You must know the big data

Source: Internet
Author: User
Keywords Big data big data can big data can Google big Data can Google big data big data can Google the big data through

If there is a technology company that accurately defines the concept of "big data", it must be Google. According to Komsko, a search research firm, only one months in March 2012, Google processed as many as 12.2 billion search terms.

Not only does Google store the network connections that appear in its search results, it also stores the behavior of everyone searching for keywords that accurately records the time, content, and manner in which people conduct searches. This data allows Google to optimize the sort of ads and turn search traffic into a profit model. Google can not only track people's search behavior, but it can also predict what the searcher will do next. In other words, Google can predict your intentions before you realize what you're looking for. The ability to capture, store, and analyze massive human-computer data, and then predict it, is called "Big data."

2012: Large Data Crossroads?

Why does big data suddenly get so hot? Why did the New York Times define 2012 as a "crossroads of Big Data"?

The fact that big data enters the mainstream is a combination of three trends:

First, many high-end consumer goods companies have strengthened their use of large data. Social networking giant Facebook uses big data to track users ' behavior in their networks, and by identifying your friends on its network, it gives new friends recommendations, and the more friends they have, the higher the viscosity between them and Facebook. More friends mean users will share more photos, post more status updates, and play more games.

Commercial website Linkdin uses large data to establish a link between job seekers and job openings. With Linkdin, headhunters no longer have to take their chances with a strange phone call from potential recruits, and they can find potential recruits and contact them by simply searching. Similarly, job seekers can automatically sell themselves to potential employers by contacting others on the site.

Second, all two companies were listed earlier in 2012. Facebook is listed on Nasdaq and LINKEDIN is listed on the New York Stock Exchange. The two companies, like Google, are ostensibly consumer goods companies, but they are essentially big data companies. In addition to the two, Splunk also completed its IPO in 2012, a large data enterprise that helps large and medium-sized enterprises provide operational intelligence. The public offerings of these companies have raised Wall Street's interest in big data. That interest has brought unprecedented pomp-and venture capitalists in Silicon Valley have been investing in big data companies. The big data will spark the next wave of entrepreneurship, which is expected to replace Wall Street in the coming years.

Third, Amazon, Facebook, LinkedIn, and other active users of data-core consumer goods, are starting to look forward to an unobstructed experience of using large data in their jobs, rather than just life and entertainment. Users have been trying to figure out why, since internet retailers can recommend reading lists, recommending movies and recommending products to buy, why their businesses can't do anything like that.

For example, since a car rental company has information about a customer's past car rental and the inventory of available vehicles, why can't these companies be smarter about providing the right vehicles to different car owners? Companies can also use new technologies to leverage public information-such as the status of a particular market, meeting activity information, and other events that may affect market demand and supply. By combining internal supply chain data with external market data, companies can more accurately predict what vehicles are available and when.

Similarly, retailers should be able to combine open and internal data from outside to use this mixed data for product pricing and market layout. At the same time can also consider the impact of the spot supply capacity of a variety of factors and consumer shopping habits, including which two products to match will sell better, so that retailers can increase the average amount of consumer purchases, so as to achieve higher profits.

(Responsible editor: The good of the Legacy)

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