A government-enterprise data governance system based on business data

Abstract

The present invention relates to the technical field of data governance, and discloses a government-enterprise data governance system based on business data. The present invention queries the working logs of all government-enterprise data in the system database according to the data query acquisition module, analyzes the usage of the data in the system according to the query results, migrates some of the internal data of the system to the network disk for backup according to the analysis results, ensures that the system database has enough storage space to accommodate new data, and when a new data source needs to be uploaded to the system database, analyzes the new data source, ensures the security of the data source before uploading, and guarantees the security of the system database.

Description

Technical Field

[0001] The present invention relates to the technical field of data governance, and particularly to a government-enterprise data governance system based on business data. Background Art

[0002] Government-enterprise data refers to various types of data generated during the business transactions and cooperation processes between government agencies and enterprises. These data cover multiple fields such as government affairs management, enterprise operation, market monitoring, and public services, including but not limited to administrative record data, enterprise production and operation data, public service data, etc. With the rapid development of information technology, government-enterprise agencies have accumulated a large amount of business data in their daily operations. However, these data are often scattered in different business systems, databases, and files, lacking unified management and governance.

[0003] The existing government-enterprise data governance systems have the following problems. As the business develops, the government-enterprise data is increasing and being updated in real time. However, the storage capacity of the system database is limited. If the data in the system database is not migrated regularly, new data will not be able to be stored in the system. Therefore, the present application proposes a government-enterprise data governance system based on business data. Summary of the Invention

[0004] The purpose of the present invention is to provide a government-enterprise data governance system based on business data to solve the above technical problems.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A government-enterprise data governance system based on business data includes a data query and acquisition module, a data analysis module, an internal governance module, an external governance module, and an early warning module;

[0007] The data query and acquisition module is used to query the work logs corresponding to the government-enterprise data;

[0008] The data analysis module is used to analyze the work logs of the government-enterprise data according to the query results of the data query and acquisition module;

[0009] The internal governance module is used to migrate the internal data sources of the system database according to the analysis results of the data analysis module;

[0010] The external governance module is used to perform security management on the external data sources according to the analysis results of the data analysis module.

[0011] As a further description of the solution of the present invention, the working process of the data analysis module includes:

[0012] The government and enterprise data sources inside the system database are classified into n categories of data according to content, and the classification numbers are in sequence as: 1, 2, …, i, …, n, where i belongs to n;

[0013] Construct a data usage coefficient calculation model, and the expression is: , where is the data usage coefficient of the i-th category of data, is the data redundancy index of the i-th category of data, is the data contribution index of the i-th category of data, and are the corresponding weight coefficients respectively;

[0014] The calculation expression of the data redundancy index of the i-th category of data is: , where is the time when the i-th category of data is uploaded to the system, is the system usage frequency.

[0015] As a further description of the solution of the present invention, the assignment method of the data contribution index of the i-th category of data is:

[0016] Statistical analysis is performed on the usage frequencies of n categories of data. When the usage frequency of the i-th category of data ranks among the top one-third of all data, then , when the usage frequency of the i-th category of data ranks among the middle one-third of all data, then , when the usage frequency of the i-th category of data ranks among the last one-third of all data, then .

[0017] As a further description of the solution of the present invention, the working process of the data analysis module further includes:

[0018] Obtain the total number of times the j-th category of data is used , the number of times the j-th category of data is used within the current period and the number of times the usage of the j-th category of data changes relative to the previous period within the current period ;

[0019] According to the obtained parameters, construct a data migration coefficient calculation model, and the expression is:

[0020] ;

[0021] In the formula, is the migration coefficient of the j-th category of data.

[0022] As a further description of the solution of the present invention, the working process of the internal governance module includes:

[0023] Calculate the data usage coefficients of n types of data in sequence through the data usage coefficient calculation model, and sort the data usage coefficients of the n types of data from small to large;

[0024] Intercept the top q data in the ranking as the preliminary migration objects, where q belongs to n and j belongs to q;

[0025] The migration coefficient of the j-th type of data is compared with the set migration coefficient threshold If the migration coefficient of the j-th type of data is less than the set migration coefficient threshold , then the j-th type of data needs to be migrated to the network disk. If the migration coefficient of the j-th type of data is greater than or equal to the set migration coefficient threshold , then the j-th type of data does not need to be migrated to the network disk temporarily.

[0026] As a further description of the solution of the present invention, the working process of the data analysis module further includes:

[0027] When an external data source Q needs to be uploaded to the system database, obtain the source address A of the external data source that is about to be updated to the system database;

[0028] According to the obtained source address A of the external data source Q that is about to be updated to the system database, query the historical record of uploading the data source from the source address A to the system database;

[0029] Obtain the total number of times of uploading the data source from the source address A to the system database. Taking as a cycle, obtain the number of times of uploading the data source from the source address A to the system database in each cycle within the historical time period, and construct a curve of the number of times of uploading the data source from the source address A to the system database in each cycle within the historical time period changing with time ;

[0030] Construct a mathematical model for the security coefficient of the external data source Q, and the expression is:

[0031] ;

[0032] In the formula, , are weight coefficients, is the initial cycle of the historical time period, is the end cycle of the historical time period, is the first derivative of the curve , is the maximum value of the first derivative of the curve , is the minimum value of the first derivative of the curve , is the safety factor of the external data source Q.

[0033] As a further description of the solution of the present invention, the working process of the external governance module includes:

[0034] Compare the safety factor of the external data source Q with the set safety factor threshold If the safety factor of the external data source Q is less than the set safety factor threshold , it indicates that the security of the external data source Q is poor, and the external data source Q needs to be verified before it can be uploaded to the system database. If the safety factor of the external data source Q is greater than or equal to the set safety factor threshold , it indicates that the security of the external data source Q is good.

[0035] As a further description of the solution of the present invention, the working method of the governance system includes:

[0036] Step S1: Regularly migrate the internal data source of the system database to ensure that when a new external data source is uploaded to the system database, the system database has enough space to accept it;

[0037] Step S2: When a new external data source is uploaded to the system database, perform a security assessment on the external data source to be uploaded.

[0038] The beneficial effects of the present invention are as follows: 1. According to the data query and acquisition module, the working logs of all government and enterprise data in the system database are queried. Based on the query results, the usage of the data in the system is analyzed. According to the analysis results, some data inside the system are migrated to the network disk for backup to ensure that the system database has enough storage space to accommodate new data. When a new data source needs to be uploaded to the system database, the new data source is analyzed to ensure the security of the data source before uploading, thus ensuring the security of the system database.

[0039] 2. First, the present invention classifies the government and enterprise data sources inside the system database into n categories according to content. Then, it queries the usage of each category of data through work logs. Next, it calculates the redundancy index of the data based on the time when the data is uploaded to the system and the usage frequency. Then, it assigns values to the impact index of the data according to the usage frequency of the data. Furthermore, it calculates the usage coefficient of the data based on the redundancy index and the impact index of the data. It calculates the usage coefficients of the n categories of data in turn, sorts the usage coefficients of the n categories of data from small to large, intercepts the top q data as the preliminary migration objects, and then analyzes the top q data, calculates the migration coefficient of the data through a formula. Finally, it compares the migration coefficient of the j-th category of data with the set migration coefficient threshold. If the migration coefficient of the j-th category of data is less than the set migration coefficient threshold, the j-th category of data needs to be migrated to the network disk. If the migration coefficient of the j-th category of data is greater than or equal to the set migration coefficient threshold, the j-th category of data does not need to be migrated to the network disk temporarily.

[0040] 3. The present invention provides a solution for verifying the security of external data sources. First, it obtains the source address A of the external data source Q. Taking as a cycle, it obtains the number of times the source address A uploads the data source to the system database within each cycle in the historical time period, and constructs a curve of the number of times the source address A uploads the data source to the system database changing with time within each cycle in the historical time period. It calculates the security coefficient of the external data source Q through a formula according to the obtained parameters, and compares the security coefficient of the external data source Q with the set security coefficient threshold. If the security coefficient of the external data source Q is less than the set security coefficient threshold, it indicates that the security of the external data source Q is poor, and the external data source Q needs to be verified before it can be uploaded to the system database. If the security coefficient of the external data source Q is greater than or equal to the set security coefficient threshold, it indicates that the security of the external data source Q is good. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The following further describes the present invention with reference to the accompanying drawings.

[0042] Figure 1 FIG. is a schematic structural diagram of a government and enterprise data governance system based on business data provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0044] Please refer to Figure 1, the present invention is a government and enterprise data governance system based on business data, including a data query and acquisition module, a data analysis module, an internal governance module, an external governance module, and an early warning module;

[0045] The data query and acquisition module is used to query the work logs corresponding to the government and enterprise data;

[0046] The data analysis module is used to analyze the work logs of the government and enterprise data according to the query results of the data query and acquisition module;

[0047] The internal governance module is used to migrate the internal data sources of the system database according to the analysis results of the data analysis module;

[0048] The external governance module is used to perform security management on the external data sources according to the analysis results of the data analysis module.

[0049] Through the above technical solution, the present invention queries the work logs of all government and enterprise data in the system database according to the data query and acquisition module, analyzes the usage of the data in the system according to the query results, migrates some of the internal data of the system to the network disk for backup according to the analysis results, ensures that the system database has enough storage space to accommodate new data, analyzes the new data sources when new data sources need to be uploaded to the system database, and ensures the security of the data sources before uploading, thus ensuring the security of the system database.

[0050] As a further description of the solution of the present invention, the working process of the data analysis module includes:

[0051] Classify the internal government and enterprise data sources in the system database into n types of data according to the content, and the classification numbers are in turn: 1, 2,..., i,..., n, where i belongs to n;

[0052] Construct a data usage coefficient calculation model, and the expression is: , where is the usage coefficient of the i-th type of data, is the redundancy index of the i-th type of data, is the contribution index of the i-th type of data, and are the corresponding weight coefficients respectively;

[0053] The calculation expression of the redundancy index of the i-th type of data is: , where is the upload system time of the i-th type of data, is the system usage frequency.

[0054] As a further description of the solution of the present invention, the assignment method of the contribution index of the i-th type of data is:

[0055] Statistically analyze the usage frequency of n types of data. When the usage frequency of the i-th type of data ranks in the top one-third of all data, then = 1. When the usage frequency of the i-th type of data ranks in the middle one-third of all data, then = 0.5. When the usage frequency of the i-th type of data ranks in the bottom one-third of all data, then = 0.2.

[0056] As a further description of the solution of the present invention, the working process of the data analysis module further includes:

[0057] Obtain the total number of times the j-th type of data is used the number of times the j-th type of data is used within the current period and the number of times the usage of the j-th type of data changes relative to the previous period within the current period ;

[0058] According to the obtained parameters, construct a data migration coefficient calculation model, and the expression is:

[0059] ;

[0060] In the formula, is the migration coefficient of the j-th type of data.

[0061] As a further description of the solution of the present invention, the working process of the internal governance module includes:

[0062] Calculate the data usage coefficients of n types of data in sequence through the data usage coefficient calculation model, and sort the data usage coefficients of n types of data from small to large;

[0063] Intercept the top q data as the preliminary migration objects, where q belongs to n and j belongs to q;

[0064] Compare the migration coefficient of the j-th type of data with the set migration coefficient threshold . If the migration coefficient of the j-th type of data is less than the set migration coefficient threshold , then the j-th type of data needs to be migrated to the network disk. If the migration coefficient of the j-th type of data is greater than or equal to the set migration coefficient threshold , then it is temporarily not necessary to migrate the j-th type of data to the network disk.

[0065] Through the above technical solution, in this embodiment, the government and enterprise data sources inside the system database are first classified into n categories of data according to content, then the usage of each category of data is queried through the work log, and then the redundancy index of the data is calculated based on the time when the data is uploaded to the system and the usage frequency. Then, the impact index of the data is assigned according to the usage frequency of the data, and then the usage coefficient of the data is calculated based on the redundancy index and the impact index of the data. The usage coefficients of the n categories of data are calculated in turn, and the usage coefficients of the n categories of data are sorted from small to large, and the top q data are intercepted as the preliminary migration objects, and then the top q data are analyzed through the formula Calculate the migration coefficient of the data. Finally, the migration coefficient of the j-th category of data is compared with the set migration coefficient threshold . If the migration coefficient of the j-th category of data is less than the set migration coefficient threshold , then the j-th category of data needs to be migrated to the network disk. If the migration coefficient of the j-th category of data is greater than or equal to the set migration coefficient threshold , then the j-th category of data does not need to be migrated to the network disk for the time being.

[0066] As a further description of the solution of the present invention, the working process of the data analysis module further includes:

[0067] When an external data source Q needs to be uploaded to the system database, obtain the source address A of the external data source to be updated to the system database;

[0068] According to the obtained source address A of the external data source Q to be updated to the system database, query the historical record of uploading the data source from the source address A to the system database;

[0069] Obtain the total number of times of uploading the data source from the source address A to the system database. Taking as a cycle, obtain the number of times of uploading the data source from the source address A to the system database in each cycle within the historical time period, and construct a curve of the number of times of uploading the data source from the source address A to the system database in each cycle within the historical time period changing with time ;

[0070] Construct a mathematical model for the security coefficient of the external data source Q, and the expression is:

[0071] ;

[0072] In the formula, , are weight coefficients, is the initial cycle of the historical time period, is the end cycle of the historical time period, is the curve The first derivative of is the maximum value of the first derivative of the curve and is the minimum value of the first derivative of the curve . is the safety factor of the external data source Q.

[0073] As a further description of the solution of the present invention, the working process of the external governance module includes:

[0074] Compare the safety factor of the external data source Q with the set safety factor threshold . If the safety factor of the external data source Q is less than the set safety factor threshold , it indicates that the security of the external data source Q is poor and the external data source Q needs to be verified before it can be uploaded to the system database. If the safety factor of the external data source Q is greater than or equal to the set safety factor threshold , it indicates that the security of the external data source Q is good.

[0075] Through the above technical solution, this embodiment provides a solution for verifying the security of an external data source. First, obtain the source address A of the external data source Q, and take it as a cycle to obtain the number of times the source address A uploads data sources to the system database within each cycle in the historical time period, and construct a curve of the number of times the source address A uploads data sources to the system database within each cycle in the historical time period changing with time. Calculate the safety factor of the external data source Q according to the obtained parameters through the formula , compare the safety factor of the external data source Q with the set safety factor threshold . If the safety factor of the external data source Q is less than the set safety factor threshold , it indicates that the security of the external data source Q is poor and the external data source Q needs to be verified before it can be uploaded to the system database. If the safety factor of the external data source Q is greater than or equal to the set safety factor threshold , it indicates that the security of the external data source Q is good.

[0076] As a further description of the solution of the present invention, the working method of the governance system includes:

[0077] Step S1: Regularly migrate the internal data sources in the system database to ensure that when a new external data source is uploaded to the system database, the system database has enough space to accept it;

[0078] Step S2: When a new external data source is uploaded to the system database, perform a security assessment on the external data source to be uploaded.

[0079] It should be noted that all the weight coefficients, thresholds, and threshold intervals in the present invention are obtained based on empirical data and do not require excessive description.

[0080] The above has described a specific embodiment of the present invention in detail. However, the above content is only a preferred embodiment of the present invention and should not be considered as limiting the scope of implementation of the present invention. Any equivalent changes and improvements made within the scope of the application of the present invention should still fall within the scope covered by the patent of the present invention.

Claims

1. A government and enterprise data governance system based on business data, characterized in that: It includes data query and acquisition module, data analysis module, internal governance module, external governance module and early warning module; The data query acquisition module is used to query the work log corresponding to the government and enterprise data; The data analysis module is used to analyze the work log of government and enterprise data according to the query results of the data query acquisition module; The internal governance module is used to migrate the internal data source of the system database according to the analysis results of the data analysis module; The external governance module is used to perform security management on the external data source according to the analysis results of the data analysis module; The working process of the data analysis module also includes: Get the total number of times the jth type of data is used , the number of times the j-th type of data is used in the current cycle and the number of changes in the use of the j-th type of data in the current cycle relative to the previous cycle ; According to the obtained parameters, a data migration coefficient calculation model is constructed, and the expression is: ； In the formula, is the migration coefficient of the j-th type of data; The working process of the data analysis module also includes: When an external data source Q needs to be uploaded to the system database, the source address A of the external data source to be updated to the system database is obtained; According to the acquired source address A of the external data source Q to be updated to the system database, query the historical records of the source address A uploading the data source to the system database; Get the total number of times source address A uploads data sources to the system database. For a period, obtain the number of times source address A uploads data sources to the system database in each period in the historical time period, and construct a curve of the number of times source address A uploads data sources to the system database in each period in the historical time period over time ; Construct the mathematical model of the safety factor of the external data source Q, the expression is: ； In the formula, , is the weight coefficient, is the initial period of the historical time period, The historical time period ends the cycle, For curve The first derivative of For curve The maximum value of the first-order derivative of For curve The minimum value of the first-order derivative of is the safety factor of the external data source Q.

2. According to claim 1, a government and enterprise data governance system based on business data is characterized in that: The working process of the data analysis module includes: The government and enterprise data sources in the system database are classified into n categories according to their contents. The classification numbers are: 1, 2, ..., i, ..., n, where i belongs to n; Construct a data usage coefficient calculation model, the expression is: ,in, is the coefficient of data usage of the i-th category, is the redundancy index of the i-th type of data, Contribution index for the i-th category of data, and are the corresponding weight coefficients respectively; The calculation expression of the i-th type data redundancy index is: ,in, The time when the i-th type of data is uploaded to the system. The frequency used by the system.

3. According to claim 2, a government and enterprise data governance system based on business data is characterized in that: The method for assigning the i-th type of data contribution index is: The usage frequency of n types of data is counted. When the usage frequency of the i-th type of data ranks in the top one third of all data, then , when the usage frequency of the i-th type of data ranks in the middle third of all data, then , when the usage frequency of the i-th type of data ranks in the last third of all data, then .

4. According to the business data-based government and enterprise data governance system of claim 1, it is characterized in that: The working process of the internal governance module includes: The data usage coefficients of n types of data are calculated in sequence through the data usage coefficient calculation model, and the data usage coefficients of the n types of data are sorted from small to large; The top q ranked data are intercepted as the objects to be migrated, where q belongs to n and j belongs to q; The migration coefficient of the j-th type of data With the migration coefficient threshold set By comparison, if the migration coefficient of the j-th type of data is Less than the set migration coefficient threshold , then the j-th type of data needs to be migrated to the network disk. If the migration coefficient of the j-th type of data is Greater than or equal to the set migration coefficient threshold , then there is no need to migrate the jth type of data to the network disk for the time being.

5. According to claim 1, a government and enterprise data governance system based on business data is characterized in that: The working process of the external governance module includes: The safety factor of the external data source Q With the set safety factor threshold By comparison, if the safety factor of the external data source Q Less than the set safety factor threshold , it means that the security of the external data source Q is poor, and the external data source Q needs to be verified before it can be uploaded to the system database. If the security factor of the external data source Q is Greater than or equal to the set safety factor threshold , it means that the external data source Q has good security.

6. The government and enterprise data governance system based on business data according to any one of claims 1 to 5, characterized in that: The working methods of the governance system include: Step S1: Migrate the data source inside the system database periodically to ensure that when a new external data source is uploaded to the system database, the system database has enough space to receive it; Step S2: When a new external data source is uploaded to the system database, a security assessment is performed on the uploaded external data source.

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