Big Data Handling Methods

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 past two years, the big data has been widely discussed by the public, and even become the selling point of many business marketing. Undoubtedly, the development and popularization of intelligent devices make the mass data collection possible. But the big data is not pure "data big", it contains a kind of calculation and thinking way change, want to exert big data insight, still face the challenge of collecting, managing, analyzing data. How can these obstacles be broken? How can large data be used in the future to create greater value? These questions are worth our cool judgment in the heat of the big data. April 26, Tsinghua University set up "Tsinghua ...

The big data boom has sparked a major change in thinking, production and lifestyles, and it can be said that a new era has been opened up. For the financial industry with natural data attribute, on the one hand, large data can provide sufficient information support for the operation and management of financial institutions. On the other hand, large data-breeding new financial forms pose serious challenges to traditional financial institutions. What the financial institutions will do in this great social revolution is very much expected. 　　To this end, The Economist has invited a number of senior managers of financial institutions as well as industry experts to explore the financial sector in the big data era of change and development. ...

This article originally contained the FT website, original title: Big Data:are We making a big mistake, it seems that I saw a bit late, but still share it. Because it does discuss some of the issues I've been thinking about recently, it's a speculative article. 　　If you've never known big data before, this can be considered a primer. This article is only opinion, because the query is more simple than the proof, but the big data is now hot, these negative comments, if as a conversation to collect, is also good ...

The big data is a vague and ambiguous term used to describe a large-scale phenomenon that is now rapidly becoming the focus of entrepreneurs, scientists, governments and the media. The big data is impressive. 5 years ago, a Google research team published a remarkable study in the world's most famous science journal Nature. Without any medical test results, the team was able to track the spread of flu trends across the United States at the time, and it was even faster than the US Centers for Disease Control (CDC). Google's tracking is only later than the outbreak of flu ...

If one day can predict the future, then what are your first things to do? Buy lottery? That second, third thing? Selling a first off, we talk about it later. Big data is an industry, broadly speaking refers to the whole product chain of mass information generation, dissemination, collection, processing and value creation in the era of information overload. In the narrow sense, it refers to the related industries of big data storage and processing and data mining. The most common use of big data on the market today is in analysis and prediction. According to myself in this industry for 10 years ...

With the emergence of new channels and technologies such as social networks, mobile computing and sensors, a large number of new data have emerged. We live in an era of exponential growth in data, and conventional technology has struggled to cope with the massive amount of data at PB (1024TB) levels. We have entered the era of diversified data. How do we deal with such a large data structure and the age of unstructured information? "The advent of the big data age is beyond doubt," he said, as he interviewed Teradata, Stephen Brobst Baoliming, chief technical officer. Only those ...