Big data is just a concept or a practical one

Since last year, the word "big data" began to appear frequently, whether in the Internet industry or in other industries.

The "concept" nature of things in China's internet circles can always be spread quickly, there are many reasons, including the overall atmosphere: most of the internet entrepreneurs are hoping to change the world through forward-looking innovation, by the capital sought, and finally cash out. In this process, the concept of rapid spread, packaging, become a variety of tagged products. But the pragmatist only passively accepts, lacks the correct cognition profound exploration.

It can be seen from the 2008 Big data concept began to spread, in Baidu and Google's "Big Data" and "large" search trends (data Baidu's PV weighting processing, and Google equal to reflect the trend contrast):

The word big data, Baidu's Chinese search the explosive far higher than the English Google search.

This is the legendary Silicon Valley technology maturity curve (speculation cycle), and in the domestic Internet industry has been passed on and carried forward more powerful.

A joke: "The current big data in the country, is like a bunch of adolescent children talking about" sex ", everyone likes to talk, if not talk about as if they are not normal, but only a few people really have experience. Really experienced, but mouth shut, smile just ". The internet industry has grown rapidly, and these children will be adults sooner or later, but so far, the vast majority of beneficiaries have been just labeled vendors, like vendors selling illegal publications to adolescent children.

What is big data exactly?

So what is big data anyway? Is big data just a concept or is there a real future?

First of all, all the data is the function of looking for the law.

materialist dialectics says: The world is material, material is movement, movement is regular, and law can be mastered. Whether it's the earliest statistics, data analysis after the advent of computers, data mining, and big data up to now. We are all exploring the laws of the world, trying to understand the world by law.

In the absence of computers and the Internet, senior scientists laid the groundwork for mathematics and statistics. After the advent of computers, the ability to store and compute data has increased significantly, and the ability to collate and analyze data has increased significantly. And the advent and development of the Internet, so that the collection of means to further enrich the volume of data greatly increased. The game is constantly enriched by data-seeking patterns.

This process, the data on the one hand is getting bigger, on the other hand more and more "small", how to say: The process of evolution can be simply said to "the overall sample coverage" and "the value of micro-data exploration." The essence of the data is the sampling and the model, because the technical means cannot acquire all the object characteristics, only through the partial simulation all, through the abstract model to describe the object. After the advent of computers and the Internet, the ability to access information, and the analysis and mining capabilities of the data are greatly enhanced, the sample to try to cover the more and more large, and the object itself is more and more detailed description.

Like we want to know the quality of this car apple. Previously only randomly sampled 100, to see whether the appearance of bad damage; Now sample 7,000, each apple with more than 30 data to describe the characteristics and quality of apple. You don't need to take a sample of 100% to get the data, then each Apple more than 100 data describes the characteristics and quality, even the entire growth cycle data.

But whether it's statistics, data analysis, data mining, or today's big data. Our mission has not changed from start to finish: by collecting, collating and analyzing data, we find patterns, infer nature, and even predict the future.

At any stage, the task is limited, and we can only speculate on the nature of the object, not all of it. In the development of technology to a certain stage can produce new technologies and methodologies, but also in the speculation and forecasting a step closer, out of this step can greatly improve productivity, which is the value of big data.

Examples of specific industries

Next we choose an industry that is easier to abstract and illustrate: basketball (NBA).

Early in the NBA, due to the lack of commercialization, the statistics on a game are very limited, whether the players, coaches, or team managers know the players in an intuitive, or the most basic statistics.

The NBA began its full data statistics in 1986. So now the news all love to use: "Since 1986 has statistics, this is the Nth player single field to play XXX data ..." NBA statistics officially entered the modern, database technology successful application, so that you can easily find historical data from www.nba.com.

And from this day on, another topic emerges. As we like to put the martial arts characters in the martial arts column, rank, data integrity, a large number of data references become a new hobby of the media. So, "scoring weapon", "Defensive titans", "shooting master" these words, gradually by "how many points per game", "complete how many rebounds + capping", "shooting hit" and so on. All the fans are starting to like the data.

But looking at the data, it will be difficult to understand: when the young Marbury, a field of 20 points 7.6 assists, how can be called lone wolf? Look at the data, it will be difficult to understand, Bowen this data is bland, steals no gorgeous guy, defense is far more powerful than the two-term steals King magician? How can understand, Stoudemire career field are 8.8 rebounds 1.4 caps, Garnett in the Celtics also on the field are 8.9 rebounds 1.4 caps, but kg of defense and Stoudemire, that is the difference?

In fact, because the data is too simple to describe a player's microscopic data, there is simply no way to use data to describe the role or characteristics of a player playing on the pitch.

21st century, the details of micro-data more and more into the NBA, professional NBA data mining company Synergy Sports appeared. "SI" revealed a basketball god Jordan's professional statistics: the bull 80.2% offensive to the hands of his hand, 83.9% of the shooting is a jumper, 54.3% of the shooting from the right side of the stadium, 17% of the offensive from the opening of the singles , 2.67 steps after the first step to pull the jump, opponent interference in place, the hit rate is 46.3%, and so on.

To this point, the data began to enter the new era. And this year's NBA playoffs, the United States media began to run the field are running distance, speed, the fastest speed, and so also added to the analysis of the dimension. New technology has increased the value of micro-data exploration. Maybe we can call it: Big data.

Look at Big Data right

Data does not lie. But to be precise about one thing, it takes enough data and enough microscopic digging. But the data will never be more than enough. For example, basketball games, data and perception, will always be intertwined. More and more data models will give the result of an infinitely close impression, but when the data or perception of either side eminence, talking about basketball is no longer fun. No matter how understanding the data, but also need to coach design tactics, play players specific, motivate team morale, to win the game, the data itself will not "win the ball."

Big data is a progression, but we have absolutely no need for mythology, and there is no need to be an ogre. Big Data is a concept, and it is only a logical product of our understanding of the development of the world at this stage. Rational view of big data, let good for production and research services, more to play our own innovation and initiative, will be more valuable.

Big data is just a concept or a practical one