Internet is developed in contemporary society, and information technology is widely used in all fields of society. Of course, using information technology to promote the development of higher education is also the process of educational informatization. With the rapid development of information technology, big data is accumulating rapidly. Big data records the pace of information technology development and is also conducive to the effective development of information technology in society. As a place to train talents, colleges and universities naturally have a large amount of data accumulation and huge amount of information. Big data has a great impact on higher education. It not only promotes the development of higher education, but also reflects the process of data accumulation in higher education. This kind of data is shared with the external environment and plays a role in promoting higher education.
1 Big data promotes the development of higher education.
In the years of development, higher education has gradually adapted to the rapid development process of informatization, and informatization of higher education is an inevitable condition, which has a completely effective role in the reform and improvement of higher education. Informatization of higher education also plays an important role in improving teaching quality and guiding the innovation of teaching mode. Informatization of higher education is conducive to strengthening the construction of campus culture, promoting the high-level development of education, improving teaching methods, giving full play to various functions of education, cultivating talents, exchanging information and improving teaching environment. Informatization of higher education is a necessary condition for the development and promotion of education. A lot of information exchange will inevitably produce a lot of data. Collect and process big data to facilitate data retrieval and query. Higher education itself has the characteristics of large amount of information, diverse and complicated data. Making good use of big data to contribute to the development of higher education will certainly promote the development of higher education. The application of big data in the classroom can change the traditional teaching mode and give full play to the unlimited potential of information technology. Both time and space barriers can be broken by information technology, which will help students to better integrate into the classroom, make them more adaptable to the classroom, and thus understand knowledge more easily. The wide application of big data is also applicable to scientific research. The application of comprehensive information of big data plays a key role in promoting information sharing and exchange. The application of modern information technology in social science will improve the traditional research methods, not only enhance the credibility of the results, but also improve the work efficiency. Moreover, the application of big data in serving people will enable colleges and universities to better grasp the needs of society and understand the society's desire for talents, thus cultivating talents who can adapt to society. This is conducive to strengthening the relationship between universities and society and enabling universities to better perform their social functions. Big data is also conducive to the construction and inheritance of campus culture in colleges and universities. Colleges and universities have the responsibility and obligation to spread excellent national and world culture to more students. As cultural carriers, colleges and universities are better equipped to carry out cultural education and promote cultural and technical exchanges through information technology.
2 the relationship between big data and higher education
The relationship between big data and higher education is not only a simple application relationship, but also a passive acceptance of big data by universities. In fact, universities and big data are interdependent and mutually reinforcing, and the development of higher education is also the development of big data. At the same time, the development of big data also promotes the development of higher education. Big data can be said as a tool. First, it conforms to the development process of higher education, and has made many improvements and upgrades for the development of higher education. For example, big data promotes the process of talent training in colleges and universities, which is conducive to colleges and universities to select higher talents suitable for society, tap the potential value of talents, better serve society and people, help students find their own advantages, and make the development of talents smooth. As mentioned above, big data helps universities to establish a sound cultural system, and helps universities to carry out cultural inheritance, educational form reform and innovation. Big data helps colleges and universities to understand social needs and cultivate all-round talents to adapt to society. Conversely, higher education also plays a very important role in promoting the development of big data. Colleges and universities have a huge amount of information, relatively complete records and perfect forms, and a very perfect data collection system, so college education also plays a positive role in the development of big data. Long-term data utilization in colleges and universities will naturally produce many effective data sorting methods, and the research on data is also very meticulous, which will supplement and improve the data and analyze and innovate the data recording methods. Therefore, the collation and utilization of data by higher education will also make more contributions to the development of big data. After talking about the mutual utilization of higher education and big data, we should also consider the common development of big data and higher education. After establishing a relatively perfect way to process and utilize big data, many colleges and universities often communicate and share data processing methods and collection methods with the outside world. Most data processing work is purposeful. For example, the information retrieval work on the internet is to think about what you need first and then search online, so it is very important to sort out the information. University education is generally divided into liberal arts and science, and then there are engineering, medicine, normal schools, business and so on. Different data have different processing methods, and different data categories are sometimes interoperable, so the processing methods and overall thinking of big data are different and related, which requires researchers to analyze and sort out for a long time. The use of big data needs professional recognition, otherwise it will waste resources. It seems that only universities and researchers in society are qualified to certify big data. Big data is widely used in information technology, social sciences and other disciplines, which provides a good data reference for more data users while ensuring the authenticity and reliability of data. In other words, the use of data in the process of university education directly affects the utilization rate of big data, and universities provide more technical support for big data, which also limits the development of big data, so this relationship between big data and university education affects the development of both.
3 Big Data in the process of promoting the development of higher education problems encountered
It is undeniable that big data has made many contributions to the development of higher education. However, in the process of big data promoting higher education, there are still some problems that hinder the promotion of big data, which leads to big data not playing its due role and making greater contributions to higher education. First of all, the low utilization rate of big data in colleges and universities is mainly reflected in the narrow understanding of requirements in the process of data search and collection, which leads to imperfect data collection and incomplete receipt collection, which will lead to difficulties in the application process and lack of information and resources. So the reason is that the data collector's work is flawed, or the method of data mobile phone is incorrect and irregular, which leads to data loss. Secondly, the problem of incomplete utilization of big data is due to the nonstandard technology and improper operation of data users. Compared with the traditional data usage methods, the modern use of big data for data retrieval and usage has become more powerful. Through scientific and technological means, you can easily choose the data you need from a large number of databases to use. This not only greatly reduces the difficulty of operation, but also saves a lot of time. As we all know, data mining is complicated and tedious, and it requires a serious and meticulous working attitude of data mining workers, and it is not sloppy at all. However, through technical means and advanced internet technology, many problems that may arise in the work can be well solved. But machines are machines, and there can never be anyone's thinking. Even if there is, it is also added by people, and it can never go beyond people's thinking. Therefore, there may be many mistakes in the machine, and people need external help to supervise the collection and processing of data. A slight error will cause data errors and affect the use of data.
4. Countermeasures to Promote Big Data and Improve the Effectiveness of Higher Education
In view of the above problems, the first solution is to let people fully understand the role of big data, so that people can fundamentally establish the basic concept of the role of big data, and then big data can still serve people better. Big data is an indispensable means of data collection and processing in modern society with information explosion. The rapid development of society is bound to be accompanied by thousands of data. Therefore, if we want to extract really useful data from so many dazzling data, we must establish a complete database with the help of scientific and technological means to facilitate people's extraction and utilization of data. After understanding the role of big data, we should make good use of big data and use it correctly. In the process of using big data, it is necessary to standardize the use method to prevent users from abusing big data. The retrieval and classification process should also be carefully operated, because it is not only an error, but also every subsequent step may cause misunderstanding and deviation in data processing, leading to the wrong use of big data. In order to make better use of big data and promote the development of big data in higher education, colleges and universities should establish a perfect platform for using big data, so that users can have a place to look up and use resources to improve the utilization rate of big data. As for the configuration on campus, it is necessary to maintain it in time, constantly supervise and improve the storage of big data, further strengthen the efficiency of data use and give full play to its due value. In terms of personnel allocation and selection, we should carefully screen the truly useful talents, classify and sort out the data in detail, and better help the data users on campus to use the data.
5 abstract
In the era of big data explosion, people who can make better use of information and use it for themselves have played the real value of big data. Correctly treating big data, rationally using big data, organically combining big data with higher education and giving full play to its due value will help people explore unknown knowledge and make good use of big data, that is, it will promote higher education.
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The meaning of big data
Today's society is a rapidly developing society with advanced technology and information circulation. People's communication is getting closer and closer, and life is becoming more and more convenient. Big data is the product of this high-tech era. [10] Ma Yun, the founder of Alibaba, mentioned in his speech that the future era will not be the IT era, but the DT era. DT is Data Technology, and showing big data is very important for Alibaba Group. [ 1 1]
Some people compare the data to a coal mine with energy. Coal is divided into coking coal, anthracite, fat coal and lean coal by nature, but the mining cost of open-pit coal mine and deep-mountain coal mine is different. Similarly, big data is not "big" but "useful". Value content and mining cost are more important than quantity. For many industries, how to use these large-scale data is the key to win the competition. [ 12]
The value of big data is reflected in the following aspects:
(1) Enterprises that provide products or services to a large number of consumers can use big data for precise marketing;
(2) Small and beautiful SMEs can use big data for service transformation;
(3) Traditional enterprises that must be transformed under the pressure of the Internet need to keep pace with the times and make full use of the value of big data.
However, the great significance of "big data" in economic development does not mean that it can replace all rational thinking on social issues, and the logic of scientific development cannot be lost in massive data. Ludwig von mises, a famous economist, once warned: "As far as today is concerned, many people are so busy accumulating useless information that they lose their understanding of the special economic significance of explaining and solving problems." This really requires vigilance.
In this era of rapid development of intelligent hardware, an important problem that puzzles application developers is how to find that delicate balance among power consumption, coverage, transmission rate and cost. Enterprises can use relevant data and analysis to help them reduce costs, improve efficiency, develop new products, make more informed business decisions and so on. For example, by combining big data with high-performance analysis, the following situations may be beneficial to the enterprise:
(1) Analyzing the root causes of faults, problems and defects in time may save enterprises billions of dollars every year.
(2) Plan real-time traffic routes for thousands of express vehicles to avoid congestion.
(3) Analyze all SKUs and make pricing and clearance with the goal of maximizing profits.
(4) Push the preferential information that the customer may be interested in according to his buying habits.
(5) Quickly identify gold medal customers from a large number of customers.
(6) Using clickstream analysis and data mining to avoid fraud.
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