New industry pushing new environment--"Shanghai opportunity in Big Data age"

Source: Internet
Author: User
Keywords Large data large data large data industry large data large data industry industry large data large data industry industry discipline large data large data industry industry discipline large data era

From the big data industry nuggets, the importance of Shanghai is self-evident. Recently, many government committees, colleges and universities have been discussing the "Big data industry", hoping to accelerate the pace of industry advancement. But in a lively sound, we are aware that the "new" large data industry is not only the technology, but also it will profoundly affect the industrial chain and social mode of operation, forcing us to create a new environment to adapt to the new industry.

Develop the "data scientist" springtime

According to statistics, the world today in 24 hours, can produce the equivalent of 1.68 billion DVD capacity of data, produce 294 billion emails, equivalent to the entire United States in 2 years produced by the paper Mail. 90% of all the data that humankind has received so far has been generated over the past two years. Searching for useful information in such a vast ocean of data is like looking for a needle in a haystack. In short, it is not a huge amount of data can "naturally" dig out the value behind, its "dry haystack" negative effects, enough to make unprepared people rush.

It is urgent to find valuable information and application in data ocean, and to improve the efficiency of data mining and utilization. Zhu Yangyang, a professor at the School of Computer Science at Fudan University, argues that some basic research on the data discipline is now less popular than the big data industry. He thought it necessary to establish a specialized discipline, it can be called data science or data, it provides basic theory and method for large data research in many disciplines and fields, on the basis of which, it gradually forms the data science of the subdivision field, such as: Bioinformatics, meteorological data, financial data science, geo-data, etc.

This means that the traditional pattern of training talents by subject classification also needs innovation. Large data industries need such a group of people who are good at integrating multidisciplinary knowledge: it can be based on information science, explore the acquisition, storage, processing and excavation of large data and other innovative technologies and methods, but also from the perspective of management to explore the modern enterprise production management and business operation decisions brought about by the change and impact. Over the years, people have advised that Shanghai should speed up the training of interdisciplinary talents. Such people are not only proficient in technology, but also know how to apply technology to business decisions. If the proposal of "data scientist" is implemented, it will be an opportunity for the training model of creative talents in Shanghai.

Data sharing needs legislation

If the "dry haystack" effect of the solution, but also rely on new technology research, interdisciplinary training to solve the talent, then the rational use of large data, the Internet will be forced to improve the legal norms.

The embodiment of large data value can not be separated from sharing, but due to a considerable part of the data involved in the privacy of ordinary people, the use of data, especially commercial use, should have an interest border. For example, data collection should inform the customer of their business purpose, but after the advent of the big data age, the data mined may be converted to other applications. Wei, a teacher and a new media expert at Shanghai Jiaotong University's School of Media and Design, has now a considerable portion of personal data already in the hands of different institutions and companies. For example, the police department has the driving licence information, the Bank has the credit card billing information, the hospital has the health information. Imagine that one day, some businesses will be "providing more accurate services" in the name of the same time with the original scattered among the various agencies of data, mining potential business value, to push more merchandise advertising ... Will the consumer be overwhelmed?

Again, the previous data preservation has the timeliness, passed the stipulated time, the data will naturally destroy. But in the big data age, data may remain in company B's database even when a company is destroyed. In other words, the data will remain, and the use of the boundaries is blurred, resulting in a more formidable potential threat.

The information Technology Department of the City Science Commission is brewing to form a large data industry alliance. According to the relevant leaders, most of the members of the Alliance are still technology-based enterprises, "we particularly want to have the legal community to participate in the canonical data attributes." Using good data according to law is an unavoidable problem in large data industry. "More and more people in the industry are forming a consensus: it is urgent to set legal constraints on the use of data sharing." Hu Gang, a legal expert at China Internet Association, argues that for business organizations, the preservation and sharing of data should follow the "minimum, adequate" standard; from a social point of view, the importance of Internet laws and regulations is obvious and needs to be adjusted accordingly. Only by being multi-pronged can we address the challenge of privacy issues.

Focus on the potential risk of large data

Large data suddenly "big hot", but also make many it enterprises eager to, but the rational view, large data industry mature, inseparable from the "step-by-step" strategy. Business data processing and analysis company Deng Hambei China Business Director Li Jinmin that the first step is the enterprise's own internal data to do early integration and application, such as in the enterprise to establish a data warehouse, to meet the needs of enterprise universal decision-making. The second step is to get out of the enterprise, do the internal and external data fusion and analysis. For example, for a bank, because credit card payment involves different industries of retailers or brands, just analyze their own credit card data, may not fully understand the customer's real needs, which requires the integration of different business information analysis. The third step is to become a data-driven, customer-centric new company, which will involve changes in management thinking.

Thinking farther, the more popular new industries, new concepts, the more we need to be rational and cautious attitude. Can big data save everything, is it really omnipotent? In the opinion of some industry personage, big Data is not the commercial weapon of the invincible. As we have more and more data available, there are more and more statistically significant correlations. Many of these relationships have no practical significance and are likely to lead people astray in the real solution of the problem. Therefore, some experts suggest that, while actively promoting the large data industry, we still need a sober set of speakers and think tanks, who are constantly looking at the potential risks of large data and reminding policymakers not to put "eggs" in a "basket" of big data, but there are some ideas and methods that are equally valuable in addition to large data.

As Wei, we cannot rely too much on the role of large data, ignoring the ability of the human brain to understand and cause judgments. A right, great decision depends not only on cold digital analysis, but also on the experience and intuition of policymakers, which are just what the data is powerless to do.

(Responsible editor: Fumingli)

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