CN105243515B - Enterprise condition management system - Google Patents
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Abstract
The invention relates to the technical field of system management, in particular to an enterprise condition management system. The first acquisition unit is used for acquiring enterprise data of an enterprise user and client data related to the enterprise user; the first storage unit is used for storing enterprise data customer data; the analysis unit is used for obtaining a first structural relationship and/or a second structural relationship of the enterprise data; the structural analysis unit is used for obtaining consumption data related to the enterprise user according to the first structural relationship and/or the second structural relationship; the management unit is used for analyzing the consumption data. The enterprise user operation assisting system has the advantages that characteristics of different data can be analyzed, more accurate analysis results are obtained, enterprise users are helped to automatically obtain data analysis for operation help of the enterprise users through the enterprise condition management system, enterprise cost is reduced, manual operation is reduced, and enterprise efficiency is improved.
Description
Technical Field
The invention relates to the technical field of system management, in particular to an enterprise condition management system.
Background
Enterprises, as main participants of economic activities in the market, are growing with the development of division of labor in society, and popularization of the internet and coming of the big data era, all put forward higher requirements on the enterprises in daily operation management, and require the enterprises to be more intelligent in self management and more efficient in operation efficiency of the enterprises.
The enterprise operation efficiency is improved, comprehensive analysis management needs to be carried out on enterprise conditions, at present, systems for enterprise management only store and simply count data of the systems in a general mode, screening and association relation of a large amount of data is not involved, high-end analysis of data mining cannot be achieved, different methods cannot be adopted for fine analysis of different data, deviation exists between analysis and actual conditions obtained by enterprise users, and therefore help to the enterprise users is limited.
Disclosure of Invention
In order to solve the above problems in the enterprise situation management, an enterprise situation management system capable of adopting different analysis methods according to different data is provided.
The specific technical scheme is as follows:
an enterprise situation management system, comprising:
the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring enterprise data of an enterprise user and client data related to the enterprise user in real time;
the first storage unit is connected with the first acquisition unit and comprises a plurality of mutually independent storage modules, and each storage module is used for storing the enterprise data and the client data related to one enterprise user;
the analysis unit is connected with the first storage unit and used for performing structural analysis on the corresponding relationship among the enterprise data to obtain a first structural relationship related to the enterprise data; and/or
The structure analysis module is used for carrying out structure analysis on the corresponding relation among the data of the customer data to obtain a second structure relation related to the customer data;
the structure analysis unit is connected with the analysis unit and used for analyzing and obtaining consumption data related to the enterprise user according to the first structure relation and/or the second structure relation;
the consumption data includes consumption products and consumption amounts corresponding to consumers of different age groups;
and the management unit is connected with the structure analysis unit and used for analyzing the consumption data and transmitting the analysis result to the enterprise user.
Preferably, in the above-mentioned enterprise situation management system, each of the storage modules includes:
a first storage component for storing the enterprise data;
a second storage section for storing the customer data.
Preferably, the above-mentioned enterprise situation management system includes:
the first storage unit is a MySQL database.
Preferably, the above-mentioned enterprise situation management system includes:
the first semantic unit is connected with the analysis unit and used for performing semantic expansion on the unstructured enterprise data in the analysis unit to obtain first expanded data related to the enterprise data, and the analysis unit performs structural analysis on the corresponding relationship among the data on the first expanded data to obtain a first structural relationship related to the enterprise data;
and the second semantic unit is connected with the analysis unit and used for performing semantic expansion on the unstructured client data in the analysis unit to obtain second expanded data related to the client data, and the analysis unit performs structural analysis on the corresponding relationship among the second expanded data to obtain a second structural relationship related to the client data.
Preferably, in the above-mentioned enterprise situation management system, the structure analysis unit includes:
the first structure module is used for analyzing and obtaining the consumption data of the consumer to the industry associated with the enterprise user according to the first structure relation associated with the enterprise data;
and the second structure module is connected with the first structure module and used for establishing the second structure relationship related to the customer data according to the consumption data related to the industry where the enterprise user is located, and obtaining the consumption data of the consumer to the enterprise user through analysis of the second structure relationship.
Preferably, in the above-mentioned enterprise situation management system, the management unit includes:
the first management module is used for obtaining the purchasing demand data of the consumers in different age groups on the same product according to the consumption data related to the first structure module;
the second management module is used for acquiring the purchasing demand data of the products of the enterprise users of the consumers in different age groups according to the consumption data related to the second structure module;
and the data visualization management module is respectively connected with the first management module and the second management module and is used for displaying the consumption data and the different purchase demand data related to the enterprise user in a visualization mode.
Preferably, the above-mentioned enterprise situation management system, among others,
a second collection unit to collect authentication information associated with the enterprise user;
the second storage unit is connected with the second acquisition unit and used for storing the verification information;
and the verification unit is connected with the second storage unit and used for carrying out identity verification on the enterprise user according to the verification message.
Preferably, the above-mentioned enterprise situation management system further includes:
and the display unit is connected with the management unit and used for displaying and managing the analysis result of the enterprise user.
The invention has the beneficial effects that: the characteristics of the data of difference can be analyzed, the incidence relation between the data is obtained, rapid and deep analysis is carried out on the huge data of number, a more accurate analysis result is obtained, the enterprise user is helped to automatically obtain the data analysis of the enterprise user operation help through the enterprise condition management system, the enterprise cost is reduced, the manual operation is reduced, and the enterprise efficiency is improved.
Drawings
FIG. 1 is a schematic diagram of an overall architecture of an enterprise situation management system in accordance with a preferred embodiment of the present invention;
fig. 2-6 are schematic diagrams of a portion of the enterprise situation management system based on fig. 1 according to a preferred embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
The invention is further described with reference to the following drawings and specific examples, which are not intended to be limiting.
As shown in figure 1 of the drawings, in which,
an enterprise situation management system, comprising:
the system comprises a first acquisition unit 1, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring enterprise data of enterprise users and client data related to the enterprise users in real time;
the first storage unit 2 is connected with the first acquisition unit 1, the first storage unit 2 comprises a plurality of mutually independent storage modules 210, and each storage module 210 is used for storing enterprise data and client data related to one enterprise user;
the analysis unit 3 is connected with the first storage unit 2 and used for performing structural analysis on the corresponding relationship among the data of the enterprise data to obtain a first structural relationship related to the enterprise data; and/or
The structure analysis module is used for carrying out structure analysis on the corresponding relation among the data of the client data to obtain a second structure relation related to the client data;
the structure analysis unit 4 is connected with the analysis unit 3 and is used for analyzing and obtaining consumption data related to the enterprise users according to the first structure relationship and/or the second structure relationship;
the consumption data includes consumption products and consumption amounts corresponding to consumers of different age groups;
and the management unit 5 is connected with the structure analysis unit 4 and used for analyzing the consumption data and transmitting the analysis result to the enterprise user.
In the embodiment, the enterprise situation management system collects enterprise data of enterprise users and client data related to the enterprise users through a first collection unit 1; the enterprise data is used for reflecting the enterprise users and industry basic information related to the enterprise users in real time, and the industry basic information can be conventional classification in the industry, for example, in the clothing industry, the conventional classification is as follows: clothing, pants, skirts, coats, undergarments, and the like; the customer data is used for reflecting the product types and product click numbers of consumers in different age groups in real time; the enterprise data and the client data related to an enterprise user are stored in the independent storage module 210 in the first storage unit 2, and the parsing unit 3 performs structure parsing on the structured data in the enterprise data and the client data respectively according to the corresponding relationship between the data to obtain a structural relationship, for example, the structured data with the corresponding relationship is summarized in a same table to form a certain corresponding structural relationship.
For example, the enterprise data of the enterprise user for making women's clothes, in which the total sales amount of clothes and the respective sales amounts of jacket and trousers sold respectively form a corresponding relationship, the total sales amount of clothes and the respective sales amounts of clothes in four seasons style form a corresponding relationship, and the respective sales amounts of jacket and trousers sold and the respective sales amounts of clothes in four seasons style form a corresponding relationship, is obtained as a structural relationship based on the total sales amount by the corresponding relationship with the sales amounts of the different clothes. Similarly, for example, the customer data, the corresponding relationship between the total number of the customers and the number of the customers in different age stages, the corresponding relationship between the different age stages and the types of the purchased products, and the corresponding relationship between the different age stages and the number of the purchased products, a structural relationship based on the total number of the customers is obtained through the corresponding relationship between the different purchase demands of the customers.
After obtaining the relevant structure relationship of the enterprise user, consumption data related to the enterprise user, such as the number of consumer groups and sales number corresponding to a certain product of the enterprise user, is obtained through the structure analysis unit 4. The management unit 5 compares the quantity with the yield of the enterprise user to obtain a result of the supply-demand relationship between the yield and the sales, and sends the result to the enterprise user so that the enterprise user can adjust the operation.
In a preferred embodiment, as shown in FIG. 2, the memory block comprises:
a first storage section 211 for storing user information of an enterprise user;
and a second storage component 212 for storing customer data corresponding to the enterprise user.
Two storage components are arranged to store the obtained data of the enterprise users respectively, so that the independence of the data is guaranteed, and the data can be called conveniently.
On the basis of the above technical solution, the first storage unit 2 is a MySQL database.
Each storage component in the storage unit uses a database management system MySQL, and the overall cost of the system is reduced by utilizing the characteristics of small volume, high speed and low overall cost.
In a preferred embodiment, as shown in fig. 3, the method comprises:
the first semantic unit 6 is connected with the analysis unit 3 and used for performing semantic expansion on unstructured enterprise data in the analysis unit 3 to obtain first expanded data related to the enterprise data, and the analysis unit 3 performs structural analysis on the corresponding relationship among the data on the first expanded data to obtain a first structural relationship related to the enterprise data;
and the second semantic unit 7 is connected with the analysis unit 3 and is used for performing semantic expansion on unstructured client data in the analysis unit 3 to obtain second expanded data related to the client data, and the analysis unit 3 performs structural analysis on the corresponding relationship among the data on the second expanded data to obtain a second structural relationship related to the client data.
The first semantic unit 6 and the second semantic unit 7 perform semantic expansion on unstructured data which cannot form corresponding relations with other data in enterprise data and client data of enterprise users, for example, in the enterprise data, semantic expansion can be performed on an accessory waistband of clothing, a brooch and the like, for example, the waistband expansion corresponds to trousers, the brooch corresponds to a coat and the like; because the semantic expansion is the common knowledge of people in the field, the semantic annotation processing is carried out on the data, so that the natural language has a semantic logical relationship, and the wide and effective semantic reasoning can be carried out in a network environment, thereby ensuring that the system more accurately and comprehensively determines the corresponding relationship between the data, and not carrying out detailed description on the semantic expansion; in the system, the extended data deduced by semantic reasoning is sent back to the analysis unit 3, so that the analysis unit 3 is helped to obtain a first structural relationship through the corresponding extended data and the enterprise data and obtain a second structural relationship through the corresponding extended data and the client data.
In a preferred embodiment, as shown in fig. 4, the structure analysis unit 4 includes:
the first structure module 401 is configured to obtain consumption data of the industry in which the consumer is associated with the enterprise user according to a first structural relationship analysis related to the enterprise data;
and the second structure module 402 is connected to the first structure module 401, and is configured to establish a second structure relationship associated with the customer data according to the consumption data associated with the industry where the enterprise user is located, and obtain the consumption data of the enterprise user by the consumer through second structure relationship analysis.
The first structure module 401 is configured to obtain consumption data of the consumer on the industry where the enterprise user is located after obtaining the first structure relationship according to the parsing unit 3, where the consumption data related to the same row is mainly consumption demand of consumers in different age groups on products in the industry.
The second structure module 402 is configured to obtain the consumption data of the consumer on the product of the enterprise user by combining the first structure relationship after obtaining the second structure relationship according to the parsing unit 3, where the consumption data is mainly the consumption demand of the consumers of different ages on the product of the enterprise user.
Fig. 5 is a schematic structural diagram of the present invention, which includes a management unit, a structural analysis unit and a display unit.
In a preferred embodiment, as shown in fig. 5, the management unit 5 includes:
a first management module 501, configured to obtain purchase demand data of consumers of different ages for the same product according to the consumption data associated with the first structure module 401;
a second management module 502, configured to obtain purchase demand data of products of enterprise users from consumers of different ages according to the consumption data associated with the second structure module 402;
the data visualization management module 503 is respectively connected to the first management module 501 and the second management module 502, and is configured to display consumption data and different purchase demand data associated with the enterprise user in a visualization manner.
The first management module 501 obtains the purchase demand of different consumers for products in the same industry, that is, the predicted demand of products in the same industry in the market according to the consumption data, for example, in the above clothing case, the sales of the hemp skirts for different consumption in the whole year is 1 ten thousand, and the sales in spring and summer is 8 thousand, and the predicted demand of the hemp skirts for spring and summer in the next year is 7 thousand to 1 ten thousand; the second management module 502 obtains the purchase demand of the product of the enterprise user according to the consumption data, that is, the predicted demand amount of the product of the enterprise user in the market, for example, on the basis of the prediction of the hemp skirt, the enterprise user obtains fifty percent of the total sales amount of the enterprise user in the total industry according to the system, and finds that the sales amount of the hemp skirt in spring and summer of the year is only thirty percent of the total sales amount of the industry according to the consumption data, and according to the data analysis, if the production amount is insufficient, the production amount of the hemp skirt can be increased in the production task of the next year; the data visualization management module 503 displays the predicted demand obtained by the management module to enterprise users in a visualization manner, where the visualization manner may be specifically expressed in forms, specifications, materials, colors, fonts, legends, examples, and the like, so as to achieve standardization of visualization management, and to embody objects to be managed in a clear manner.
In a preferred embodiment, as shown in fig. 6, including,
a second collecting unit 8 for collecting authentication information associated with the enterprise user;
the second storage unit 9 is connected with the second acquisition unit 8 and used for storing the verification information;
and the verification unit 10 is connected with the second storage unit 9 and used for performing identity verification on the enterprise user according to the verification message.
The enterprise user logs in the system through identity authentication, and the system acquires authentication information of the enterprise user, wherein the authentication information of the enterprise user comprises a system login password, an enterprise registration address, an enterprise operation address and the like; when an enterprise user logs in the system, authentication information needs to be input, the authentication unit 10 compares the input authentication information with the stored authentication information, if the input authentication information conforms to the stored authentication information, the enterprise user passes through identity authentication and can log in the system smoothly, otherwise, the enterprise user cannot pass through identity authentication and can not log in the system.
In the preferred embodiment, as shown in fig. 5, based on the above contents, the management unit is further connected to a display unit 11, which is connected to the management unit 5, for displaying the analysis result of the enterprise user.
In the clothing example, the enterprise user produces one hundred skirts for consumers in the age range of 20 to 30 years in advance, but the sales volume of the age range is up to 50 according to the data, and the comparison result is sent to the enterprise user so that the enterprise user can adjust the operation, for example, the production of the skirts is reduced to achieve the supply and demand balance.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.
Claims (5)
1. An enterprise situation management system, comprising:
the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring enterprise data of an enterprise user and client data related to the enterprise user in real time;
the first storage unit is connected with the first acquisition unit and comprises a plurality of mutually independent storage modules, and each storage module is used for storing the enterprise data and the client data related to one enterprise user;
the analysis unit is connected with the first storage unit and used for performing structural analysis on the corresponding relationship among the enterprise data to obtain a first structural relationship related to the enterprise data; and/or
The structure analysis module is used for carrying out structure analysis on the corresponding relation among the data of the customer data to obtain a second structure relation related to the customer data;
the structure analysis unit is connected with the analysis unit and used for analyzing and obtaining consumption data related to the enterprise user according to the first structure relation and/or the second structure relation;
the consumption data includes consumption products and consumption amounts corresponding to consumers of different age groups;
the management unit is connected with the structure analysis unit and used for analyzing the consumption data and transmitting an analysis result to the enterprise user;
each of the storage modules includes:
a first storage component for storing the enterprise data;
second storage means for storing the customer data;
the first storage unit is a MySQL database;
the first semantic unit is connected with the analysis unit and used for performing semantic expansion on the unstructured enterprise data in the analysis unit to obtain first expanded data related to the enterprise data, and the analysis unit performs structural analysis on the corresponding relationship among the data on the first expanded data to obtain a first structural relationship related to the enterprise data;
and the second semantic unit is connected with the analysis unit and used for performing semantic expansion on the unstructured client data in the analysis unit to obtain second expanded data related to the client data, and the analysis unit performs structural analysis on the corresponding relationship among the second expanded data to obtain a second structural relationship related to the client data.
2. The enterprise situation management system of claim 1, wherein said structural analysis unit comprises:
the first structure module is used for analyzing and obtaining the consumption data of the consumer to the industry associated with the enterprise user according to the first structure relation associated with the enterprise data;
and the second structure module is connected with the first structure module and used for establishing the second structure relationship related to the customer data according to the consumption data related to the industry where the enterprise user is located, and obtaining the consumption data of the consumer to the enterprise user through analysis of the second structure relationship.
3. The enterprise situation management system of claim 2, wherein said management unit comprises:
the first management module is used for obtaining the purchasing demand data of the consumers in different age groups on the same product according to the consumption data related to the first structure module;
the second management module is used for acquiring the purchasing demand data of the products of the enterprise users of the consumers in different age groups according to the consumption data related to the second structure module;
and the data visualization management module is respectively connected with the first management module and the second management module and is used for displaying the consumption data and the different purchase demand data related to the enterprise user in a visualization mode.
4. The enterprise situation management system of claim 1, comprising,
a second collection unit to collect authentication information associated with the enterprise user;
the second storage unit is connected with the second acquisition unit and used for storing the verification information;
and the verification unit is connected with the second storage unit and used for carrying out identity verification on the enterprise user according to the verification message.
5. The enterprise situation management system of claim 1, further comprising:
and the display unit is connected with the management unit and used for displaying and managing the analysis result of the enterprise user.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101452471A (en) * | 2007-12-03 | 2009-06-10 | 国际商业机器公司 | Web 2.0 system and method for dynamic categorization of heterogeneous and regulated enterprise assets |
| CN102436506A (en) * | 2011-12-27 | 2012-05-02 | Tcl集团股份有限公司 | Mass data processing method and device for network server |
| CN102693498A (en) * | 2012-05-16 | 2012-09-26 | 上海卓达信息技术有限公司 | Accurate recommendation method based on incomplete data |
| CN103295148A (en) * | 2012-02-27 | 2013-09-11 | 埃森哲环球服务有限公司 | Digital consumer data model and customer analytic record |
| CN103678659A (en) * | 2013-12-24 | 2014-03-26 | 焦点科技股份有限公司 | E-commerce website cheat user identification method and system based on random forest algorithm |
| CN103714139A (en) * | 2013-12-20 | 2014-04-09 | 华南理工大学 | Parallel data mining method for identifying a mass of mobile client bases |
| CN104732425A (en) * | 2015-03-24 | 2015-06-24 | 浪潮集团有限公司 | E-commerce platform customer behavior analytical method based on big data |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AUPQ283599A0 (en) * | 1999-09-15 | 1999-10-07 | Express Promotions Australia Pty Ltd | Account services system and process |
| CN101149829A (en) * | 2006-09-22 | 2008-03-26 | 阿里巴巴公司 | Client data centralized processing method and system |
| CN102163205A (en) * | 2010-02-21 | 2011-08-24 | 施章祖 | Automatic excavation system for analogous customer groups |
| CN104574127B (en) * | 2013-10-21 | 2018-07-06 | 北京中海纪元数字技术发展股份有限公司 | innovative marketing platform |
| CN104732311A (en) * | 2013-12-23 | 2015-06-24 | 北京索为高科系统技术有限公司 | Enterprise data management system based on unified data models |
| CN104182389B (en) * | 2014-07-21 | 2018-01-19 | 安徽华贞信息科技有限公司 | A kind of big data analyzing business intelligence service system based on semanteme |
-
2015
- 2015-11-09 CN CN201510759961.5A patent/CN105243515B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101452471A (en) * | 2007-12-03 | 2009-06-10 | 国际商业机器公司 | Web 2.0 system and method for dynamic categorization of heterogeneous and regulated enterprise assets |
| CN102436506A (en) * | 2011-12-27 | 2012-05-02 | Tcl集团股份有限公司 | Mass data processing method and device for network server |
| CN103295148A (en) * | 2012-02-27 | 2013-09-11 | 埃森哲环球服务有限公司 | Digital consumer data model and customer analytic record |
| CN102693498A (en) * | 2012-05-16 | 2012-09-26 | 上海卓达信息技术有限公司 | Accurate recommendation method based on incomplete data |
| CN103714139A (en) * | 2013-12-20 | 2014-04-09 | 华南理工大学 | Parallel data mining method for identifying a mass of mobile client bases |
| CN103678659A (en) * | 2013-12-24 | 2014-03-26 | 焦点科技股份有限公司 | E-commerce website cheat user identification method and system based on random forest algorithm |
| CN104732425A (en) * | 2015-03-24 | 2015-06-24 | 浪潮集团有限公司 | E-commerce platform customer behavior analytical method based on big data |
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