Explore the value of big data to enterprises from the perspective of Tao.

Explore the value of big data to enterprises from the perspective of Tao.

This paper is more about how big data can generate value for enterprises from a higher level, perhaps what we call "Tao". There are many viewpoints worth learning and thinking about. This article is more of a direction and a relatively "virtual" description. If you have been engaged in big data work or data analysis related work for a period of time, I believe you have some experience in this article.

However, the realization of the value of big data and the real "landing" is definitely not a simple matter. How a company makes big data generate value is definitely not a slogan. It really needs the support of all aspects of the enterprise. In the early stage, we need to invest a lot of resources in technology, such as big data-related developers, data analysts and various machines.

The construction of data base is only the most basic work. If you really want to make the data have commercial value for the enterprise, and don't let the basic input of the data become a decoration, you need the support of the company's "culture", otherwise it will become a slogan just posted on the wall:

"Let the data speak! Act according to the data! "

"All decisions need data support!"

To generate value, data needs to be watered by the "culture" of the enterprise and infiltrated into the "soul" of the enterprise, which will involve the change of working methods, processes, habits and thinking of many people in the enterprise. This is often "painful". Take a look at this article!

First, big data really transforms enterprises from self-centeredness to customer-centeredness.

Enterprises are born for customers and the purpose is to make profits for shareholders. Only by serving customers well can we make a profit. However, in the past, many enterprises could not be customer-centric, because the amount of information corresponding to customers was not large, the mining was not enough, and the system did not support it. The current insurance industry is a typical example. The application of big data can restore the business object of an enterprise from the rough induction of customers (the so-called "customer base" of refining and induction) to live customers, so that the operation is targeted, the service to customers is better and the investment efficiency is higher.

Second, big data will subvert the traditional management methods of enterprises to a certain extent.

The management mode of modern enterprises comes from imitating the army, relying on layers of organization and strict processes, making correct decisions by layers of information collection and gathering, and then ensuring the implementation of decisions through the transmission and decomposition of decisions in the organization and the standardization of processes, ensuring the quality assurance of every business activity and avoiding risks to a certain extent. This used to be a useful and clumsy method. In the era of big data, we may reconstruct the management model of enterprises. Through the analysis and mining of big data, a large number of businesses can make their own decisions without relying on expanding organizations and complex processes. Everyone makes decisions based on big data and relies on established rules to make decisions. There is not much difference between CEO decision and front-line personnel decision. So do enterprises still need so many levels of organization and complicated processes?

Third, another important role of big data is to change business logic and provide the possibility of direct answers from other angles.

Nowadays, people's thinking or enterprise's decision-making is actually a leading logical force. We investigate, collect data, summarize and finally form our own inferences and decision-making opinions. This is a business logic process of observing, thinking, reasoning and making decisions. The logical formation of people and organizations requires a lot of study, training and practice, and the cost is very huge.

But is this the only way? Big data gives us another choice, which is to use the power of data to get the answer directly. For example, when we were studying mathematics, we learned the multiplication table of 1999 when we were young, geometry in middle school and calculus in college, and we encountered a difficult problem. We try to solve it by using years of study experience, but we have another way. We can directly search online to see if there is this problem. If there is, just copy the answer directly. Many people will criticize this as * * * and cheating.

But why should we study? I thought it was to solve the problem. If I can find the answer at any time, I can find the best answer with the least effort. Can't such a search be a bright road? In other words, in order to get what it is, we don't have to understand why. We are not denying the power of logic, but at least we have a new great power to rely on, which is the power of big data in the future.

Fourth, through big data, we may have a new perspective to discover new business opportunities and reconstruct new business models.

We look at the world now, such as analyzing food corruption at home, mainly by our eyes and our experience, but if we have a microscope and we see bad bacteria at once, then the analysis is completely different. Big data is our microscope, which allows us to discover new business opportunities from a new perspective and possibly reconstruct business models. Our product design may be different, many things need not be guessed, customers' habits and preferences are clear at a glance, and our design can easily hit customers' hearts; Our marketing is also completely different. We know what customers like and hate, which is more targeted. Especially microscopes and wide-angle lenses, we will have more new horizons. This wide-angle lens is a cross-industry data stream, which allows us to see things that we could not see in the past. For example, the car case mentioned above, driving is driving, and insurance is insurance, which is irrelevant, but when we pass the big data of driving to the insurance company, the business model of the entire insurance company will be completely changed and completely reconstructed.

Verb (abbreviation of verb) The revolutionary influence of data development on the technical architecture of IT itself.

Finally, I want to talk about the revolutionary impact of the development of big data on the technical architecture of IT itself. The foundation of big data is IT system. The IT systems of our modern enterprises are basically based on IOE(IBM minicomputer, Oracle database, EMC storage) +Cisco mode. This model is a vertically extended architecture, which is suitable for solving business processes with a certain amount of data under the established model. But in the era of big data, it will soon face the problems of cost, technology and business model. The demand for IT by big data will soon exceed the technical peak of the existing vendor architecture, and the growth of massive data will bring about the trend of de-IOE. At present, the horizontal expansion architecture+open source software instead of vertical expansion architecture+proprietary software is essentially brought about by the big data business model, which means that big data will drive a new round of architectural changes in the IT industry. The so-called national security factor in the IOE trend is completely secondary.

Therefore, Americans say that big data is a kind of resource, like big oil fields and big coal mines, which can continuously dig out great wealth. And unlike ordinary resources, it is renewable, and the more you dig, the more valuable it is, which is against the laws of nature. This is true for enterprises, industries, countries and people. Who doesn't like such things? Therefore, it makes perfect sense that big data is so popular.

The above is what Bian Xiao shared for you to discuss the value of big data to enterprises from the perspective of Tao. For more information, you can pay attention to the global ivy and share more dry goods.