Big Data predictions from the ten-side haze

What is the weather service like in the big data age? In the visible future, the integration of geographical information, socioeconomic and other multidimensional data, can let people know what might happen next moment, such as whether the wind will blow the door billboard, a high-speed junction in front of the rain is not a traffic jam.

In the past 2013, "Haze" has become the most disturbing hot word for many urban people. In Beijing, the government has even had to try to reduce emissions of various pollutants by means of site shutdowns, bus stops and factory shutdowns.

Where did the enemy of the ten "haze" come from? The arrival of the large data age may be traced to the fact that it helps people to understand and judge the most important aspect of the living environment-air quality more accurately.

The value core of future big data is forecast. China, director of the Institute of Information Technology, Weiping, China Advanced Technology Research Institute is carrying out a scientific research, through the collection and analysis of haze weather produced by various data, to find the main cause of haze weather. "This is some seemingly disorganized data, and we build a big database that looks for regularity." "This research project, working with Microsoft, is expected to provide a scientific basis for the government to govern haze weather once it has found the rules."

A new technology revealed on the Microsoft Innovation Day, October 30, 2013, tries to get people to understand the real air quality in their area. On this basis, people can make smarter and healthier decisions, such as when and where to fit outdoors, or when to wear a mask or close a window.

"These work are on the basis of large data can be carried out, no matter how advanced the model, no massive data entry, can not achieve very good results." "China Meteorological Bureau Public Meteorological Service Center senior engineer Tangqioghong said."

In the big data age, data does not simply refer to people's information posted on the Internet. The world's industrial equipment, automobiles, electric meters have countless digital sensors, at any time to measure and pass on the location, temperature, humidity and even the chemical changes in the air.

Microsoft uses data mining and machine learning techniques to make full use of large data, based on air quality data provided by existing monitoring stations and other sources of data in the city (including meteorological, traffic, mobility, road network structures, population concentrations, etc.) An implicit mapping between the monitoring information and the corresponding result is established, so that the urban air quality data containing fine particulate matter information can be inferred in real time.

What is the weather service like in the big data age? Tangqioghong that in the visible future, the integration of geographical information, socio-economic data of the meteorological services, can let people know what can happen at any time and place, such as whether the wind will blow the door billboards, a high-speed junction in front of the rain, will not happen to flash floods.

In fact, large data is at the foot, although many times we do not realize.

Global data volumes are growing at an alarming rate of doubling every 18 months, and the world is being digitally digitized. In fact, from urban traffic to air quality, from architectural design to film and television production, large data analysis applications have permeated every aspect of life. How do big data change people's lives? To this end, we interviewed Microsoft Microsoft, President Peter Lee, Microsoft Dean Wuen, the world's senior vice President Zhou Yijien, opened the mystery of big data.

Digital Business Age: What is large data and machine learning? What is the prospect of commercial application of this technology?

Wuen: I often cite an example, say your mother will come to Beijing to see you tomorrow, she tells you the flight number in the mail, will arrive 5 o'clock in the afternoon tomorrow. But you were in the meeting that afternoon, at three or four, the computer will automatically take out the flight number in the mail, the airline's website to check, tell you the flight late, to 7 points to come. And it will decide when to inform you when to start and how to proceed according to the traffic conditions. It can advise you how many minutes to take a taxi, take the subway, or even find a nearby friend to drive you on your social network.

These automation can be done, but today there is no such system and services, so only a few minutes to look at, a waste of time, and on many occasions not allowed. This kind of thing is actually large data and machine learning characterization, need a lot of different kinds of data, there are mail data, map data, aircraft data, traffic data. Large data is not only large, but also diverse and integrated.

Large data is also used in other areas, such as newspaper and magazine articles in the end how many people look, what we have to say, forward to whom. These things may have to be done before the questionnaire to get, today through the Internet more opportunities to access. If the large data collected are fragmented and complicated, how do you see them? This requires data visualization, which is important to managers. Before making a decision, the manager wants to see how this thing will react in a certain area, and pull it up and see.

Large data and machine learning is really a similar application in every industry.

Digital Business era: Some say that big data and cloud computing are two sides of the problem, and cloud computing is the foundation for a big data age. But what are the obstacles and challenges when big data and cloud computing really hit the ground, or the consumer?

Zhou Yijien: In fact, ordinary users have enjoyed a lot of big data and cloud computing benefits and benefits, but we are not clearly aware of it. For example, use Windows Phone for text input, enter the previous word, there will be the next word or words Hint association. or use a cell phone or PC to send and receive mail, spam filtering function. These are the technologies that integrate large data and machine learning to be realized.

Similar applications are ubiquitous, and there may be too many places, and we have ignored it.

Another typical example is about clouds. For example, we store photos on the phone in the cloud, even if the phone is lost and a new one, you can still download the photos from the cloud again.

Digital business Age: Wearable devices are like "the human body's internet of things", which can be used to detect data such as body temperature, blood pressure, heart rate, and so on. So where is the biggest opportunity for Microsoft to wear devices in the future, in hardware, in the cloud, or in software?

Peter Lee: There are three areas, but I am most heartened by the clouds. The reason is cloud, because cloud computing environment has a lot of data, a lot of computing power, plus machine learning function, can show very advanced intelligent products. For example, you can see from the cloud that you've had enough exercise in the past year to determine if the food you're eating is healthy enough, and to give you feedback to your doctor. These need to have a very good cloud architecture.