The era of data becoming productivity will come!

In today's society, data has been like air and water, surrounding us all the time. When we wake up in the morning, the smart Bracelet records our sleep time and quality. After breakfast, rush to work on the bus or subway, dribble, the traffic card reader has recorded our boarding place and time. Along the way, we brush our friends' circle, see and smell, and our mobile phones record our favorite content, or movies, or variety shows, or financial products. After work, I asked a few friends to have a meal. I opened the map to search for the evaluated restaurants nearby. The map left our traces. Every day, we are not only enjoying the convenience brought by the information age, but also producing and contributing our data as hard-working bees.

When it comes to big data, let's turn our attention to the scientists hundreds of years ago and see how data can bring great changes to our lives step by step. In 1600, our ancestors described the universe we are in with "the harmonious universe". In the middle of the picture is the earth we live on. There are 27 spheres around the middle of the earth to show the sun, planets and other stars we can see. Why 27 layers? Because these are the data that various planets or the sun can be observed around the earth at that time. Unfortunately, a spherical model cannot explain the real data observed. Therefore, considering that the sun needs to add three spheres, a planet needs to add three spheres, and so on. According to the observed data, a total of 27 spheres are needed to show the harmony of the universe.

From 1609 to 1619, Kepler discovered three laws of planetary motion, namely, the law of ellipse, the law of area and the law of harmony, by sorting out and analyzing a large number of observed data of planetary motion. However, the discovery of these laws is not an easy thing. Kepler first compared the astronomical phenomena at the same time of each year year year by year to eliminate the disturbance of the earth's rotation and revolution to the data, and then found the basic laws of planetary motion. It can be seen that even if we have a large number of observation data, we can't enjoy the beautiful scenery around us without a pair of eyes that are good at discovering "beauty". How can we have a pair of eyes, to appreciate the vagaries of cirrus clouds, to feel the colorful nature?

First of all, we need to be able to collect data from different dimensions and cross integrate them. At present, the development of the Internet is largely driven by the basic needs of consumption, entertainment, making friends and so on. Correspondingly, in the process of information system development, more attention is paid to the security, stability and management convenience of the system, while ignoring the relevance between different dimensions of data. In fact, the vast majority of enterprises and organizations that want to mine their own data value and conduct efficient knowledge management are facing similar problems.

In addition to different dimensions of data integration, cross fusion analysis of different platform data has a higher mining value. For example, it is very important for the 4S shop to accurately predict the sales volume in the next few months. Order too much, it is easy to cause product backlog, increase inventory costs. Ordering too little will lengthen the waiting time of users, drain potential customers, or reduce the customer experience. If we integrate the user's browsing and Q & a data in different communities, and further analyze the recent user's test drive data, we can build a model to predict the sales scale of different types of vehicles in the future. In addition, parking lot managers can also use users' online search, comment and test drive data to define competitors from the perspective of consumers, and then formulate corresponding competitive strategies.

With the development of information technology, the government, universities, enterprises and other organizations have recorded all kinds of data from different angles. How to mine the value of data under the premise of ensuring data security? It is very important to establish the analysis theory and method system under the background of big data. Statistical analysis of data refers to the use of sample data and statistical methods to restore the statistical characteristics of the overall data, through which to restore the full picture of the real world reflected by the data. In fact, the empirical statistical results of complex systems have found that, unlike the classical normal distribution hypothesis, many practical complex systems have the characteristics of power-law distribution, such as people's wealth distribution, the number of router connections in the Internet, the link relationship in the web page, the distribution of trading objects in the trade network, people's daily travel distance, protein folding and gene distribution The distribution of real systems, such as regulatory networks, is power-law. Taking the distribution of wealth as an example, the classical theory usually assumes that our distribution of social wealth is olive shaped, that is, the number of middle-income groups accounts for the vast majority, and the people with many or few incomes only account for a small part of the whole social population. However, the empirical data shows that with the increase of wealth, the proportion of people who occupy the corresponding wealth is declining rapidly. This law found in different real systems is very important for us to understand the simple laws in the complex world.

Now we also know that in addition to the system statistical analysis at the macro level, the analysis of high-dimensional and sparse data such as the individual's physical state, consumption mode, learning habits and driving habits at the micro level, as well as the statistical analysis of the consumption mode, risk preference and travel rules at the meso level (also known as meso level) are important for