel do not respond, partially available archives can be generated based on existing data, reducing work delays due to missing archives and improving the efficiency of collaborative office work within the enterprise.

[0025] Relevance analysis module: used to analyze the relevance of fragmented archive information data in the fragmented archive information data classification storage module; In an optional embodiment, in the association analysis module, the association analysis is as follows: Assume that each fragmented archive information data has several attributes for analyzing the association; Assume that the fragmented archive information data set is , where n is the total number of fragmented archive information data; For each fragmented archive information data , k=1,2,...,n, there are m attributes to describe it, For example, the attributes in the m attributes may be: enterprise registration information, enterprise organizational structure, business contract information, project information, financial statement data, financial audit information, employee information, training and development information; Suppose the vector composed of m attributes is ; For any two fragmented archive information data and , i ≠ j, their attribute vectors and The Euclidean distance is: ; Their attribute similarity for: ; This formula ensures that the similarity value is between 0 and 1, with 0 being completely dissimilar and 1 being completely identical.

[0026] In the association analysis module, the correlation of the fragmented archival information data in the association analysis module can also be calculated by statistical correlation analysis, for example, by using the principal component analysis multivariate statistical method. When multiple fragmented archival information data have a higher load on a certain principal component, it indicates that these data have a strong correlation in this dimension.

[0027] Follow-up display module: in the enterprise archive data generated by the archive information generation module, according to the relevance of the fragmented archive information data in the association analysis module, the associated fragmented archive information data whose relevance meets the set threshold value are displayed together in the generated enterprise archive data; In an optional embodiment, in the follow-up display module, the set threshold of the correlation is 0.8, that is, the attribute similarity of the two fragmented archive information data is greater than or equal to 0.8.

[0028] The correlation analysis module analyzes the correlation of the fragmented archive information data, and the follow-up display module displays the related fragmented archive information data that meets the set threshold in the generated enterprise archive according to the correlation. This helps users obtain more comprehensive and valuable archive information, not limited to the acquisition of permissions.

[0029] like Figure 1 The enterprise archives information intelligent management method based on big data shown includes the following steps: S1. Use the data collection module to collect enterprise archive data from various business systems within the enterprise and external data sources. Use wireless transmission to transmit the collected enterprise archive data to the data transfer module in real time or at a fixed time. The data transfer module will temporarily store the data in a centralized manner to form a data cache pool. S2, the archive information fragmentation and marking module extracts the complete enterprise archive data from the data transfer module, and splits a complete archive into multiple fragmented archive information data according to the preset fragmentation rules; S3. For each fragmented archive information data, mark the enterprise basic information identifier, archive subject classification code, project number or contract number, department code or department name, and sequence number according to the established association marking system; S4, the fragmented archive information data classification storage module classifies and stores the fragmented archive information data; S5. The user authority module grants the user a first-level authority or a second-level authority, wherein a first-level authority is used to retrieve all fragmented archival information data of all categories in the fragmented archival information data classification storage module; a second-level authority is used to retrieve all fragmented archival information data of one category in the fragmented archival information data classification storage module; S6. When a user initiates a request to generate enterprise archive data: If the user has the first-level authority, he can directly retrieve all the fragmented archival information data related to the enterprise archival data, and generate a complete enterprise archival data based on the association tags of the fragmented archival information data; If the user has the second-level authority, a fragmented archival information data related to the enterprise archival data is retrieved from the category in the fragmented archival information data classification storage module, and an enterprise archival data is directly generated from the related fragmented archival information data; When it is necessary to restore a more complete or complete archive information data through a combination of multiple secondary permissions, first, within a set time, multiple users with secondary permissions respectively initiate retrieval requests for fragmented archive information within their authority ranges, and respectively obtain corresponding fragmented archive information data, thereby obtaining multiple fragmented archive information data, and generating an enterprise archive data based on the association tags of the multiple fragmented archive information data; If some users with second-level permissions do not initiate a request to retrieve the fragmented archival information data within their authority within the set time, the generation of enterprise archival data this time will only generate the enterprise archival data of the fragmented archival information data that issued the retrieval request within the set time; S7, the association analysis module is used to analyze the association of the fragmented archive information data in the fragmented archive information data classification storage module; S8. In the follow-up display module, in the enterprise archive data generated by the archive information generation module, according to the relevance of the fragmented archive information data in the association analysis module, the associated fragmented archive information data whose relevance meets the set threshold is displayed together in the generated enterprise archive data.

[0030] Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0031] In the embodiments provided by the present invention, it should be understood that the disclosed system or method can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0032] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0033] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0034] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the basic features of the present invention.

[0035] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An enterprise archive information intelligent management system based on big data, characterized in that: include: Data collection module: used to collect enterprise archive data from various business systems within the enterprise and external data sources; Data transfer module: The data acquisition module transmits the enterprise archive data to the data transfer module through wireless transmission. The data transfer module is used to store the enterprise archive data collected by the data acquisition module; Archive information fragmentation and marking module: used to split each complete enterprise archive data in the data transfer module, split a complete enterprise archive data into multiple fragmented archive information data according to the preset fragmentation rules, and associate and mark each fragmented archive information data in a complete enterprise archive data; Fragmented archive information data classification storage module: used to classify and store multiple fragmented archive information data, and each fragmented archive information data of a complete enterprise archive data corresponds to a classification; User authority module: used to authorize user authority, which includes primary authority and secondary authority; a primary authority is used to retrieve all fragmented archive information data of all categories in the fragmented archive information data classification storage module; A secondary permission is used to retrieve all fragmented archive information data of a category in the fragmented archive information data classification storage module; Archive information generation module: retrieves the fragmented archive information data in the fragmented archive information data classification storage module according to the user authority provided by the user authority module, and is used to retrieve one or more fragmented archive information data with associated tags to generate an enterprise archive.

2. The enterprise archives information intelligent management system based on big data according to claim 1 is characterized in that: In the archive information generation module, when a user initiates a request to generate an enterprise archive data; If the user has the first-level authority, he can directly retrieve all the fragmented archival information data related to the enterprise archival data, and generate a complete enterprise archival data based on the association tags of the fragmented archival information data; If the user has the second-level authority, a fragmented archival information data related to the enterprise archival data is retrieved from the category in the fragmented archival information data classification storage module, and an enterprise archival data is directly generated from the related fragmented archival information data; When it is necessary to restore a more complete or complete archive information data through a combination of multiple secondary permissions, first, within a set time, multiple users with secondary permissions respectively initiate retrieval requests for fragmented archive information within their authority ranges, and respectively obtain corresponding fragmented archive information data, thereby obtaining multiple fragmented archive information data, and generating an enterprise archive data based on the association tags of the multiple fragmented archive information data; If some users with second-level permissions do not initiate a request to retrieve the fragmented archival information data within their authority within the set time, the generation of enterprise archival data this time will only generate the enterprise archival data of the fragmented archival information data for which a retrieval request was issued within the set time.

3. The enterprise archives information intelligent management system based on big data according to claim 1 is characterized in that: Also includes: Relevance analysis module: used to analyze the relevance of fragmented archive information data in the fragmented archive information data classification storage module; Follow-up display module: In the enterprise archive data generated by the archive information generation module, according to the relevance of the fragmented archive information data in the association analysis module, the associated fragmented archive information data whose relevance meets the set threshold are displayed together in the generated enterprise archive data.

4. The enterprise archives information intelligent management system based on big data according to claim 3 is characterized in that: In the association analysis module, the association analysis is as follows: Assume that each fragmented archive information data has several attributes for analyzing the association; Assume that the fragmented archive information data set is , where n is the total number of fragmented archive information data; For each fragmented archive information data , k=1,2,...,n, there are m attributes to describe it; Suppose the vector composed of m attributes is ; For any two fragmented archive information data and , i ≠ j, their attribute vectors and The Euclidean distance is: ; Their attribute similarity for: .

5. The enterprise archives information intelligent management system based on big data according to claim 4 is characterized in that: In the follow-up display module, the set threshold of the correlation is 0.8, that is, the attribute similarity of the two fragmented archive information data is greater than or equal to 0.

8.

6. The enterprise archives information intelligent management system based on big data according to claim 1 is characterized in that: In the data collection module, enterprise files include: employee personnel files, sales files, administrative files, financial files, production files, and R&D files.

7. The enterprise archives information intelligent management system based on big data according to claim 1 is characterized in that: In the archive information fragmentation and marking module, the associated marking content includes: enterprise basic information identifier, archive subject classification code, project number or contract number, department code or department name, and sequential number.

8. The enterprise archives information intelligent management method based on big data according to any one of claims 1 to 7, characterized in that: The following steps are involved: S1, the data collection module is used to collect enterprise archive data from various business systems within the enterprise and external data sources, and transmit the collected enterprise archive data to the data transfer module in real time through wireless transmission. The data transfer module centrally stores the data to form a data cache pool; S2, the archive information fragmentation and marking module extracts the complete enterprise archive data from the data transfer module, and splits a complete archive into multiple fragmented archive information data according to the preset fragmentation rules; S3, associate and mark each fragmented archival information data in a complete enterprise archival data, wherein the associated mark content includes the enterprise basic information identifier, archival subject classification code, project number or contract number, department code or department name, and sequence number; S4, the fragmented archive information data classification storage module classifies and stores the fragmented archive information data; S5. The user authority module grants the user a first-level authority or a second-level authority, wherein a first-level authority is used to retrieve all fragmented archival information data of all categories in the fragmented archival information data classification storage module; a second-level authority is used to retrieve all fragmented archival information data of one category in the fragmented archival information data classification storage module; S6. When a user initiates a request to generate enterprise archive data: If the user has the first-level authority, he can directly retrieve all the fragmented archival information data related to the enterprise archival data, and generate a complete enterprise archival data based on the association tags of the fragmented archival information data; If the user has the second-level authority, a fragmented archival information data related to the enterprise archival data is retrieved from the category in the fragmented archival information data classification storage module, and an enterprise archival data is directly generated from the related fragmented archival information data; When it is necessary to restore a more complete or complete archive information data through a combination of multiple secondary permissions, first, within a set time, multiple users with secondary permissions respectively initiate retrieval requests for fragmented archive information within their authority ranges, and respectively obtain corresponding fragmented archive information data, thereby obtaining multiple fragmented archive information data, and generating an enterprise archive data based on the association tags of the multiple fragmented archive information data; If some users with second-level permissions do not initiate a request to retrieve the fragmented archival information data within their authority within the set time, the generation of enterprise archival data this time will only generate the enterprise archival data of the fragmented archival information data that issued the retrieval request within the set time; S7, the association analysis module is used to analyze the association of the fragmented archive information data in the fragmented archive information data classification storage module; S8. In the follow-up display module, in the enterprise archive data generated by the archive information generation module, according to the relevance of the fragmented archive information data in the association analysis module, the associated fragmented archive information data whose relevance meets the set threshold is displayed together in the generated enterprise archive data.

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