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Written by: Deng Yinglin
2019-12-11 16:01
Last updated: 2019-12-11 16:01In recent years, society and the international community have talked about "big data" from time to time, and often use it together with the development of innovation and technology. However, in a social atmosphere where science and technology are first, how to use big data? Will the situation be as fleeting as it was in the past "Technet stocks" era? Will trained personnel be useless?
Big data is actually closely related to life. With the rapid development of the Internet, whether it is online shopping or just looking for and browsing information on the Internet, the user preferences and habits generated in the process have all become big data, which is not only helpful to social development, but also to the business community. In other words, if you can make good use of data, you can grasp the pulse of the market and create unlimited business opportunities. Some human resources consultants have bluntly stated that the market is still hungry for data analysis talents, even if the economy is currently in a weak state. A data scientist who works at a large chain drug store revealed that every week a headhunting company is "digging", and it is known that graduates start salary The asking price can reach 20,000 yuan, which is higher than the average level of university students in Hong Kong.
Deng Wenli pointed out that future data analysis will become increasingly important. (Photo by Zheng Zifeng)
In the 1990s, technology developed rapidly in many fields. The concept investment of Kewang was hot and attracted a lot of funds. The market was almost optimistic about technology stocks. The stock price was soaring and the valuation gradually "off the ground", eventually forming an investment bubble. On March 10, 2000, after the US Nasdaq index hit a new high and closed at the market, it bottomed out all the way, and the dotcom bubble burst. After that, many people will learn from it before investing, and even deliberately avoid investing in Kewang.
Today, the Internet has become a part of Hong Kong people's life, and daily shopping, work and study are inseparable from the Internet. Behind the search and browsing of information, users have accumulated a large amount of data. Whether it is banking, insurance, medical or other industries, more and more attention is paid to data analysis and application. In addition to providing personalized products and services to customer needs, they also By analyzing and adjusting data and formulating development plans, companies can operate more efficiently and find new opportunities and business opportunities. The Hong Kong Government also proposed in the 2017 Policy Address that it will strengthen innovation and technology development in eight directions, including opening up government data; the "Hong Kong Smart City Blueprint" also talks about promoting digitalization and opening up more public and private sector data for construction One of the measures of "smart government". With all aspects of openness and development of data, a large number of professionals in data analysis and application of data are required.
Observe industry development trends
Hang Seng University of Hong Kong launched the "Bachelor of Science in Data Science and Business Intelligence (Honours)" in 2014, which is the first bachelor's degree program in Hong Kong to integrate "Data Science" and "Business Intelligence". Deng Wenli, deputy dean and head of the Department of Mathematics and Statistics, Evergrande School of Decision Science, said that in the past, designing and testing analytical tools took time, cost, and manpower. To facilitate statistics, missing or incomplete data is often ignored. Today's technology is advanced, and data collection and analysis is easier than in the past. "Now it is new, fast, and flat. Every industry and different types of work. As long as there is data, there is room for development in data science."
Many people think that "data analysis" is a difficult science. There is no foundation to avoid it. However, Deng Wenli believes that data is ubiquitous. Appropriate analysis can also observe the development models of different industries. It is neither dull nor detached. As long as you don't resist numbers, data analysis is also fun. He quoted the international business authoritative journal "Harvard Business Review" as calling data scientists "the sexiest jobs of the twenty-first century."
Huang Haolan, who is engaged in data analysis related work, was interested in data science as early as middle school. After considering, he entered Evergrande to take a "Bachelor of Science in Data Science and Business Intelligence (Honours)" course. He believed that "Machine Learning ”Coordinating with big data can have a great impact on the world, and it can make a lot of decisions and replace manpower." He recalled that when he was an intern in a large-scale drugstore chain in his third year of college, one of the topics was to rely on the sales of goods and customers as a whole. Consumption habits, speculating when the flu peak will start, he described the work content as being more grounded, more interested in data science, and intending to continue to develop.
Basic concepts and skills are difficult to eliminate
In fact, in addition to forecasting, data science can also solve existing problems. Deng Wenli said that data science is mainly divided into three parts, including investigating sensitive data (such as the proportion of tax evasion companies, the support of a political figure), regression analysis (such as estimating the average salary by gender, education, and occupation), and dealing with missing or filling Incomplete data, such as respondents' refusal to provide sensitive information, or other unpredictable circumstances.
For example, Deng Wenli pointed out that during the development of new drugs, there are not many people testing drugs, so each case is valuable information, but not every trial person can complete the course of treatment. Traditional tools will automatically ignore incomplete data, but nowadays Electronic tools are developed. As long as appropriate analysis tools can be designed, useful information and accurate analysis can still be retained to help compare the effectiveness of new and old drugs and develop new drugs. He described the findings as being applicable in the real world, prompting him to continue his research efforts.
In daily life, people inevitably search for information online. Deng Wenli pointed out that those who understand the data can convert data such as the number of occurrences and frequency of keywords in search engines (such as google search) into data for prediction and analysis, and estimate the public's concerns. Incidents, such as the recent anti-revision storm, the names of many political figures appeared repeatedly.
The Internet world is unpredictable and technology is changing rapidly. Can the things learned catch up with the development? Deng Wenli said with a smile that he did n’t know the Internet when he was young. He graduated from the Department of Mathematics of the Chinese University of Hong Kong in 1988. He graduated with a Master of Philosophy in Statistics from CUHK one year later. Today, most of the tools he used in school have been used. Eliminated, but the concepts and techniques learned are still valid.
Increasing demand for talent
Deng Wenli described that with the advancement of technology and more and more people using smart phones, more data will be provided. Therefore, data science is a "long-term success" and there is no need to worry about it being replaced. Although artificial intelligence (AI) is new Trends, but AI also needs to be "taught". Data science analysis tools and statistical methods are one of the "teachers." He added that the industry needs to keep pace with the times, so it is necessary to learn at the right time.
Big data is convenient, but there are concerns about leaking personal privacy. Deng Wenli emphasized that data science is also ethical, and relevant parts will be covered in the course, including the need to obtain the permission of the relevant company or person when collecting data, and the use of the collected data should be clearly informed; in addition to the data cannot be wrong, protect and manage the data The responsibility is also a compulsory content of the course.
Zhou Qiping, Managing Director of Anjun Human Resources Consultant. (Profile picture)
Zhou Qiping, Managing Director of Anjun Human Resources Consulting, pointed out that the demand for talents who can research and analyze big data is increasing in Hong Kong society. Because there are not many talents in this industry, even if the market conditions in Hong Kong are worsening, overall consumer sentiment is declining. Manpower, but there is still a shortage of talent in this industry. In addition, under the current social circumstances, there are fewer overseas or domestic talents willing to come to Hong Kong, which creates a shortage of people.
Huang Haolan also revealed that there is a shortage of people in the industry. Even if the economic situation is not good, the average headhunting company still "digs corners" every week. Considering the rapid development of the industry, the basics learned at Evergrande were relatively basic, and the analysis of data from different industries will also There are differences, so you must study and study constantly. He is currently studying a master's course related to the industry to pave the way for future work. He reminded that the data scientist market is not quite mature, and there is no clear career ladder, but it has more opportunities than when he was in the first or second year of college. "At that time, the job opportunities of fresh graduates related to online recruitment platforms could be said to be completely absent. Fortunately, he won an award in the "hackathon" competition. Some teachers recommended him to practice at a large drugstore chain. After graduation, he was hired by the internship company as a full-time employee.
Qiping Zhou said that many companies take the relevant degree as the minimum requirement when recruiting. To deal with complicated data, the minimum requirement for employers is the master's degree. If you have knowledge of both IT and business organizations, the starting salary point ranges from 13,000 to 1.8,000 yuan, and if you work for a large enterprise, multinational enterprise or government department, it can reach 20,000 to 25,000 yuan. As for those who have relevant internship experience, the asking price is always higher.
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However, Qiping Zhou reminded that many colleges and universities have business courses, and the talents who analyze and study big data are not as professional and irreplaceable as actuaries. Those with experience in IT and data analysis can transfer their job skills to work. The place is in the ability to analyze and interpret data. She reminded students to pay attention to the course content before choosing a course. When recruiting, they must pay attention to the different job requirements of data analysts and data scientists. Generally speaking, scientists need to understand the integration of analysis procedures and design. Out statistical tools, while analysts are less demanding. 
Hang Seng University of Hong Kong started the "Bachelor of Science (Hons) in Data Science and Business Intelligence" course in 2014 to train data scientists. The first batch of graduates joined the workplace last year. Deng Wenli pointed out that future data analysis will become increasingly important.
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