CN112257001A - Education decision-making system based on big data analysis - Google Patents
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Abstract
The invention discloses an education decision system based on big data analysis, which belongs to the technical field of data analysis decision systems and comprises a PC (personal computer) end, a mobile phone end and a server end, wherein the server end comprises: the system comprises a data standard management unit, a data cleaning service unit, an analysis model management unit, a data statistics unit, a data visualization display unit, a data source unit, a service application unit, a data unit and an application support unit. By adopting the task scheduling technology, the problem that tasks can be randomly configured and combined is solved, the flexible combination, disassembly, combination and the like of service data are improved, the original complicated processing mode is simplified, the processing efficiency of the service data is improved, and meanwhile, the later maintenance cost is reduced; the invention adopts metadata management to uniformly manage technical metadata and solves the standardized processing foundation and the verification criterion of data.
Description
Technical Field
The invention relates to the technical field of data analysis decision systems, in particular to an education decision system based on big data analysis.
Background
With the development of science and technology, colleges and universities conveniently monitor and manage all internal business data of schools, staff information and student information in the schools are input into the system by introducing some school systems, each user has a single account with real-name authentication, and the staff and the students can log in the school systems to check bulletins issued by the schools and obtain school information at any time and any place.
However, most of the existing school systems do not have the personalized customization function, cannot be expanded, cannot be configured in diagrams, cannot visually know the results of various service data, are hard coded, and therefore the later maintenance cost is high, new functions are difficult to expand on the original basis, and the original school systems are very inconvenient to use.
To this end, we propose an educational decision system based on big data analysis to solve the above problems.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides an education decision-making system based on big data analysis, which briefly describes the technical effects achieved below.
In order to achieve the purpose, the invention adopts the following technical scheme:
an education decision-making system based on big data analysis comprises a PC end, a mobile phone end and a server end, wherein the server end comprises:
the data standard management unit is used for managing all the data standards after carding and centrally managing related definition information of each data table and data items;
the data cleaning service unit is used for cleaning various heterogeneous data sources, realizing data transmission channels and standard session processing, and bringing all data into the same platform for data management;
the analysis model management unit is used for managing the analysis model and the indexes thereof and operating the user-defined indexes;
the data statistical unit is used for providing automatic data calculation and summarization for a user;
the data visualization display unit is used for providing graphical and tabular display of various analysis results and drilling of any dimension for a user;
the system comprises a data source unit, a data processing unit and a data processing unit, wherein the data source unit is used for collecting school operation data, data types and data sources, the data sources comprise school business system data, state data, early warning data and filling data, and the data sources are mainly structured data;
the service application unit is used for performing functions such as quality monitoring, quality analysis, data early warning, task management, home-school interaction, public setting, basic data configuration, data acquisition, notification announcement, system management, password modification, online investigation, leadership cockpit, personal information viewing, mobile terminal, department condition, teaching condition, class condition and school-in condition on the basis of data analysis application on the data unit;
the data unit is used for providing the capabilities of data extraction, cleaning, filtering, conversion, loading and the like, dividing the capabilities into a service library, an index library, a special course and the like, and providing data support for an application layer;
and the application support unit is arranged between the service application unit and the data unit, and mainly integrates an application support tool to provide support and basic resource management for the application service of the upper layer. The application support unit mainly supports data-level access and does not involve business logic.
Further, the server side further comprises a data early warning unit, wherein the data early warning unit is used for monitoring all monitoring service data in the system, automatically generating new information after the system meets the early warning requirement, and automatically pushing the new information to the monitoring user according to the pushing service provided by the information management module.
Further, the users all perform real-name authentication, and the real-name authentication comprises name authentication, identity card number authentication, gender authentication and number authentication.
Further, the number authentication may be one of student number authentication or employee number authentication.
Further, the user employs role-based unified user rights management.
Furthermore, the system realizes the separation of the front end and the rear end, the front end is combined with H5 and VUE technology, and the rear end adopts a Spring Boot frame. Redis is used for storing login information in a cache to realize quick login. MyBatis as a persistent layer framework, eliminating manual setting of almost all JDBC codes and parameters and retrieval of result sets; MySQL, MongoDB for data storage, database connection pool by Druid. Based on the Swagger specification, a JSON format description file is automatically generated based on the project code of the Spring Boot.
The system adopts a layered design and comprises a data source layer, a data layer, a supporting layer, an application layer and an interaction layer. The loose coupling structure between each layer of the system, and each layer of the system is clearly positioned and relatively independent.
On one hand, the system automatically captures data of original service management systems of schools; on the other hand, the system collects and mines key data through functions of task management, template import, evaluation, questionnaire and the like, integrates data models of all data, forms analytical model data based on five quality index systems of student comprehensive quality evaluation, teacher comprehensive capability evaluation, course running state evaluation, professional development level evaluation and school quality benefit evaluation preset by the system, and finally presents the analysis result to each role user in a multi-dimensional visual mode to provide data support, problem early warning and intelligent analysis for analysis, judgment and decision of the talent culture quality of schools.
A decision method of an education decision system based on big data analysis comprises the following steps:
step one, establishing a data standard according to national standards, education industry standards, company specifications and technical attributes;
step two, integrating application system data of each education service, and cleaning the data by using an ETL tool to ensure that the cleaned data completely meet the data standard of the step one;
step three, according to the data after the step two is finished, service data are disassembled and combined, and data information is combined into data bins of schools, teachers, students, expenses and the like according to education management requirements;
step four, according to the data after the step two is finished, according to the time axis, the administrative management framework of the school, the party and committee organization system, the professional management mode, the teacher attribute, the student attribute and other information, establishing the transverse and longitudinal analysis dimension and the information blade;
step five, performing data pre-summarizing treatment according to the data results of the step two and the step four to form various measurement data taking schools, teachers and students as main bodies;
step six, establishing each analysis application service according to the business theme according to the data results of the step three, the step four and the step five in an application service layer;
and step seven, displaying the analysis results in a mode of a histogram, a trend graph, a heat point diagram and the like according to the data results of the step three, the step four, the step five and the step six and the requirements of the analysis subject on a display layer.
Compared with the prior art, the invention has the beneficial effects that:
1. compared with the prior art, the task scheduling technology is adopted, the problem that tasks can be randomly configured and combined is solved, flexible combination, disassembly, combination and the like of service data are improved, the original complex processing mode is simplified, the processing efficiency of the service data is improved, and meanwhile the later maintenance cost is reduced;
2. compared with the prior art, the method adopts metadata management to uniformly manage technical metadata, and solves the problem of the standardized processing basis and the verification criterion of the data;
3. compared with the prior art, the method has the advantages that the visualization technology is adopted, so that the final data result can be displayed in the modes of a histogram, a trend graph, a hotspot graph and the like, the visualized data monitoring and data analysis are realized, and the problems that the analysis result is difficult to express, cannot be visually positioned and cannot be observed in a multi-dimension mode are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
FIG. 1 is a schematic structural diagram of a technical framework in an educational decision-making system based on big data analysis according to the present invention;
fig. 2 is a user right management diagram of an education decision system based on big data analysis according to 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.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention.
Referring to fig. 1-2, an education decision system based on big data analysis includes a PC terminal, a mobile phone terminal and a server terminal, and the server terminal includes:
the data standard management unit is used for managing all the data standards after carding and centrally managing related definition information of each data table and data items;
the data cleaning service unit is used for cleaning various heterogeneous data sources, realizing data transmission channels and standard session processing, and bringing all data into the same platform for data management;
the analysis model management unit is used for managing the analysis model and the indexes thereof and operating the user-defined indexes;
the data statistical unit is used for providing automatic data calculation and summarization for a user;
the data visualization display unit is used for providing graphical and tabular display of various analysis results and drilling of any dimension for a user;
the system comprises a data source unit, a data processing unit and a data processing unit, wherein the data source unit is used for collecting school operation data, data types and data sources, the data sources comprise school business system data, state data, early warning data and filling data, and the data sources are mainly structured data;
the service application unit is used for performing functions such as quality monitoring, quality analysis, data early warning, task management, home-school interaction, public setting, basic data configuration, data acquisition, notification announcement, system management, password modification, online investigation, leadership cockpit, personal information viewing, mobile terminal, department condition, teaching condition, class condition and school-in condition on the basis of data analysis application on the data unit;
the data unit is used for providing the capabilities of data extraction, cleaning, filtering, conversion, loading and the like, dividing the capabilities into a service library, an index library, a special course and the like, and providing data support for an application layer;
and the application support unit is arranged between the service application unit and the data unit, and mainly integrates an application support tool to provide support and basic resource management for the application service of the upper layer. The application support unit mainly supports data-level access and does not involve business logic.
More specifically, the server side further comprises a data early warning unit, wherein the data early warning unit is used for monitoring all monitoring service data in the system, automatically generating new information after the system meets the early warning requirement, and automatically pushing the new information to the monitoring user according to the pushing service provided by the information management module.
More specifically, the users perform real-name authentication, which includes name authentication, identification number authentication, gender authentication, and number authentication.
More specifically, the number authentication may be one of student number authentication or employee number authentication.
More specifically, users employ role-based unified user rights management.
More specifically, the user needs education affiliates using various kinds of education informatization systems, including students, teachers, government personnel, and the like.
More specifically, the tissue: the unit where the user is located, such as a finance department, a textbook department, and the like.
More specifically, the item: and various education related informatization systems, such as a educational administration management system, a teacher management system and the like.
More specifically, the role: and (4) the set of the permissions, wherein each role corresponds to a group of corresponding permissions. Once a user is assigned the appropriate role, the user has all the operational rights for that role.
More specifically, the resource: menus, data tables, etc.
A decision method of an education decision system based on big data analysis comprises the following steps:
step one, establishing a data standard according to national standards, education industry standards, company specifications and technical attributes;
step two, integrating application system data of each education service, and cleaning the data by using an ETL tool to ensure that the cleaned data completely meet the data standard of the step one;
step three, according to the data after the step two is finished, service data are disassembled and combined, and data information is combined into data bins of schools, teachers, students, expenses and the like according to education management requirements;
step four, according to the data after the step two is finished, according to the time axis, the administrative management framework of the school, the party and committee organization system, the professional management mode, the teacher attribute, the student attribute and other information, establishing the transverse and longitudinal analysis dimension and the information blade;
step five, performing data pre-summarizing treatment according to the data results of the step two and the step four to form various measurement data taking schools, teachers and students as main bodies;
step six, establishing each analysis application service according to the business theme according to the data results of the step three, the step four and the step five in an application service layer;
and step seven, displaying the analysis results in a mode of a histogram, a trend graph, a heat point diagram and the like according to the data results of the step three, the step four, the step five and the step six and the requirements of the analysis subject on a display layer.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (6)
1. The education decision-making system based on big data analysis is characterized by comprising a PC (personal computer) end, a mobile phone end and a server end, wherein the server end comprises:
the data standard management unit is used for managing all the data standards after carding and centrally managing related definition information of each data table and data items;
the data cleaning service unit is used for cleaning various heterogeneous data sources, realizing data transmission channels and standard session processing, and bringing all data into the same platform for data management;
the analysis model management unit is used for managing the analysis model and the indexes thereof and operating the user-defined indexes;
the data statistical unit is used for providing automatic data calculation and summarization for a user;
the data visualization display unit is used for providing graphical and tabular display of various analysis results and drilling of any dimension for a user;
the system comprises a data source unit, a data processing unit and a data processing unit, wherein the data source unit is used for collecting school operation data, data types and data sources, the data sources comprise school business system data, state data, early warning data and filling data, and the data sources are mainly structured data;
the service application unit is used for performing functions such as quality monitoring, quality analysis, data early warning, task management, home-school interaction, public setting, basic data configuration, data acquisition, notification announcement, system management, password modification, online investigation, leadership cockpit, personal information viewing, mobile terminal, department condition, teaching condition, class condition and school-in condition on the basis of data analysis application on the data unit;
the data unit is used for providing the capabilities of data extraction, cleaning, filtering, conversion, loading and the like, dividing the capabilities into a service library, an index library, a special course and the like, and providing data support for an application layer;
and the application support unit is arranged between the service application unit and the data unit, and mainly integrates an application support tool to provide support and basic resource management for the application service of the upper layer. The application support unit mainly supports data-level access and does not involve business logic.
2. The education decision-making system based on big data analysis according to claim 1, wherein the server further comprises a data early warning unit, the data early warning unit is used for monitoring all monitored business data in the system, automatically generating new messages after the system meets early warning requirements, and automatically pushing the new messages to monitoring users according to pushing services provided by the information management module.
3. The big data analysis-based educational decision making system according to claim 1, wherein the users each perform real-name authentication, the real-name authentication comprising name authentication, identification number authentication, gender authentication, and number authentication.
4. A big data analysis-based educational decision making system according to claim 3, wherein the number certificate can be one of a student number certificate or an employee number certificate.
5. The big data analysis-based educational decision making system according to claim 3, wherein the user employs role-based unified user rights management.
6. A decision method of an education decision system based on big data analysis is characterized by comprising the following steps:
step one, establishing a data standard according to national standards, education industry standards, company specifications and technical attributes;
step two, integrating application system data of each education service, and cleaning the data by using an ETL tool to ensure that the cleaned data completely meet the data standard of the step one;
step three, according to the data after the step two is finished, service data are disassembled and combined, and data information is combined into data bins of schools, teachers, students, expenses and the like according to education management requirements;
step four, according to the data after the step two is finished, according to the time axis, the administrative management framework of the school, the party and committee organization system, the professional management mode, the teacher attribute, the student attribute and other information, establishing the transverse and longitudinal analysis dimension and the information blade;
step five, performing data pre-summarizing treatment according to the data results of the step two and the step four to form various measurement data taking schools, teachers and students as main bodies;
step six, establishing each analysis application service according to the business theme according to the data results of the step three, the step four and the step five in an application service layer;
and step seven, displaying the analysis results in a mode of a histogram, a trend graph, a heat point diagram and the like according to the data results of the step three, the step four, the step five and the step six and the requirements of the analysis subject on a display layer.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113592680A (en) * | 2021-07-28 | 2021-11-02 | 浙江省公众信息产业有限公司 | Service platform based on regional education big data |
| CN114238720A (en) * | 2021-11-19 | 2022-03-25 | 中国直升机设计研究所 | Data linkage based view analysis display method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103810530A (en) * | 2014-03-11 | 2014-05-21 | 邓鸣凤 | Digital campus scheme |
| CN104573071A (en) * | 2015-01-26 | 2015-04-29 | 湖南大学 | Intelligent school situation analysis system and method based on megadata technology |
| US20150193699A1 (en) * | 2014-01-08 | 2015-07-09 | Civitas Learning, Inc. | Data-adaptive insight and action platform for higher education |
| CN108090854A (en) * | 2017-12-15 | 2018-05-29 | 佛山租我科技有限公司 | The Web-based instruction and resource-sharing management platform based on Information Environment |
| CN108520365A (en) * | 2018-04-23 | 2018-09-11 | 温州市鹿城区中津先进科技研究院 | Education decision system based on big data analysis |
-
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150193699A1 (en) * | 2014-01-08 | 2015-07-09 | Civitas Learning, Inc. | Data-adaptive insight and action platform for higher education |
| CN103810530A (en) * | 2014-03-11 | 2014-05-21 | 邓鸣凤 | Digital campus scheme |
| CN104573071A (en) * | 2015-01-26 | 2015-04-29 | 湖南大学 | Intelligent school situation analysis system and method based on megadata technology |
| CN108090854A (en) * | 2017-12-15 | 2018-05-29 | 佛山租我科技有限公司 | The Web-based instruction and resource-sharing management platform based on Information Environment |
| CN108520365A (en) * | 2018-04-23 | 2018-09-11 | 温州市鹿城区中津先进科技研究院 | Education decision system based on big data analysis |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113592680A (en) * | 2021-07-28 | 2021-11-02 | 浙江省公众信息产业有限公司 | Service platform based on regional education big data |
| CN114238720A (en) * | 2021-11-19 | 2022-03-25 | 中国直升机设计研究所 | Data linkage based view analysis display method and system |
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