Solutions for Higher Education Industry

University education has been closely related to the data, and multifaceted data integration for teaching, study and research, and combination with the effective use of big data technology, can fundamentally bring an all-around ascension to education.

Through comprehensive analysis of big data, students are facilitated to improve their learning efficiency and provided with personalized learning services in line with career planning; at the same time, it also helps education and scientific research institutions to accelerate the improvement of scientific research achievements and education quality and cultivate more and more outstanding innovative talents.

1.11.1 Current status of industry

1. Until today, the information construction of colleges and universities in our country has been 20 or 30 years during which university informatization,from teaching management assisted by stand-alone application system to universal application of various functional management systems, from Center construction to fully integrated digital campus network, helped to accumulate the mass data while bringing profound changes to management of colleges and universities.

2. Each functional subsystem is independently developed and operated,lacking in overall planning; Education resource data are stored in different systems and there is insufficient communication between systems,which fail to realize data sharing and results in a serious phenomenon of "information islands".

3. The use of information system stays only at the level of replacing manual work, and data analysis and application are not in place.

1.2Current Problems

Firstly, in the education big data area are there two major issues to be solved, namely,learning behavioral data analysis and administrative data analysis.

1. University behavioral data: make education more personalized, refined and intelligent.

2. Educational administration big data: connect all data to improve the efficiency of administrative management.

Under the premise of well disposing the two major issues, the following three goals for the informatization of colleges and universities should be realized.

Firstly, analyze students' learning data to make personalized learning possible, and truly teach students in accordance with their aptitude.

Secondly, promote teaching innovation and improve teaching quality.

Thirdly, optimize administrative management, realize interconnection, data sharing of various systems.

Of course, in the course of concrete construction will there be a series of problems as follows:

建设过程遇到的一系列问题图

What are the most vexing questions for you during the construction of higher education big data?

May you be worried about wrong big data analysis results? Is the university data interface incomplete? Fragmented construction lacking of uniform norms?
Complex cross-departmental coordination and communication? How to choose a cooperative company?
Isn’t there big data companies in local? How to build and implement big data? How to truly create real value?
Yonghong Tech will let you know there are now worries!

2.1Overall Architecture Diagram

·The one-stop big data analysis products and solution provided by Yonghong can help users to quickly set up big data analysis platform, agilely manufacture exclusive analysis report, and provide users with operation of flexible interactive analysis to quickly release data value in the process of business collaboration.

The Overall Architecture Diagram is as follows:

整体架构图

The first step is to tease out the data sources and clarify the underlying data.

整理数据源图

The second step is to screen, clean, integrate data,form special data after normalization of multiple sources.

数据筛选图

The third step is to tease out the core indicators and clarify the target of data analysis.

梳理核心指标图

The fourth step is to make data analysis report.

制作数据分析报告图

Quickly building a big data analysis platform in four steps,
and Yonghong Tech facilitates you to release data value speedily and flexibly.

The first step is to tease out the data sources and clarify the underlying data.
The second step is to screen, clean, integrate data, form special data after normalization of multiple sources.
The third step is to tease out the core indicators and clarify the target of data analysis.
The fourth step is to make data analysis report.

3.1The Value of Yonghong

1. Break down the barriers of vertical business system, integrate business data and realize comprehensive analysis of data to provide sufficient decision-making basis for the leadership.

2. Agile edition of the data report, flexible data analysis and beautiful visual presentation can fully meet all requirements for fast analysis.

3. Efficient big data processing ability helps users to confidently deal with massive historical data and rapidly growing incremental data, and a second response to the calculation and display of data at level of ten billion can be achieved.

4. It helps users to easily integrate depth analysis algorithm and understand data more clearly so as to explore the value of data.

5. With a complete solution for industry, it provides users with comprehensive data analysis and consulting services.

Yonghong Z-Suite one-stop big data analysis platform can create values for our customers and make them achieve success based on excellent data techniques.