CN116628086A - Visual application data sharing method and system - Google Patents
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Abstract
The application relates to the technical field of enterprise digitization, and provides a method and a system for sharing visual application data, wherein the method comprises the following steps: acquiring enterprise application data based on the enterprise basic information to obtain an application data acquisition result; preprocessing the application data acquisition result to obtain an application data processing result; performing cluster analysis on the application data processing result, and identifying the application data cluster analysis result to obtain a plurality of attribute data sets; performing visual mapping on the plurality of attribute data sets to obtain a plurality of attribute data visual mapping results; and constructing a data sharing display platform, and inputting a plurality of attribute data visualization mapping results into the data sharing display platform for data sharing. The method can solve the problem of low working efficiency of staff due to low transparency of enterprise data, and can improve the transparency of the enterprise data, thereby improving the working efficiency of the staff.
Description
Technical Field
The application relates to the technical field of enterprise digitization, in particular to a visual application data sharing method and a system.
Background
As enterprise application data size and variety increases, more and more enterprises and organizations begin to appreciate the importance of data sharing. As an important informatization means, data sharing has become one of important ways for enterprises to acquire, utilize and create value, and can help the enterprises to better utilize own data resources and improve the value and competitiveness of the data. At present, when enterprise application data is subjected to data sharing, the situation of low transparency of data sharing often occurs due to low digitization level, so that office efficiency of enterprise staff is affected.
In summary, the problem of low staff work efficiency caused by low transparency of enterprise data in the prior art exists.
Disclosure of Invention
Accordingly, it is necessary to provide a method and a system for sharing visual application data in order to solve the above-mentioned technical problems.
A method of visualizing application data sharing, the method comprising: acquiring enterprise application data based on the enterprise basic information to obtain an application data acquisition result; preprocessing the application data acquisition result to obtain an application data processing result; performing cluster analysis on the application data processing result, and identifying the application data cluster analysis result to obtain a plurality of attribute data sets; performing visual mapping on the plurality of attribute data sets to obtain a plurality of attribute data visual mapping results; and constructing a data sharing display platform, and inputting a plurality of attribute data visualization mapping results into the data sharing display platform for data sharing.
In one embodiment, further comprising: performing data deduplication on the application data acquisition result to obtain an application data deduplication result; performing outlier rejection on the application data deduplication result to obtain a first application data processing result; filling missing data in the first application data processing result to obtain the application data processing result.
In one embodiment, further comprising: randomly selecting K cluster center points from the application data processing result, wherein K is an integer greater than or equal to 3; then calculating the distance between each data in the application data processing result and the central points of K clusters, and distributing the distances to the clusters closest to each other; re-calculating the center point of each cluster, and re-distributing each data in the application data processing result; and presetting iteration times, and obtaining a clustering analysis result when the data clustering iteration times meet the preset iteration times.
In one embodiment, further comprising: extracting attribute characteristics of the data cluster analysis result to obtain a plurality of cluster attribute characteristics; setting a plurality of data attribute tags according to a plurality of the cluster attribute features; and identifying the data sets in the data cluster analysis result according to the data attribute tags to obtain a plurality of attribute data sets.
In one embodiment, further comprising: obtaining a plurality of data visualization mapping modes; constructing a data mapping matching table based on historical visual mapping data, and embedding a plurality of data visual mapping modes into the data mapping matching table; inputting a plurality of attribute data sets into the data mapping matching table to match the mapping modes, and obtaining an adaptive mapping mode; and performing visual mapping on the attribute data sets based on the adaptive mapping mode to obtain visual mapping results of the attribute data sets.
In one embodiment, further comprising: presetting a data sharing rule, wherein the data sharing rule comprises a data sharing range, user level setting, data acquisition permission and display module setting, and the user level setting and the data acquisition permission have a corresponding relationship; constructing an interface and a functional module of the data sharing display platform based on the preset data sharing rule to obtain the data sharing display platform; and inputting the plurality of attribute data visualization mapping results into corresponding data display modules in the data sharing display platform for data sharing.
In one embodiment, further comprising: user grade division is carried out according to the personnel grade of the enterprise, and a plurality of user grades are obtained; setting data acquisition permission according to a plurality of user grades; and presetting a user grade updating period, and updating the user grade through the user grade updating period.
A visualization application data sharing system, comprising:
the application data acquisition result acquisition module is used for acquiring enterprise application data based on the enterprise basic information to acquire an application data acquisition result;
the application data processing result obtaining module is used for preprocessing the application data acquisition result to obtain an application data processing result;
the attribute data set obtaining module is used for carrying out cluster analysis on the application data processing results and identifying the application data cluster analysis results to obtain a plurality of attribute data sets;
the visual mapping module is used for performing visual mapping on the plurality of attribute data sets to obtain a plurality of attribute data visual mapping results;
and the data display sharing module is used for constructing a data sharing display platform, and inputting a plurality of attribute data visualization mapping results into the data sharing display platform for data sharing.
The visual application data sharing method and the visual application data sharing system can solve the problem of low working efficiency of staff due to low transparency of enterprise data, and acquire application data acquisition results by acquiring enterprise application data based on enterprise basic information; preprocessing the application data acquisition result to obtain an application data processing result; performing cluster analysis on the application data processing result, and identifying the application data cluster analysis result to obtain a plurality of attribute data sets; performing visual mapping on the plurality of attribute data sets to obtain a plurality of attribute data visual mapping results; and constructing a data sharing display platform, and inputting a plurality of attribute data visualization mapping results into the data sharing display platform for data sharing. By the method, the transparency of enterprise data can be improved, so that the working efficiency of staff is improved.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
FIG. 1 is a schematic flow chart of a method for sharing visual application data;
FIG. 2 is a schematic flow chart of a method for obtaining application data processing results in a visual application data sharing method;
FIG. 3 is a schematic flow chart of a clustering analysis result obtained in a visualized application data sharing method;
fig. 4 is a schematic structural diagram of a visual application data sharing system according to the present application.
Reference numerals illustrate: the system comprises an application data acquisition result obtaining module 1, an application data processing result obtaining module 2, an attribute data set obtaining module 3, a visual mapping module 4 and a data display sharing module 5.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
As shown in fig. 1, the present application provides a method for sharing visual application data, which includes:
step S100: acquiring enterprise application data based on the enterprise basic information to obtain an application data acquisition result;
specifically, data automation acquisition is performed on application data of an enterprise according to enterprise operation information, the enterprise application data comprises various data such as enterprise user data, enterprise system data, enterprise employee data, third party data, equipment data and the like, an application data acquisition result is obtained, and support is provided for visual display of the next enterprise application data by obtaining the application data acquisition result.
Step S200: preprocessing the application data acquisition result to obtain an application data processing result;
as shown in fig. 2, in one embodiment, step S200 of the present application further includes:
step S210: performing data deduplication on the application data acquisition result to obtain an application data deduplication result;
step S220: performing outlier rejection on the application data deduplication result to obtain a first application data processing result;
step S230: filling missing data in the first application data processing result to obtain the application data processing result.
Specifically, an enterprise application data acquisition result is obtained, and data deduplication processing is firstly carried out on the application data acquisition result, wherein the data deduplication processing refers to removing repeated data in the application data acquisition result, only one piece of valuable data is reserved, and an application data deduplication result is obtained. And then, removing abnormal data from the application data insect expelling result, wherein the abnormal data is data which does not accord with normal theory or has larger difference value between the data, and obtaining a first application data processing result. And finally, filling the missing data of the first application data processing result, wherein the filling of the missing data refers to supplementing the data according to the correlation between the front and rear adjacent data of the data, and the application data processing result is obtained. The data deduplication, outlier rejection and missing data filling processing are carried out on the application data acquisition result, so that the redundancy degree of the data can be reduced, the accuracy of the data can be improved, and the subsequent processing time of the data can be shortened.
Step S300: performing cluster analysis on the application data processing result, and identifying the application data cluster analysis result to obtain a plurality of attribute data sets;
as shown in fig. 3, in one embodiment, the step S300 of the present application further includes:
step S310: randomly selecting K cluster center points from the application data processing result, wherein K is an integer greater than or equal to 3;
step S320: then calculating the distance between each data in the application data processing result and the central points of K clusters, and distributing the distances to the clusters closest to each other;
step S330: re-calculating the center point of each cluster, and re-distributing each data in the application data processing result;
step S340: and presetting iteration times, and obtaining a clustering analysis result when the data clustering iteration times meet the preset iteration times.
Specifically, cluster analysis is performed on the application data processing result through a cluster analysis algorithm, and K cluster center points are randomly selected from the application data processing result, wherein a random selection method can be selected through a random mode of roulette, and K is an integer greater than or equal to 3. Then calculating the distance between each data in the application data processing result and the central points of K clusters, and distributing the data to the clusters closest to the data; iterative selection is then continued, the center point of each cluster is recalculated, and the application data is reassigned to the cluster closest to it. The number of cluster iterations is preset, which can be set by a person skilled in the art in a user-defined manner based on the actual situation. And when the data clustering iteration number is equal to the preset iteration number, obtaining a clustering analysis result of the application data processing result. The clustering algorithm is utilized to perform clustering analysis on the application data processing result, so that data can be automatically grouped, and the efficiency of data analysis is improved.
In one embodiment, the step S300 of the present application further includes:
step S350: extracting attribute characteristics of the data cluster analysis result to obtain a plurality of cluster attribute characteristics;
step S360: setting a plurality of data attribute tags according to a plurality of the cluster attribute features;
step S370: and identifying the data sets in the data cluster analysis result according to the data attribute tags to obtain a plurality of attribute data sets.
Specifically, firstly, extracting attribute features from the data cluster analysis result, wherein the attribute features are functions and roles of data characterization, such as: and obtaining a plurality of clustering attribute characteristics by a plurality of attributes such as employee information, enterprise operation data, enterprise system and the like. And then setting a plurality of data attribute tags according to the plurality of clustering attribute features, wherein the data attribute tags are used for expressing the functions of the clustering attribute features. And finally, identifying the data sets in the data clustering analysis result according to a plurality of data attribute tags, for example, enterprise expenditure data, enterprise receivability data, enterprise accounts receivable and the like, and obtaining a plurality of attribute data sets. By obtaining multiple attribute data sets, data support is provided for the next step of attribute data visualization presentation.
Step S400: performing visual mapping on the plurality of attribute data sets to obtain a plurality of attribute data visual mapping results;
in one embodiment, step S400 of the present application further includes:
step S410: obtaining a plurality of data visualization mapping modes;
step S420: constructing a data mapping matching table based on historical visual mapping data, and embedding a plurality of data visual mapping modes into the data mapping matching table;
step S430: inputting a plurality of attribute data sets into the data mapping matching table to match the mapping modes, and obtaining an adaptive mapping mode;
step S440: and performing visual mapping on the attribute data sets based on the adaptive mapping mode to obtain visual mapping results of the attribute data sets.
Specifically, a plurality of data visualization mapping modes are obtained, wherein the data visualization mapping modes are used for performing visualization display on data, for example: bar graph, data table, line graph, relation graph, histogram and other data expression modes.
And carrying out data search and inquiry based on a big data technology to obtain a plurality of historical visual mapping data, wherein the historical visual mapping data comprise data types and corresponding visual mapping modes, a data mapping matching table is constructed based on a BP neural network, and the data mapping matching table is a neural network model which can be subjected to continuous iterative optimization in machine learning and is obtained by carrying out supervision training through a training data set. Constructing a sample data set according to the historical visual mapping data, and dividing the sample data set into a data training set and a data verification set according to a data dividing proportion, wherein the data dividing proportion can be set in a self-defined way by a person skilled in the art, for example: 80%, 20%. And performing supervision training on the data mapping matching table through the sample training set, verifying the data mapping matching table through the data verification set when the accuracy of the output result tends to be in a convergence state, obtaining the data mapping matching table when the accuracy of the verification result reaches a preset index, and then embedding a plurality of data visualization mapping modes into the data mapping matching table.
And inputting a plurality of attribute data sets into the data mapping matching table to perform mapping mode matching to obtain an adaptive mapping mode, and performing visual mapping on the attribute data sets according to the adaptive mapping mode, wherein visual mapping can be performed through various tools such as Tableau, power BI and the like to obtain visual mapping results of the attribute data. For example: when the data management trend is analyzed, the data can be displayed in a line graph mode. The visual mapping result of the attribute data is obtained, so that the data can be clearly and intuitively displayed, and the working efficiency is improved.
Step S500: and constructing a data sharing display platform, and inputting a plurality of attribute data visualization mapping results into the data sharing display platform for data sharing.
In one embodiment, step S500 of the present application further includes:
step S510: presetting a data sharing rule, wherein the data sharing rule comprises a data sharing range, user level setting, data acquisition permission and display module setting, and the user level setting and the data acquisition permission have a corresponding relationship;
in one embodiment, step S510 of the present application further includes:
step S511: user grade division is carried out according to the personnel grade of the enterprise, and a plurality of user grades are obtained;
step S512: setting data acquisition permission according to a plurality of user grades;
step S513: and presetting a user grade updating period, and updating the user grade through the user grade updating period.
Specifically, a data sharing rule is preset, wherein the data sharing rule comprises a data sharing range, user level settings, data acquisition rights and display module settings. The data sharing range refers to non-privacy data meeting the working requirements, the user level refers to a display module used for setting different user levels, and the display module is used for setting a display interface according to data attributes and functions, wherein the user level setting and the data acquisition permission are in one-to-one correspondence.
Firstly, acquiring enterprise personnel levels according to basic information of an enterprise, wherein the enterprise personnel levels refer to different positions in the enterprise, for example: and (3) carrying out user grade division on the enterprise total manager, the department manager, the common staff and the like according to the enterprise staff grade to obtain a plurality of user grades, for example: first-level of enterprise total manager, third-level of department total manager, etc. And then setting data acquisition permission according to a plurality of user grades, wherein the data acquisition permission refers to permission for acquiring enterprise sharing display data. For example: the department manager has the right to acquire all data, and the department manager has the right to acquire all data of the department. A preset user level update period, which can be set by a person skilled in the art in a user-defined manner, for example: for 1 month. And updating the user level according to the user level updating period, so that the flexibility of setting the data acquisition permission can be improved.
Step S520: constructing an interface and a functional module of the data sharing display platform based on the preset data sharing rule to obtain the data sharing display platform;
step S530: and inputting the plurality of attribute data visualization mapping results into corresponding data display modules in the data sharing display platform for data sharing.
Specifically, an interface and a functional module of the data sharing display platform are built on an enterprise internal website according to the preset data sharing rule, and the data sharing display platform is obtained. And finally, inputting the plurality of attribute data visualization mapping results into corresponding data display modules in the data sharing display platform for data sharing. The method solves the problem of low working efficiency of staff due to low transparency of enterprise data, and can improve the transparency of the enterprise data, thereby improving the working efficiency of the staff.
In one embodiment, as shown in fig. 4, there is provided a digital twin-based fresh meat proportioning process management system, comprising: an application data acquisition result obtaining module 1, an application data processing result obtaining module 2, an attribute data set obtaining module 3, a visual mapping module 4, a data display sharing module 5, wherein:
the application data acquisition result acquisition module 1 is used for acquiring enterprise application data based on enterprise basic information to acquire an application data acquisition result;
the application data processing result obtaining module 2 is used for preprocessing the application data acquisition result to obtain an application data processing result;
the attribute data set obtaining module 3 is used for carrying out cluster analysis on the application data processing result and identifying the application data cluster analysis result to obtain a plurality of attribute data sets;
the visual mapping module 4 is used for performing visual mapping on the plurality of attribute data sets to obtain a plurality of attribute data visual mapping results;
the data display sharing module 5 is used for constructing a data sharing display platform, and inputting a plurality of attribute data visualization mapping results into the data sharing display platform for data sharing.
In one embodiment, the system further comprises:
the data deduplication module is used for performing data deduplication on the application data acquisition result to obtain an application data deduplication result;
the abnormal value removing module is used for removing abnormal values from the application data duplicate removal result to obtain a first application data processing result;
and the missing data filling module is used for filling the missing data of the first application data processing result to obtain the application data processing result.
In one embodiment, the system further comprises:
the cluster center point selection module is used for randomly selecting K cluster center points from the application data processing result, wherein K is an integer greater than or equal to 3;
the data distribution module is used for calculating the distance between each data in the application data processing result and the central points of K clusters and distributing the distances to the clusters closest to each data;
the data redistribution module is used for recalculating the center point of each cluster and redistributing each data in the application data processing result;
the cluster analysis result obtaining module is used for presetting iteration times and obtaining a cluster analysis result when the data cluster iteration times meet the preset iteration times.
In one embodiment, the system further comprises:
the feature extraction module is used for extracting attribute features of the data cluster analysis result to obtain a plurality of cluster attribute features;
the data attribute tag setting module is used for setting a plurality of data attribute tags according to a plurality of clustering attribute features;
the attribute data set obtaining module is used for identifying the data sets in the data cluster analysis result according to a plurality of data attribute tags to obtain a plurality of attribute data sets.
In one embodiment, the system further comprises:
the data visual mapping mode obtaining module is used for obtaining a plurality of data visual mapping modes;
the data mapping matching table construction module is used for constructing a data mapping matching table based on historical visual mapping data and embedding a plurality of data visual mapping modes into the data mapping matching table;
the adaptation mapping mode obtaining module is used for inputting a plurality of attribute data sets into the data mapping matching table to carry out mapping mode matching so as to obtain an adaptation mapping mode;
the visual mapping result obtaining module is used for carrying out visual mapping on the attribute data sets based on the adaptive mapping mode to obtain visual mapping results of the attribute data.
In one embodiment, the system further comprises:
the data sharing rule presetting module is used for presetting data sharing rules, wherein the data sharing rules comprise a data sharing range, user level settings, data acquisition rights and display module settings, and the user level settings and the data acquisition rights have corresponding relations;
the data sharing display platform obtaining module is used for constructing an interface and a functional module of the data sharing display platform based on the preset data sharing rule to obtain the data sharing display platform;
and the data sharing module is used for inputting the plurality of attribute data visualization mapping results into the corresponding data display modules in the data sharing display platform to carry out data sharing.
In one embodiment, the system further comprises:
the user grade obtaining module is used for carrying out user grade division according to the personnel grade of the enterprise to obtain a plurality of user grades;
the digital sharing authority setting module is used for setting data acquisition authorities according to a plurality of user grades;
and the user level updating module is used for presetting a user level updating period and updating the user level according to the user level updating period.
In summary, the present application provides a method and a system for sharing visual application data, which have the following technical effects:
the method solves the problem of low working efficiency of staff due to low transparency of enterprise data, and can improve the transparency of the enterprise data, thereby improving the working efficiency of the staff. The data deduplication, outlier rejection and missing data filling processing are carried out on the application data acquisition result, so that the redundancy degree of the data can be reduced, the accuracy of the data can be improved, and the subsequent processing time of the data can be shortened. The clustering algorithm is utilized to perform clustering analysis on the application data processing result, so that data can be automatically grouped, and the efficiency of data analysis is improved.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (8)
1. A method for sharing visual application data, the method comprising:
acquiring enterprise application data based on the enterprise basic information to obtain an application data acquisition result;
preprocessing the application data acquisition result to obtain an application data processing result;
performing cluster analysis on the application data processing result, and identifying the application data cluster analysis result to obtain a plurality of attribute data sets;
performing visual mapping on the plurality of attribute data sets to obtain a plurality of attribute data visual mapping results;
and constructing a data sharing display platform, and inputting a plurality of attribute data visualization mapping results into the data sharing display platform for data sharing.
2. The method of claim 1, wherein preprocessing the application data acquisition result to obtain an application data processing result, further comprises:
performing data deduplication on the application data acquisition result to obtain an application data deduplication result;
performing outlier rejection on the application data deduplication result to obtain a first application data processing result;
filling missing data in the first application data processing result to obtain the application data processing result.
3. The method of claim 1, wherein the clustering analysis of the application data processing results further comprises:
randomly selecting K cluster center points from the application data processing result, wherein K is an integer greater than or equal to 3;
then calculating the distance between each data in the application data processing result and the central points of K clusters, and distributing the distances to the clusters closest to each other;
re-calculating the center point of each cluster, and re-distributing each data in the application data processing result;
and presetting iteration times, and obtaining a clustering analysis result when the data clustering iteration times meet the preset iteration times.
4. The method of claim 3, wherein the combining identifies the application data cluster analysis results to obtain a plurality of attribute data sets, further comprising:
extracting attribute characteristics of the data cluster analysis result to obtain a plurality of cluster attribute characteristics;
setting a plurality of data attribute tags according to a plurality of the cluster attribute features;
and identifying the data sets in the data cluster analysis result according to the data attribute tags to obtain a plurality of attribute data sets.
5. The method of claim 1, wherein the performing the visual mapping on the plurality of attribute data sets to obtain a plurality of attribute data visual mapping results, further comprises:
obtaining a plurality of data visualization mapping modes;
constructing a data mapping matching table based on historical visual mapping data, and embedding a plurality of data visual mapping modes into the data mapping matching table;
inputting a plurality of attribute data sets into the data mapping matching table to match the mapping modes, and obtaining an adaptive mapping mode;
and performing visual mapping on the attribute data sets based on the adaptive mapping mode to obtain visual mapping results of the attribute data sets.
6. The method of claim 1, wherein the constructing a data sharing display platform, inputting a plurality of the attribute data visualization mapping results into the data sharing display platform for data sharing, further comprises:
presetting a data sharing rule, wherein the data sharing rule comprises a data sharing range, user level setting, data acquisition permission and display module setting, and the user level setting and the data acquisition permission have a corresponding relationship;
constructing an interface and a functional module of the data sharing display platform based on the preset data sharing rule to obtain the data sharing display platform;
and inputting the plurality of attribute data visualization mapping results into corresponding data display modules in the data sharing display platform for data sharing.
7. The method of claim 6, wherein the method further comprises:
user grade division is carried out according to the personnel grade of the enterprise, and a plurality of user grades are obtained;
setting data acquisition permission according to a plurality of user grades;
and presetting a user grade updating period, and updating the user grade through the user grade updating period.
8. A visualization application data sharing system, the system comprising:
the application data acquisition result acquisition module is used for acquiring enterprise application data based on the enterprise basic information to acquire an application data acquisition result;
the application data processing result obtaining module is used for preprocessing the application data acquisition result to obtain an application data processing result;
the attribute data set obtaining module is used for carrying out cluster analysis on the application data processing results and identifying the application data cluster analysis results to obtain a plurality of attribute data sets;
the visual mapping module is used for performing visual mapping on the plurality of attribute data sets to obtain a plurality of attribute data visual mapping results;
and the data display sharing module is used for constructing a data sharing display platform, and inputting a plurality of attribute data visualization mapping results into the data sharing display platform for data sharing.
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