Christopher Surdak Talk About Changes In Big Data Era

The world must be changed.

You have to ask yourself whether it is to change the world, or to let some of you in the world change you.

A very large German ERP company predicts that many of the world's top 500 will be in the future.

It will disappear. 40% of the top companies like the Titanic will fall off the world.

Emerging enterprises will come out, this trend will not stop, big companies will die faster and faster, and new companies will go faster and faster.

Over the past 15 years, we have kept asking these questions: who are the customers, what products they need, what prices they need, but now the opposite is true. We need to know not only what they are, but also why.

We need to care why customers buy, why buy at that time.

The more we know about our customers, the more precise we will be for our customers' needs.

The most important point of big data analysis is that when we have different

In the first place, we must keep the timeliness; secondly, predict what to do next. We need to make a predictive analysis.

The last point is also very important. When an analysis result comes out, the enterprise must act. This action should be told to consumers in the first time, "I know you".

One case is Amazon, which will make a predictive analysis to deliver goods through the shortest distance to their customers' homes.

When you haven't made any purchasing choices, he forecasts what purchases you may make in the future.

Amazon has a very good command of customers. Not only can you predict that you want to buy it, but you know you will be very happy if you pass it.

This process requires strong data support to understand customer psychology and customer ideas. When you send freight to their home, he will feel that you understand him.

Although they are what the customers want, they want you to understand me, but if they feel that you are too much in their own lives, "if you understand me too well, I will feel panic."

This is the sense of "discomfort" corresponding to "intimacy".

When you cross this boundary line and make him feel uncomfortable, he will leave and feel that you are not a good platform.

Now everyone is talking about a company called Uber.

Taxi companies used to think that they could send passengers to the destination they wanted, but that was far from enough.

Consumers are more concerned about whether they can get on the bus at the fastest speed.

Uber has done so, so it has become the largest taxi company in the world, but in fact, no car belongs to them.

They can earn 41 billion dollars a year, and the traditional taxi companies are now in a crisis of survival.

We can see this kind of business mode in different fields.

Large scale subversion will take place in the following situations: first, the existing data and new data match each other to provide new insights; second, data analysis involves mobile data, social data, cloud data, game data, and a deep understanding of customers and understanding of suppliers.

That is to say, if you bridge the bridge of the data, you can subvert the industry.

Let's take a look at these application cases.

First, face recognition system.

From the moment of entering the door, the face is quickly snapped. By face recognition technology, we can clearly know who the person is and where he will go.

Two. A monitoring system on the streets of Shanghai.

When pedestrians arrive, cameras will grab faces to see if they are within the scope of the police search.

Let's assume that the suspect is coming. He will quickly locate him on the wanted list.

Three. A system of London underground.

When everyone walks, the system will record how many times he walks, and whether he is in good health.

This case has been landed for 5 years.

Now there are very smart toothbrushes, every day to record when you brush your teeth and brush your teeth in place.

If it is not in place, it will pmit information directly to your dentist, so the data generated by many applications of the Internet of things will affect your consumption needs.

For many large companies, they feel that they are somehow protected by the government and laws and regulations, and feel that they are invincible.

The most important thing they say is "no, I don't want to change".

But for small companies, any opportunity or innovation is for them: "yes, I can change", so the opportunity may be on them.