Stanford Data Analytics

The time is 1948, the location is Northeast China. Liaohsi into the critical phase. For the commander of the four field army Lin Biao, the most important goal after the Jinzhou is to defeat the Kuomintang new six troops. The method used by Lin Biao is to listen to the "intelligence report" every day, and the officers on duty should read out the situation and seizure of the troops. It's almost uniform data, and it's boring. Until one day, Lin Biao suddenly discovered that in a two-armed encounter in the Hu Shack, the ratio of the spear to the spear was slightly higher than the other battles, and the proportion of the car and the cart was slightly higher than the other battles.

The time is 1948, the location is Northeast China. Liaohsi into the critical phase. For the commander of the four field army Lin Biao, the most important goal after the Jinzhou is to defeat the Kuomintang new six troops. The method used by Lin Biao is to listen to the "intelligence report" every day, and the officers on duty should read out the situation and seizure of the troops. It's almost uniform data, and it's boring. Until one day, Lin Biao suddenly discovered that in a two-armed encounter in the Hu Shack, the ratio of the spear to the spear was slightly higher than the other battles, and the proportion of the car and the cart was slightly higher than the other battles.

The time is 1948, the location is Northeast China. Liaohsi into the critical phase. For the commander of the four field army Lin Biao, the most important goal after the Jinzhou is to defeat the Kuomintang new six troops. The method used by Lin Biao is to listen to the "intelligence report" every day, and the officers on duty should read out the situation and seizure of the troops. It's almost uniform data, and it's boring. Until one day, Lin Biao suddenly discovered that in a two-armed encounter in the Hu Shack, the ratio of the spear to the spear was slightly higher than the other battles, and the proportion of the car and the cart was slightly higher than the other battles.

The time is 1948, the location is Northeast China. Liaohsi into the critical phase. For the commander of the four field army Lin Biao, the most important goal after the Jinzhou is to defeat the Kuomintang new six troops. The method used by Lin Biao is to listen to the "intelligence report" every day, and the officers on duty should read out the situation and seizure of the troops. It's almost uniform data, and it's boring. Until one day, Lin Biao suddenly discovered that in a two-armed encounter in the Hu Shack, the ratio of the spear to the spear was slightly higher than the other battles, and the proportion of the car and the cart was slightly higher than the other battles.

In the "Up" section of the big data on Silicon Valley's observations (http://www.china-cloud.com/yunjishu/shujuzhongxin/20141208_44107.html?1418016591), I have basically combed through a relatively complete shape of the big data growth situation in the Silicon Valley region. A friend saw the "next" after the notice on the micro-blog to give me a message, I heard that the next chapter to introduce some of the company's large data department, ask if you can add a Google, especially Google ...

The large data in the wall are registered as dead data. Large data requires open innovation, from data openness, sharing and trading, to the opening of the value extraction ability, then to the foundation processing and analysis of the open platform, so that the data as the blood in the body of the data society long flow, moisture data economy, so that more long tail enterprises and data thinking innovators have a colorful chemical role, 　　To create a golden age of big data. My large data research trajectory I have been 4-5 years of mobile architecture and Java Virtual Machine, 4-5 years of nuclear architecture and parallel programming system, the last 4-5 years also in pursuit ...

A few weeks ago, when William Lansing, chief executive of FICO, attended Stanford University's Big Data conference, he found that the industry's heated discussion of big data had increased from three "V" to four "V", that is, volume (data volume), produced (data type) , velocity (processing speed), and value (data values). and the fourth "V" means that the industry is starting to focus on data insights, emphasizing how to get the value of large data. "The value of tapping data is exactly the more than 50 years since FICO was founded ...

Teradata, chief executive of the Greater China region, Singlun, said in an interview with Sina Science and technology, with the arrival of large data era, enterprises should be in the internal training of three kinds of ability: first, the ability to integrate enterprise data; second, explore the value behind the data and the ability to develop precise action programmes; The ability to perform accurate and rapid real-time operations. Data rapid growth Teradata Company is an intelligent analysis solutions vendors, mainly for enterprises and government agencies do data integration, analysis, exploration, mining data behind the value, thereby enhancing customer production competitiveness ...

Data visualization is the most challenging and challenging part of data analytics, but its importance does not allow us to question it. In fact, visualization is definitely one of the most important parts of analytical data analytics. Of course, storage, database query processing and algorithms are all very important. And without them visualization is impossible. But in a data-driven world, they are just at the base level. Here are six startups who are trying to radically change the visualization of their data. Some of them are highly complex visual processes, some are not. Although none of them is perfect ...

In 2006 Jonathan Goldman went to the business social networking site, LinkedIn, when LinkedIn was just a start-up, with fewer than 8 million registered people, but many members invited their friends and classmates to join, so the number of registrations increased rapidly. But it is not easy for users to find users who are already registered on the site, and the ratio does not meet the expectations of managers. Obviously, some social experiences are missing. As a LinkedIn manager says, it's like, when you get to the conference reception, you find someone ...