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Big data analysis can greatly increase the operating efficiency of traditional industries, reduce the cost of operation and maintenance, and increase the value of data. In developed countries such as Europe and the United States, industrial big data applications have become very popular.
With the development of big data applications in 2017, the value of big data will be fully reflected and become the new strategic commanding point. At the corporate and societal level, big data has become an indispensable strategic resource in market competition and has become a new focus of competition.
The emergence of a new industry will surely have new demands for jobs, and big data is no exception. In recent years, the emergence of big data has given birth to a number of new jobs, such as data product managers, big data algorithm engineers, big data analysts, data management experts, and so on. People with rich experience in data analysis will become scarce resources, and data-driven work will show explosive growth.
However, looking at the overall situation, like other emerging industries, big data still faces many problems. Since the internet finance industry has entered people's sights, questions about the industry have been heard.
On the one hand, despite the increasing number of companies investing in the big data industry, there are actually not many big data companies. Many companies have neither data nor data-solving capabilities. They are not even aware of the value of such strategic resources as big data. They just give themselves a coat of big data for better valuation and branding. These companies often lack inter-agency integration and in-depth cooperation. There is no data on how to use data, and no data is used.
On the other hand, there are many so-called big data companies on the market, all of which are companies that make profits through reselling data. Many of these companies' data sources come from the data black market. This creates confusion and confusion for the industry and users, which is fundamentally not conducive to the healthy development of the big data industry and big data companies.
Looking at the development of big data in the world, the current big data companies are mainly divided into two categories: one is companies that have big data on their own, such as Alibaba, Jingdong, Tencent, today’s headlines, Sina Weibo, and Beijing One Card Company. The vast majority of them are Internet companies. The other is companies that provide tools and capabilities for big data mining and analysis, such as Thors, percentage points, and so on.
The problems facing big data do not stop there. According to data from China Investment Network, since the beginning of April this year, seven companies in the big data industry have received financing, including four from foreign countries and three from China, amounting to approximately RMB 1.1 billion. This situation has been going on for a long time. In 2016, there were 22 big data-related companies in the first half of the year getting financing, from angels to C rounds.
With the large amount of capital entering the big data industry, the overvaluation of start-up companies is becoming more and more serious. It seems that as long as the label of big data is used, the valuations of some companies are frequently doubled. Taking Shanghai Sruid Information Technology Co., Ltd., a corporate credit data service provider, as an example, Shanghai Si Ruide not only recently obtained a multi-million-yuan financing led by Dongfang Haifu, but also successfully completed 3 rounds in the last 18 months. Financing. Another big data company Dingfu Data, which was established in August 2015, also completed two rounds of RMB 107 million in financing in more than one year.
In this regard, Zhao Jie, CEO of Shanghai Srudy Information Technology Co., Ltd., said that big data companies are sought after by capital, essentially because they are scarce. Although domestic two-year big data companies have fast financing and high frequency, there is actually not much in the market that can truly integrate financial resources. Many companies that use artificial intelligence to tell stories and have hundreds of millions of orders of magnitude of data are hard to obtain capital. Favored.
Big data has been favored by capital for market chaos
In recent years, big data has been widely applied to the Internet public opinion, Internet marketing, content distribution, Internet finance, artificial intelligence, and smart city construction. However, at the same time as the rapid development of big data, there are also phenomena of pros and cons.