A knowledge base-based enterprise data management method and system

By adopting a knowledge-based enterprise data management approach, enterprise attributes and characteristics are acquired, a valuable data knowledge base is generated, a data value identification model is built, and hierarchical management is implemented. This solves the problems of wasteful storage resources and low efficiency caused by chaotic enterprise data storage, and achieves efficient data management.

CN115796277BActive Publication Date: 2026-01-30普益智慧云科技(成都)有限公司
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Patent Information

Application Number
CN202211577854.7
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2022-12-09
Publication Date
2026-01-30
Estimated Expiration
2042-12-09

AI Technical Summary

Technical Problem

Disorganized data storage in enterprises leads to a large amount of useless data occupying storage space, resulting in low data management efficiency and wasted storage resources.

Method used

By using a knowledge-based enterprise data management approach, enterprise attribute information and data characteristics are acquired, a valuable data knowledge base is generated, a data value identification model is built, and data is transmitted to the identification model through a data interaction channel for value identification, ultimately enabling hierarchical data management.

Benefits of technology

It enables orderly and hierarchical management of enterprise data, improves data management efficiency, reduces the resource consumption of useless data, and solves the problem of storage resource waste.

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Abstract

This invention provides a knowledge base-based enterprise data management method and system, applied in the field of data management technology. The method includes: acquiring enterprise data characteristics by obtaining enterprise attribute information; generating a value data knowledge base based on these characteristics; building an enterprise data value identification model; uploading the value data knowledge base to the enterprise data value identification model to identify the value of the data; connecting to an enterprise data management system to establish a data interaction channel; transmitting the enterprise data set to the enterprise data value identification model via the data interaction channel; obtaining the data value identification results based on the enterprise data value identification model; performing data layering based on the data value identification results; outputting the data layering results; and managing the data layering based on these results. This solves the technical problems of chaotic enterprise data storage, large amounts of useless data occupying storage space, leading to low data management efficiency and wasted storage resources in existing technologies.
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Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data management, and particularly relates to an enterprise data management method and system based on a knowledge base. BACKGROUND

[0002] With the development of the Internet era, big data has become the norm of the Internet, and the development of an enterprise cannot be separated from the collection and storage of massive data. However, in the prior art, enterprise data storage is relatively chaotic, and there is mixed storage of valuable data and useless data, which leads to a large amount of useless data occupying storage space, resulting in low data management efficiency and a large amount of storage resource waste.

[0003] Therefore, in the prior art, enterprise data storage is chaotic, a large amount of useless data occupies storage space, leading to low data management efficiency and storage resource waste. SUMMARY

[0004] The present application provides an enterprise data management method and system based on a knowledge base, which is used to solve the technical problems of chaotic enterprise data storage, a large amount of useless data occupying storage space, leading to low data management efficiency and storage resource waste in the prior art.

[0005] In view of the above problems, the present application provides an enterprise data management method and system based on a knowledge base.

[0006] In a first aspect of the present application, an enterprise data management method based on a knowledge base is provided, which is applied to an enterprise data management system based on a knowledge base, and the system comprises a data layering module. The method comprises: obtaining enterprise attribute information of a target enterprise; obtaining enterprise data characteristics according to the enterprise attribute information of the target enterprise; generating a valuable data knowledge base according to the enterprise data characteristics; building an enterprise data value identification model, uploading the valuable data knowledge base to the enterprise data value identification model, and using the enterprise data value identification model to identify the value of data of the target enterprise; connecting the enterprise data management system of the target enterprise, and building a data interaction channel between the input layer of the enterprise data value identification model; transmitting the enterprise data set of the target enterprise to the enterprise data value identification model according to the data interaction channel, obtaining a data value identification result according to the enterprise data value identification model; layering data according to the data value identification result, outputting a data layering result, and managing data according to the data layering result.

[0007] In a second aspect of the present application, a knowledge base-based enterprise data management system is provided, the system comprising a data layering module, the system comprising: an enterprise attribute information acquisition module configured to acquire enterprise attribute information of a target enterprise; an enterprise data feature acquisition module configured to acquire enterprise data features according to the enterprise attribute information of the target enterprise; a value data knowledge base acquisition module configured to generate a value data knowledge base according to the enterprise data features; a value identification module configured to build an enterprise data value identification model, upload the value data knowledge base to the enterprise data value identification model, and use the value data knowledge base to identify the value of data of the target enterprise; an interactive channel construction module configured to connect an enterprise data management system of the target enterprise, and build a data interactive channel between an input layer of the enterprise data value identification model; a value identification result acquisition module configured to transmit a set of enterprise data of the target enterprise to the enterprise data value identification model according to the data interactive channel, acquire a data value identification result according to the enterprise data value identification model; and a layering management module configured to layer data according to the data value identification result, output a data layering result, and manage data according to the data layering result.

[0008] The one or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0009] The method provided by the embodiments of the present application acquires enterprise attribute information of a target enterprise, acquires enterprise data features according to the enterprise attribute information of the target enterprise, generates a value data knowledge base according to the enterprise data features, builds an enterprise data value identification model, uploads the value data knowledge base to the enterprise data value identification model, and uses the value data knowledge base to identify the value of data of the target enterprise, connects an enterprise data management system of the target enterprise, builds a data interactive channel between an input layer of the enterprise data value identification model, transmits a set of enterprise data of the target enterprise to the enterprise data value identification model according to the data interactive channel, acquires a data value identification result according to the enterprise data value identification model, layers data according to the data value identification result, outputs a data layering result, and manages data according to the data layering result. The method realizes ordered layering management of enterprise data, improves data management efficiency, and reduces the occupation of resources by non-value data in a timely manner. The technical problems of disordered storage of enterprise data, occupation of storage space by a large amount of useless data, low data management efficiency, and waste of storage resources in the prior art are solved.

[0010] The above description is only a summary of the technical solutions of the present application. In order to more clearly understand the technical means of the present application, the embodiments of the present application can be implemented in accordance with the content of the description, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application are described below. Attached Figure Description

[0011] Figure 1 This application provides a flowchart illustrating a knowledge base-based enterprise data management method.

[0012] Figure 2 A flowchart illustrating the process of obtaining data value identification results in a knowledge base-based enterprise data management method provided in this application;

[0013] Figure 3 A flowchart illustrating the process of obtaining data transmission parameters in a knowledge base-based enterprise data management method provided in this application;

[0014] Figure 4 This application provides a schematic diagram of the structure of an enterprise data management system based on a knowledge base.

[0015] Figure labeling: Enterprise attribute information acquisition module 11, Enterprise data feature acquisition module 12, Value data knowledge base acquisition module 13, Value identification module 14, Interaction channel construction module 15, Value identification result acquisition module 16, Hierarchical management module 17. Detailed Implementation

[0016] This application provides a knowledge base-based enterprise data management method and system to address the technical problems in existing technologies, such as chaotic enterprise data storage, large amounts of useless data occupying storage space, resulting in low data management efficiency and wasted storage resources.

[0017] The technical solutions in this application will now be clearly and completely described with reference to the accompanying drawings. The described embodiments are only a part of what can be achieved by this application, and not all of the contents of this application.

[0018] Example 1

[0019] like Figure 1 As shown, this application provides a knowledge-based enterprise data management method, which is applied to a knowledge-based enterprise data management system. The system includes a data layering module, and the method includes:

[0020] Step 100: Obtain the target company's enterprise attribute information;

[0021] Step 200: Obtain enterprise data characteristics based on the enterprise attribute information of the target enterprise;

[0022] Step 300: Generate a value data knowledge base based on the enterprise data characteristics described above;

[0023] Specifically, the enterprise attribute information of the target enterprise is acquired, the target enterprise being a target enterprise to be managed by enterprise data, wherein the enterprise attribute includes the specific industry of the enterprise, the data type to be managed, and the attribute category of the enterprise, etc. According to the enterprise attribute information of the target enterprise, the enterprise data features are acquired, wherein the enterprise data features include the specific technology of the enterprise and the specific data type corresponding to the technology, such as text type, video type, data type, program type, etc. According to the enterprise data features, the value data knowledge base is generated, which contains the data value of the data type corresponding to each technology of the enterprise. That is, the corresponding data value of the data type in each technology classification of the enterprise is labeled according to the enterprise technology classification, and the data value is stored in the value data knowledge base to generate the value data knowledge base. This facilitates subsequent value assessment of the value data in the enterprise through the value data knowledge base.

[0024] Step 400: building an enterprise data value identification model, uploading the value data knowledge base to the enterprise data value identification model for value identification of the data of the target enterprise;

[0025] Step 500: connecting the enterprise data management system of the target enterprise to build a data interaction channel between the input layer of the enterprise data value identification model;

[0026] Step 600: transmitting the enterprise data set of the target enterprise to the enterprise data value identification model according to the data interaction channel, and acquiring a data value identification result according to the enterprise data value identification model;

[0027] Step 700: data layering according to the data value identification result, outputting a data layering result, and performing data layering management according to the data layering result.

[0028] Specifically, the enterprise data value identification model is constructed, the value data knowledge base is uploaded to the enterprise data value identification model for value identification of the data of the target enterprise. Then, the enterprise data management system of the target enterprise is connected to build a data interaction channel between the input layer of the enterprise data value identification model, so that the enterprise data value identification model can acquire the data information of the target enterprise. According to the data interaction channel, the enterprise data set of the target enterprise is transmitted to the enterprise data value identification model, and a data value identification result is acquired according to the enterprise data value identification model. Finally, the data value identification result is data layered, and a layering result is outputted, i.e., the data value identification result is divided into different levels, the data is managed in layers according to the acquired data layering result, the ordered layering management of the enterprise data is realized, the data management efficiency is improved, and the occupation of resources by non-value data is reduced in time.

[0029] As Figure 2As shown, the method provided in the embodiment of the present application further includes steps 400:

[0030] Step 410: connecting the enterprise data management system of the target enterprise to obtain a plurality of data management modules, wherein the data types of each management module in the plurality of data management modules are different;

[0031] Step 420: obtaining the enterprise data set according to the plurality of data management modules;

[0032] Step 430: inputting the enterprise data set into the enterprise data value identification model;

[0033] Step 440: performing value identification according to the value data knowledge base embedded in the enterprise data value identification model to obtain the data value identification result.

[0034] Specifically, the enterprise data management system of the target enterprise is connected to obtain a plurality of data management modules, wherein the plurality of data management modules are used for managing different types of data. According to the plurality of data management modules, the enterprise data set is obtained, which contains all data of the enterprise, such as value data and non-value data. The value data and the non-value data are marked before being stored in the management module. Further, the enterprise data set is input into the enterprise data value identification model, and the value identification is performed through the value data knowledge base embedded in the enterprise data value identification model to identify the data value of each management module corresponding to the data type in the enterprise data set, and the data value identification result is obtained.

[0035] The method provided in the embodiment of the present application further includes step 440:

[0036] Step 441: identifying each management module in the plurality of data management modules according to the value data knowledge base embedded in the enterprise data value identification model to obtain a plurality of value data sets, wherein the plurality of value data sets correspond one-to-one to the plurality of data management modules;

[0037] Step 442: obtaining the proportion of the plurality of value data sets in the total data of the corresponding management module to obtain the value data coverage rate;

[0038] Step 443: taking the value data coverage rate as the data value identification result output.

[0039] Specifically, each management module in the plurality of data management modules is identified according to the value data knowledge base embedded in the enterprise data value identification model, value data in all management modules is acquired, and a plurality of value data sets are obtained. The plurality of value data sets and the plurality of data management modules correspond to each other. Subsequently, a proportion of the plurality of value data sets in total data of the corresponding management module is acquired, that is, a proportion of value data of each data management module in total data of the corresponding management module is acquired, and a value data coverage rate is acquired. The value data coverage rate is taken as a data value identification result for value output, and evaluation of data value is completed.

[0040] The method step 440 provided in the embodiment of the application further includes:

[0041] Step 444: performing module value grade analysis on the plurality of data management modules according to the value data coverage rate, and acquiring a module value grade;

[0042] Step 445: judging based on the module value grade, and acquiring an identified management module with a value data coverage rate greater than a preset value data coverage rate;

[0043] Step 446: acquiring a data partition instruction according to the identified management module;

[0044] Step 447: performing partition management of value data and non-value data on data in the identified management module according to the data partition instruction.

[0045] Specifically, the plurality of data management modules are subjected to module value grade analysis according to the value data coverage rate, and a value grade of each data management module is acquired. When the value grade of the data management module is acquired, a value grade corresponding to a different coverage rate is acquired by predefining a data coverage rate and grade correspondence. The identified management module with the value data coverage rate greater than the preset value data coverage rate is acquired based on the module value grade. The data partition instruction is acquired according to the identified management module, and the data partition instruction is used for partitioning value data and non-value data in the identified management module. The partition management of value data and non-value data on data in the identified management module is completed by acquiring the data partition instruction.

[0046] The method step 700 provided in the embodiment of the application further includes:

[0047] Step 710: connecting the value data knowledge base, and performing information entropy assignment on value data in the value data knowledge base;

[0048] Step 720: performing value grade division on a corresponding value data set in each management module according to the value data knowledge base after information entropy assignment, and acquiring a grade division result;

[0049] Step 730: hierarchical management of the value data in the identification management module according to the grade division result.

[0050] Specifically, the value data knowledge base is connected, and the value data in the value data knowledge base is assigned an information entropy. The information entropy is the importance of the value data information, and the greater the entropy value, the higher the value. For example, in program data, different technologies correspond to different values. For example, program data of new technologies has a higher value, and program data corresponding to old technologies has a lower value. Or, whether it is a core technology of the company is determined, and an information entropy is assigned. The greater the entropy value, the greater the importance of the corresponding value data information. Subsequently, the value data knowledge base after the information entropy assignment is used to divide the value data set in each management module into grades to obtain a grade division result. The value data knowledge base after the information entropy assignment is used to divide the value data set into grades. The value data in the identification management module is managed in layers according to the grade division result, and hierarchical management of the value data is achieved.

[0051] As shown in Figure 3 The method steps 600 provided by the embodiment of the present application further include:

[0052] Step 610: obtaining a network configuration environment of the data interaction channel;

[0053] Step 620: obtaining channel load data for data transmission in the network configuration environment;

[0054] Step 630: generating data transmission parameters according to the channel load data;

[0055] Step 640: transmitting the enterprise data set of the target enterprise according to the data transmission parameters.

[0056] Specifically, the network configuration environment of the data interaction channel is obtained, and the load data of the data transmission channel is obtained through the network configuration environment. The load data of the transmission channel is the specific data transmission capacity of the channel. When the data transmission amount is large at the same time, the transmission channel load is large, and continuous data transmission will result in low data transmission efficiency, and problems such as freezing, delay, or response failure in the data transmission process. According to the channel load data, data transmission parameters are generated. When the data transmission parameters are generated, the transmission parameters are obtained according to the target function, including data packet size, transmission interval, etc. By obtaining the transmission parameters, it is avoided that the transmission channel reaches the maximum load, resulting in freezing, delay, or response failure in the data transmission process. According to the data transmission parameters, the enterprise data set of the target enterprise is transmitted.

[0057] The method steps 600 provided by the embodiment of the present application further include:

[0058] Step 650: obtaining a set of enterprise data of the target enterprise;

[0059] Step 660: performing data type and data volume analysis on the set of enterprise data of the target enterprise, obtaining data transmission type and data transmission volume value;

[0060] Step 670: taking the data transmission type and data transmission volume value as input variables, taking the channel load data as the target, building an objective function, performing transmission configuration according to the objective function, and outputting the data transmission parameters.

[0061] Specifically, a set of enterprise data of the target enterprise is obtained. The set of enterprise data of the target enterprise is analyzed in terms of data type and data volume, wherein the data type includes text data, video data, program data, etc. The transmission volume value corresponding to the data transmission type is obtained, wherein the transmission volume value is a specific data transmission volume. Further, the data transmission type and the data transmission volume value are taken as input variables, and the channel load data is taken as the target to build an objective function. In the objective function, the load data is the maximum data transmission volume, and the objective function obtains the transmission volume remaining space by calculating the difference between the maximum data transmission volume and the current data transmission volume. The transmission type and the data transmission volume value are also used to calculate the total transmission data volume, and the total transmission data volume is obtained. According to the total transmission data volume and the real-time obtained transmission volume remaining space, the data packet size and the transmission interval of the transmission data are obtained, and the data transmission parameters are obtained, so as to avoid the situation that the transmission channel reaches the maximum load, resulting in the situation of lag, delay, or response failure in the data transmission process.

[0062] In summary, the method provided by the embodiments of the present application obtains enterprise attribute information and obtains enterprise data features. According to the enterprise data features, a value data knowledge base is generated. An enterprise data value identification model is built, and the value data knowledge base is uploaded to the enterprise data value identification model for value identification of data. A data interaction channel is connected, and enterprise data sets are transmitted to the enterprise data value identification model according to the data interaction channel. According to the enterprise data value identification model, data value identification results are obtained. According to the data value identification results, data is layered, and data layering results are output. Data is managed in layers according to the data layering results. The ordered layered management of enterprise data is realized, the data management efficiency is improved, and the occupied resources of non-value data are reduced in a timely manner. The technical problems of disordered enterprise data storage, large amount of useless data occupying storage space, low data management efficiency, and waste of storage resources in the prior art are solved.

[0063] Embodiment Two

[0064] Based on the same inventive concept as the knowledge base-based enterprise data management method in the foregoing embodiments, asFigure 4 As shown, the present application provides a knowledge base-based enterprise data management system, the system comprising a data layering module, the system comprising:

[0065] An enterprise attribute information acquisition module 11 is configured to acquire enterprise attribute information of a target enterprise;

[0066] An enterprise data feature acquisition module 12 is configured to acquire enterprise data features according to the enterprise attribute information of the target enterprise;

[0067] A value data knowledge base acquisition module 13 is configured to generate a value data knowledge base according to the enterprise data features;

[0068] A value identification module 14 is configured to build an enterprise data value identification model, upload the value data knowledge base to the enterprise data value identification model, and use the enterprise data value identification model to identify the value of data of the target enterprise;

[0069] An interactive channel construction module 15 is configured to connect an enterprise data management system of the target enterprise, and build a data interactive channel between an input layer of the enterprise data value identification model;

[0070] A value identification result acquisition module 16 is configured to transmit the enterprise data set of the target enterprise to the enterprise data value identification model according to the data interactive channel, and acquire a data value identification result according to the enterprise data value identification model;

[0071] A layering management module 17 is configured to layer data according to the data value identification result, output a data layering result, and manage the data according to the data layering result.

[0072] Further, the value identification module 14 is further configured to:

[0073] Connect the enterprise data management system of the target enterprise, and acquire a plurality of data management modules, wherein the data types of each management module in the plurality of data management modules are different;

[0074] Acquire the enterprise data set according to the plurality of data management modules;

[0075] Input the enterprise data set into the enterprise data value identification model;

[0076] Identify the value according to the value data knowledge base embedded in the enterprise data value identification model, and acquire the data value identification result.

[0077] Further, the value identification module 14 is further configured to:

[0078] According to the value data knowledge base embedded in the enterprise data value identification model, each management module in the plurality of data management modules is identified, and a plurality of value data sets are obtained, wherein the plurality of value data sets correspond one-to-one to the plurality of data management modules;

[0079] Obtain the proportion of the plurality of value data sets in the total data of the corresponding management module, and obtain the value data coverage rate;

[0080] The value data coverage rate is used as the data value identification result output.

[0081] Further, the value identification module 14 is also used for:

[0082] According to the value data coverage rate, the module value grade analysis of the plurality of data management modules is performed, and the module value grade is obtained;

[0083] Based on the module value grade, it is judged that the value data coverage rate of the identified management module is greater than the preset value data coverage rate;

[0084] According to the identified management module, the data partition instruction is obtained;

[0085] According to the data partition instruction, the value data and non-value data in the identified management module are partitioned and managed.

[0086] Further, the hierarchical management module 17 is also used for:

[0087] Connect the value data knowledge base, and assign information entropy to the value data in the value data knowledge base;

[0088] According to the value data knowledge base after information entropy assignment, the value grade division of the corresponding value data set in each management module is performed, and the grade division result is obtained;

[0089] According to the grade division result, the value data in the identified management module is managed in layers.

[0090] Further, the interactive channel construction module 16 is also used for:

[0091] Obtain the network configuration environment of the data interaction channel;

[0092] Obtain the channel load data used for data transmission according to the network configuration environment;

[0093] According to the channel load data, the data transmission parameters are generated;

[0094] According to the data transmission parameters, the enterprise data set of the target enterprise is transmitted.

[0095] Further, the interaction channel construction module 16 is also used for:

[0096] acquiring a set of enterprise data of the target enterprise;

[0097] performing data type and data volume analysis on the set of enterprise data of the target enterprise, acquiring data transmission type and data transmission volume value;

[0098] taking the data transmission type and data transmission volume value as input variables, taking the channel load data as a target, building a target function, performing transmission configuration according to the target function, and outputting the data transmission parameter.

[0099] The above embodiment two is used for executing the method in the embodiment one, and the execution principle and the execution basis can be obtained from the content recorded in the embodiment one, and excessive details are not described here. Although the present application is described in combination with specific features and embodiments thereof, the present application is not limited by the example embodiments described herein. Based on the embodiments of the present application, those skilled in the art can make various modifications and variations to the present application without departing from the scope of the present application, and the content obtained in this way also belongs to the scope of protection of the present application.

Claims

1. A knowledge base based enterprise data management method, characterized by, The method is applied to a knowledge base-based enterprise data management system, the system comprising a data layering module, and the method comprising: obtaining enterprise attribute information of a target enterprise; obtaining enterprise data characteristics according to the enterprise attribute information of the target enterprise; generating a value data knowledge base according to the enterprise data characteristics; building an enterprise data value identification model, uploading the value data knowledge base to the enterprise data value identification model, and using the value data knowledge base to identify the value of data of the target enterprise; connecting the enterprise data management system of the target enterprise, and building a data interaction channel between the input layer of the enterprise data value identification model; transmitting the enterprise data set of the target enterprise to the enterprise data value identification model according to the data interaction channel, obtaining a data value identification result according to the enterprise data value identification model; performing data layering according to the data value identification result, outputting a data layering result, and performing data layering management according to the data layering result; The method further comprises: connecting the enterprise data management system of the target enterprise, and obtaining a plurality of data management modules, wherein the data types of each management module in the plurality of data management modules are different; obtaining the enterprise data set according to the plurality of data management modules; inputting the enterprise data set into the enterprise data value identification model; performing value identification according to the value data knowledge base embedded in the enterprise data value identification model, and obtaining the data value identification result; The method of performing value identification according to the value data knowledge base embedded in the enterprise data value identification model, and obtaining the data value identification result, comprises: identifying each management module in the plurality of data management modules according to the value data knowledge base embedded in the enterprise data value identification model, and obtaining a plurality of value data sets, wherein the plurality of value data sets correspond one-to-one to the plurality of data management modules; obtaining the proportion of the plurality of value data sets in the total data of the corresponding management module, and obtaining a value data coverage rate; outputting the value data coverage rate as the data value identification result; The method further comprises: performing module value level analysis on the plurality of data management modules according to the value data coverage rate, and obtaining a module value level; judging based on the module value level, and obtaining an identified management module with a value data coverage rate greater than a preset value data coverage rate; obtaining a data partitioning instruction according to the identified management module; performing partitioning management of value data and non-value data on the data in the identified management module according to the data partitioning instruction.

2. The method of claim 1, wherein, The method of performing data layering according to the data value identification result, outputting a data layering result, and performing data layering management according to the data layering result, comprises: connecting the value data knowledge base, and assigning information entropy to the value data in the value data knowledge base; performing value level division on the corresponding value data set in each management module according to the value data knowledge base after information entropy assignment, and obtaining a level division result; According to the classification result, the value data in the identification management module is managed in layers.

3. The method of claim 1, wherein, The method further comprises: Obtaining the network configuration environment of the data interaction channel; Obtaining channel load data for data transmission in the network configuration environment; Generating data transmission parameters according to the channel load data; Transmitting the enterprise data set of the target enterprise according to the data transmission parameters.

4. The method of claim 3, wherein, The method for generating data transmission parameters comprises: Obtaining the enterprise data set of the target enterprise; Analyzing the data type and data volume of the enterprise data set of the target enterprise to obtain data transmission type and data transmission volume values; Using the data transmission type and data transmission volume values as input variables and the channel load data as the target, building a target function, configuring transmission according to the target function, and outputting the data transmission parameters.

5. A knowledge base based enterprise data management system, characterized by, The system is used to implement the knowledge base-based enterprise data management method of any one of claims 1-4, and comprises a data layering module, and the system comprises: An enterprise attribute information acquisition module for acquiring enterprise attribute information of a target enterprise; An enterprise data feature acquisition module for acquiring enterprise data features according to the enterprise attribute information of the target enterprise; A value data knowledge base acquisition module for generating a value data knowledge base according to the enterprise data features; A value identification module for building an enterprise data value identification model, uploading the value data knowledge base to the enterprise data value identification model, and identifying the value of data of the target enterprise; An interaction channel construction module for connecting an enterprise data management system of the target enterprise and building a data interaction channel between an input layer of the enterprise data value identification model; A value identification result acquisition module for transmitting an enterprise data set of the target enterprise to the enterprise data value identification model according to the data interaction channel, and acquiring a data value identification result according to the enterprise data value identification model; A layering management module for layering data according to the data value identification result, outputting a data layering result, and managing data in layers according to the data layering result.

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