Big data in China

Chapter 2 Prologue

Big data in China
The first question this book addresses is, how should we understand "big data"?The English expression of big data is BigData, which means "massive data".The scale of data is so large that it can no longer be processed by current technologies and tools, so the bottleneck must be broken through, resulting in a data revolution.The processing of data includes many aspects, including collection, collation, classification, storage, analysis, prediction and delivery, etc.

Is big data as simple as that?of course not.Data is like the blood of the human body, and big data is the blood-related part of the entire human system.This concept was first involved in the fields of astronomy and genetics, because these two disciplines are very dependent on the analysis of data, especially the analysis of "massive data".It is also the product of the combination of computers and the Internet, because computers have realized the "digitization" of data, making them easy to store like numbers, and the Internet has realized the "networking" of data, allowing them to be transmitted freely and quickly through the network.

Since then, big data has truly possessed infinite vitality.The continuous development of Internet technology has penetrated into our work and life, coupled with the emergence and popularization of mobile networks, the Internet of Things and various other networked devices, an inevitable phenomenon is the rapid growth of data.90% of the data is generated after the emergence of the Internet. It is increasing exponentially in our lives. From massive to infinity, the world is being flooded by data.

What we need to pay more attention to is that data has changed from quantitative to qualitative, and it is reflected in many aspects, triggering the butterfly effect and promoting changes in other fields.

First, stimulate data thinking.A brand-new thinking mode, which was first brought to us by the arrival of the era of big data.A change in the way of thinking drives a fundamental change in the industry.This kind of change is even subversive, because thinking is the greatest productivity and the decisive force for the progress of social civilization.

Historically, the origin of business transformation is not a certain technology, but a change in the way of thinking.Thinking generates demand, and demand drives technology.With new thinking and a new perspective, people began to look down at the old economic system and traditional business concepts, think about and innovate business logic, and study more practical, advanced and efficient models.Conversely, if people cannot keep pace with the times, absorb and create new ideas that conform to the trend, and then use new ideas to reorganize resources, establish structures and formulate strategies, then the seemingly powerful volume will become a burden to continue to move forward-- Like the Qing Empire in the 19th century.

This kind of case of subverting the old order through new thinking not only occurs between national competitions, but also occurs frequently in the field of information technology.It always starts with the new thinking of information and technology, then penetrates into traditional fields, and then spreads to the whole society, changing every industry and every person.

Related cases are everywhere, such as Blackberry, Motorola, Nokia, Kodak, Yahoo, etc., such as Huawei, Lenovo, ZTE, Baidu, 360, China Mobile and their competitors-Google, Cisco, Microsoft, Samsung, Siemens, etc.

Data thinking is manifested in:
1. Analyze all data, not random sampling;
2. Do not pursue accuracy too much, but pay attention to the complexity of data;
3. More mining data correlation, rather than causality.Although the latter two are controversial in different fields, and there are differences in emphasis in the face of different needs, but in terms of data thinking, these three characteristics are enough to turn our world upside down.Of course, the decline of many super giants is not because they do not have data thinking-the reasons are always complicated, but in the final analysis they always fall on their own thinking.They are surpassed by new thinking and completely knocked down; if they do not catch up, they will be eliminated and withdraw from the stage of history.

The giants of the past lamented that they had not taken a step earlier, and the pursuers lamented where to find super thinking talents.Today, data-based thinking is the latest wisdom, although its power has not yet evolved to the point where giants can collapse.Be warned, though, that if you don't pay enough attention to it today, your name will be on the next list of fallen empires, one of the losers.Even if you are very beautiful now, when you are surpassed and defeated, you will be powerless.

Second, output "data assets".Thinking has fully demonstrated its power, and in the era of big data, another change is that data becomes an asset and is produced.This is because, when we need more comprehensive data to improve the accuracy of predictive analysis, we must create more cheap, convenient and automatic data tools to collect, process or produce data.Just like the bigger the room you live in, the more servants you need, and the greater their workload, and your requirement is that the servants should not make mistakes, and the faster the work, the better, and the more the better. You provide the perfect life.

What are these tools?The browsers, software, windows, and backdoor tools we use when surfing the Internet will record your various personal information data; the smartphones, GPS navigators, smart watches, or other digital products we use in our lives are generated all the time Data; there are also routers, smart toys, even TVs, refrigerators, etc., if they are connected to the network, they will also generate countless data while serving you.

When you go shopping with your girlfriend, you need to swipe your card and go online, so the card readers, routers, wireless WLAN and 3G networks, bank ATMs, and surveillance cameras in the supermarket are all collecting and generating data about you.

Unless you lie at home and do nothing - throw away your mobile phone, computer, landline and all your bank cards, don't go out to shop, become a complete recluse and disappear from this world, otherwise you are always a data-generating source, and is connected to an infinite Internet of data.Billions of people around the world have jointly formed a huge data production factory, providing almost immeasurable data assets.

Why do I say it is an asset?Because data means traffic in the Internet field, and traffic represents wealth.Traffic is used to monetize, it can be advertising, it can be games, and it can also be applied to e-commerce.People or companies who own these data can get huge benefits from it.At this time, business opportunities arise.

Therefore, before the era of big data opened, companies that realized the asset value of data had already begun to deploy.They have long focused on the source of data production-consumers, and sell data tools to connect people to the Internet and obtain people's data traffic.

Third, data assets can be realized.Although in fact, any asset can be realized, but no asset can exceed the value of "data".Once we have data assets, we must discover how much value it has through analysis, determine the direction of value through prediction, and classify the types of value through sorting, and finally "realize" it into user value, shareholder value, and even the value of the whole society.

In this process, the core link is prediction-this is also the purpose of big data analysis.Data is massive and complex; data is pervasive and pervasive, how to use practical technology to divide it?How to sort out the value trend from the data and establish a value chain through mathematical modeling?The most important thing is that we have to predict the possibility of the situation, and then formulate corresponding plans and take reasonable measures.

This aspect has a wide range of applications, such as the prediction of epidemics, stock prices, and economic trends.When the prediction is feasible and becomes a mechanism, people have the possibility to go further—to guide things in the desired direction through appropriate intervention.

For example, according to users' personal preferences and statistics on consumption ability, e-commerce websites recommend different products to them and guide them to spend more.The game company will analyze the player's behavior data during the running of the game, timely adjust the billing point and level difficulty for different players, and also analyze the player's consumption desire and ability to maximize the income from the player.Now all Internet companies have the ability of "precision marketing", and display different advertisements (personalized advertisements) to different users through appropriate technical means, so as to increase advertising revenue and help their advertisers improve their products. sales.

These examples are a good proof of the value of data assets and the plasticity of value.It is also a huge and complete industrial chain. Its analysis, forecasting and control technologies are also widely used in other industries, and are of immeasurable help to the improvement of our individual life, work and thinking.

The second question raised by this book is: big data is very hot, but how can it be turned into a broad and practical weapon instead of a temporary bubble?
We all have this feeling: big data is approaching and surrounding us, because now everyone is discussing, companies are discussing, the government is also researching, news is overwhelming, and theories are blooming everywhere.Data is also constantly being generated. Individuals, enterprises, government agencies, and the Internet are all generating data.All kinds of data are impacting us, and we have the feeling of "scattered flowers gradually fascinating the eyes" and "being in Lushan Mountain", and it is inevitable to feel confused and confused.

What should we mine from big data?How can enterprises and organizations complete transformation and transformation through big data?How should big data technology be practical and effective, so that it can be applied to everyone?These are general concerns, and to achieve these specific goals, we must first break down the barriers.The barriers are as much technical as they are mental and cognitive.Technical obstacles are the easiest to overcome, while mentality and understanding obstacles are often difficult to eliminate in a short period of time.

Judging from the status quo of big data development in China in the past few years, people have discovered new value from data and have made sufficient preparations at the technical level. However, the big data market has not yet been launched on a large scale (except for a few Several companies), the reason lies in the mentality, the lag of cognition and the fetters of old ideas.

Mr. Zhu, a manager of an IT company in Shanghai, gave an example of an incident he personally experienced.Not long ago, Mr. Zhu was driving on the road and was scratched by a motorcycle. Since the perpetrator refused to admit his responsibility, Mr. Zhu had no choice but to ask the relevant traffic control agency to obtain the surveillance video on the road, hoping to have an accurate account of the accident. identified.This is of course a good method, but the answer he got was: "Your request is okay, but you need to deposit your car in the traffic control department for 15 days, and the relevant data can only be retrieved after 15 days."

Mr. Zhu was very distressed: "It is obvious that something that can be done very easily and quickly, why is it done like this?"

This is a problem of perception or mentality.We know that even in a small county in China, cameras are installed on the roads and key areas; in large cities such as Bei, Shang, Guangzhou, and Shenzhen, sensors are already scattered everywhere.It is easy to collect and record videos, and these data also have the feasibility of providing more high-quality services for the society and the people.At the same time, the current big data technology can already process and analyze these data efficiently.But the fact is often the opposite, and people still cannot benefit from it. Some organizations care most about how much authority they have, rather than how many services they provide.Of course, relevant institutions also complain about this, and they also have their own reasons and frustrations.The reason lies in people's lack of service awareness, as well as the stubborn influence of old thinking and mentality, which constitute a solid resistance field, and everyone is deeply trapped in it, trying to figure it out, but they can't pull their legs out.

Big data not only has a wide application space, but also has a huge demand space.No matter in the fields of public services such as medical care, transportation, aviation, electric power, telecommunications, finance, and urban management, or in various enterprises such as manufacturing and innovation industries, there are new values ​​discovered from data and more personalized services provided. , Demand for more valuable services.In other words, we are fully ready for technology, but not yet for concept and awareness.Now China is vigorously promoting the construction of smart grids. Although the installation of smart meters is fast, the data integration at the back end is far behind. As a result, although users have installed smart meters, they cannot receive the services they deserve.For example, when there are only a few tens of kilowatt-hours left on the meter, the SMS reminder service cannot be obtained.This is exactly the same as Mr. Zhu's experience. It is not technically impossible, but the concept needs to be changed.Big data is in the ascendant and is continuously releasing more energy to promote our industrial upgrading, social transformation and enterprise transformation.If we want to benefit more from it, we need all the people to participate, break the ice, and change their minds.Only in this way can data become our "new energy source" instead of "hot potato".Only when these obstacles are first broken, can big data truly have unlimited application space in our lives and become the core driving force for social development.

To successfully break the ice and update old concepts, we must start from internal data and internal problems.Just chanting slogans and metaphysically studying specious issues will not achieve much practical effect.Enterprises, departments, and individuals with different goals and conditions can actually start their own big data journey and dig out more value from big data, but they must be down-to-earth, refuse empty talk, proceed from reality, and do small things Start from the details and lay a solid foundation.

Only by starting from the existing data, embracing customers as the core task, and solving internal problems as the basic starting point, can we effectively promote the development of our big data and successfully start the ice-breaking journey.For example, the public transportation system, after integrating the information systems of various public transportation platforms, integrates the travel of buses, subways and taxis into a "trinity", and people can use their mobile phones to check in real time how many minutes are left for the waiting bus. Arrive, confirm real-time traffic conditions and traffic congestion information, and choose your own travel tools and routes flexibly.

At present, the significant application effect of big data on enterprises and institutions is mainly reflected in two dimensions: one is to discover more business opportunities at the front end, to realize all-round care for customers, and to tap and expand greater value-added space; the other is to control risks , Improve efficiency and reduce costs.

A project manager working in a telecommunications company said to me: "Now the competition between telecommunications is becoming increasingly fierce, and the market will also be saturated. How to quickly control the market and user trends and formulate personalized and targeted marketing plans has become an important issue. The key to winning in the fierce competition. After adopting the new big data solution, we have directly improved the service speed and personalized service efficiency, and the feedback time of the data center has been shortened from the original two weeks to less than two days now. In this way, our account managers can obtain a large amount of information in real time, analyze customers' usage habits more effectively, and seize the opportunity to serve customer needs."

This is to grow on the basis of solving problems and break down obstacles on the premise of mining the value of data.For the specific application of big data in reality, especially for enterprises, they must first focus on customers and formulate strategic plans and their own big data blueprints.The second is to establish a data analysis system according to their own business priorities, and gradually improve the analysis and application capabilities of big data.The last is to customize quantifiable indicators to obtain return on investment.

Judging from the current big data practice, our application is mainly reflected in the integration and mining of existing data, and then to improve the application value of the client and drive the efficiency of the enterprise.If we want the data revolution to truly become the third industrial revolution sweeping the world and generate new productivity, there is still a lot of room for innovation.

For China, a great era has just begun.

Zhao Wei January 2014, 10 Beijing

(End of this chapter)