The concept of large data is in a mixed era

Now, the concept of large data is in a mixed era, the media is flooded with a variety of reports on large data, but there are some far-fetched, impostors, some media even the simple statistics on the title of "Big Data".

But the big difference is that the most important feature is the "use of data to find opportunities", but in the past, there are problems in finding data. Big data, must have a pre-sentence, is what data you have to be refined to solve the blind spot.

In fact, as early as 15 years ago, some of my friends have begun to show the "Big Data" charm. In the early 90, I met some professional betting-making friends who formed a team that could earn HK $ hundreds of millions of a year by racing. I was surprised to learn that a lot of people are going to lose their money on the racecourse, but they can turn this probability game into a steady profit tool. Their secret, it turns out, is to use a "data-raising" strategy-recording every race. At that time, I thought it was very strange: "The TV has been recorded in the game big data like Ah, but also to record a race to do?" ”

Later I learned that they would have taken different video recordings of races in every game. Through these videos, they analyze what the riders and horses are doing, what the consequences are, and then "clean" the data into a more accurate (Smart data). What struck me most was the fact that they did not look at the surface data, but instead looked at the core data from the opportunity for unlimited data.

There were many accidents in the course of the race, and they used the data to restore the speed of the horses in conjunction with different jockeys in different venues, if not accidentally. In this way, they can more accurately judge the strength of each horse and the opportunity to win, so, through the unknown data collection, recorded hundreds of millions of yuan.

This is what I've seen, the earliest use of large data to make business decisions. As a person who has dealt with the data for more than 10 years, I know deeply that the operation data from "seeing" to "using" and "using" to "keeping" is a complicated process in itself. The data volume of large data is definitely not the most important problem, we want not the quantity of data, but the quantity of "quality", which is the actual data.

We need to have a commercially sensitive data-making framework that enables companies to "look" more accurately and to judge what is right and what is wrong in the near future. Second, let the data really from "see" to "use", let data become the important part of building enterprise productivity. Again, let the data Marvell (DT strategy) penetrate into every corner of the enterprise, making it easy to use, from production, collection, usage, sharing and feedback. Finally, let DT strategic landing also pay special attention to data stability, accuracy, timeliness and effective implementation.

In this volatile data age, only the data to become a commercial tool to winning.