Big Data Age: Are we ready?

Cai Grace

Following the investment in Sina Weibo, the acquisition of friends, the increase in UC and ding Ding Net, Alibaba Group and 294 million U.S. dollars to buy the High German software 28% shares, become the first major shareholder of the software. The two sides agreed to build a large data service system to facilitate data sharing. He can use Alibaba's electric business platform on the merchant's trading information, logistics information and geographical information, from the simple map to the diversification of life dealers, and Alibaba can share the geographical location, traffic information data, interest point information and user data, expand customers.

This is a big figure in the large data before Jack Ma hand over Alibaba's CEO Scepter.

The advent of the big data age, the maturity of the Internet infrastructure, and the push of cloud computing technology have spawned a series of new business models, data/information services into market darlings, social networking sites, cloud services, video sites, data-sharing sites, download services, and so on. How to excavate and analyze the massive data, discover the business opportunity in the data, become the important way for the enterprise to seek the decision basis and enhance the competitiveness.

The first "Big Data Age" is McKinsey, the world's top management consultancy, and Toffler predicted the big data in the third wave in 1980, but the real push for big data to the public is the Oxford University Professor Victor Maire Schoenberg, who has been studying large data for 10 years. The depth of his thinking is that the biggest shift in the big data age--abandoning the desire for causation--instead focuses on the relationship. Just know what "is" and don't need to know why. This is the subversion of human thinking inertia for thousands of years, the cognition of human beings and the way to communicate with the outside world put forward a new challenge.

Large data is not a simple superposition of numbers, but rather a computerized analysis system to interpret the network behavior data generated and accumulated by internet companies in their day-to-day operations, so large that byte units cannot be measured in GB (1024 MB) or TB (1024 GB). The starting metering unit is at least PB (1024 TB), EB (1 million TB), or ZB (1 billion TB).

According to the statistics on the subject of "How many things are going to happen over the Internet" in a day, 294 billion emails a day, if these are paper letters, take two years to process in the United States; 2 million blogs are published online every day, which is equivalent to the Times The total number of magazines published in 770 years 250 million photos uploaded to social networking site Facebook every day, if printed out, stacked together can be as high as 80 Eiffel Tower, 864,000 hours a day video is uploaded to the video site YouTube, equivalent to uninterrupted video 98 years; every day there are 187 million hours of concerts in the streaming media music website Pan On Dora, if a computer starts playing these concerts from year one, it is still endless. Cumulative, the amount of information generated in the Internet within a day can be filled with 168 million DVD discs.

In essence, the large data itself does not have much value, is based on large data processing and analysis for the enterprise to bring enormous value-added value. Large data contains all kinds of information of enterprise operation, if can timely and effectively tidy up and analysis, can quickly and effectively help enterprise business decision, respond to customer demand, enhance competitiveness. So, in the big Data age, the data is the king, the data itself is the assets, including EMC, Hewlett-Packard, IBM, Microsoft, and other global IT giants are through the acquisition of large data-related vendors to achieve technology integration.

In China, internet companies around large data competition is also high, the recent odd Tiger 360, Baidu, Tencent is bidding for Sohu's dog. The news is that Tiger 360 is to bid 1.4 billion U.S. dollars, in the form of cash plus stock purchase Sogou. And the value of Sogou is large data.

Recently, IBM, one of the world's largest data companies, officially announced a joint lab with Sogou, sharing platforms, technical resources and talent to develop the next generation data center and large data computing platform based on System X. The joint laboratory is the first IBM-oriented technology research and development Laboratory for the Internet industry in China, designed to promote further optimization of the Internet industry infrastructure by developing forward-looking technologies to help internet companies cope with big data challenges. This also makes Sogou's worth skyrocket, become the internet company to tackle "Tang".

In the "Twelve-Five" planning of the Internet of things, the information processing technology is proposed as one of the four key technological innovation projects, including mass data storage, data mining and intelligent image analysis, which is an important part of large data. The other three information-aware technology, information transmission technology, information security technology, also closely related to large data. This lays the national level of large data in the national economy position. But it must be said that China's large data has not yet formed a top-level design, it especially software companies in the layout of large data has lagged behind. This is mainly because domestic enterprises in the database, data warehousing, business intelligence and other areas of weak foundation. If, like the photovoltaic industry, herd, out of an extreme trajectory, gets, such a large data industry is likely to die in a stampede.

However, domestic enterprises to tackle large data market still have the opportunity, but need to find the industry and entry point. Experts are more optimistic about internet companies, such as Baidu, Alibaba, Tencent and other internet companies, than traditional it and software companies have more opportunities.

This time, Ma Yun has won a commanding point, other enterprises?

(The writer is the chief analyst of the media, financial media columnist)