What's happening in Silicon Valley is the real application of big data

When you see a batch of takeout apps trying to dig people out of Uber, you have to respond to this phenomenon. In fact, "Uber more and more like Amazon, selling more and more like Uber" is becoming a new phenomenon in Silicon Valley, and the logic behind the three types of companies is based on large data logistics.

You may find it hard to hear at home doing takeout companies will and you emphasize that it's not just about delivering food, it's actually a http://www.aliyun.com/zixun/aggregation/7962.html "> logistics company, but yesterday the Silicon Valley was a delivery take-out mobile That's what App SpoonRocket told me:

"We are actually very much of a logistic company and now we are ethically food."

Uber said a year ago that he was a logistics company, just doing a taxi. If SpoonRocket, Uber are logistics companies, the flow of talent from the Amazon to Uber, from Uber to SpoonRocket is also taken for granted, their core is the urban transport and logistics data collection, and processing and analysis of these data capabilities.

medical field

The first case I'm going to say is how big data can reduce the number of first aid in American hospitals.

Because the cost of first aid is expensive and many patients in need of first aid do not have health insurance, the U.S. government is spending a lot of money on first aid, but a recent non-profit organization, Code for America, found: In fact, the crux of the U.S. hospital emergency is not a lot of people on the emergency phone call, It's that there are always some people who make emergency calls again and again.

One example they gave me was an old man who was found to be in the emergency room for a stroke four times in one months, but the reason was not that the old man had no medicine to treat the stroke, but that the old man's family was always stealing her pills for money.

The solution thus became very simple, and that was to buy her a medical box with a lock. Since then, the old man has not had a stroke.

So if the U.S. government is going to save money, they just need to find the patients who use the bulk of first aid resources and then solve their deeper problems before they are sent to first aid. The next step is how to collect big data, which involves the cooperation of various parts of the United States: The Fire Department, the police department and the town Planning Bureau.

Because the fire department and the police department have each kind of emergency call, information such as address and time, the two departments can basically determine which addresses of patients in the frequent emergency call, and the Town Planning Board (or Trade and Industry Bureau) has this address of what kind of building information, it can be used to decide what kind of personnel to send.

For example, if the address of 4 emergency calls in one months is "residential building", then a nurse should be sent to see what the situation is, and if the address of 4 emergency calls in one months is a "restaurant", then it is necessary to send other kinds of people.

Traffic Management Department

Traffic is a big hot spot, a lot of valuable information is produced at all times, but different traffic information systems are designed to make a difference, such as a subway or subway ticket station to determine which station the passenger is entering from, and which station to exit from;

The data of the two systems are separate and useful, but if you integrate them, you can basically know how many passengers, how crowded they are on a certain bus at some point, such as if it's too crowded, you can decide to increase your capacity.

Another example: A passenger from A to B, he needs to take the bus first, and then ride the subway. Typically, the passenger data is available on both the Metro and bus systems, so data to the U.S. traffic administration, even if only a passenger from a to B, is considered to be two different journeys.

But what happens if you integrate the bus and subway data? U.S. traffic management will link two trips from A to B, which is considered a trip, and if a large number of people actually the requirement is actually from a to B, not from a to a middle point C, then the city government will consider whether to do a direct from A to B Route.

Takeout Company

In San Francisco, the start-up companies have been very hot, sprig and spoonrocket have received tens of millions of dollars in financing, their model is on the Internet or mobile phone orders, and then they hire people to do healthy and nutritious fast food, send people to the hands of users. Important information, sprig in early June recruited Uber Big data of Angela Wise, and SpoonRocket has just recruited a person to make big data.

Why is it that a takeaway is so enthusiastic about big data? Because through user data analysis, they can predict in which area, what time the user's order may be bursting, thus, the take-away company can adjust the capacity in advance and shorten the user wait time, Because the user experience of the take-away company depends greatly on whether or not to deliver the fast food within 10-20 minutes after the user orders.

These companies also use large data to optimize the route of take-away vehicles, with the aim of ensuring that fast food is delivered to users in the most efficient and cost-effective manner.

Of course, the U.S. here is not like the take-away in China's office, it is not a daily 11:30 to write a list, and then sent to the 12, the United States are basically the takeaway at any time, ready to send, so it is very important to make predictions.

In fact, large data applications also play a guiding role in corporate expansion decisions. The founder of SpoonRocket, for example, told me he was thinking of jumping out of San Francisco into other cities on the west coast like Los Angeles and Seattle, but which City did the most good for spoonrocket business? Big Data can help him out of different city priorities and make SpoonRocket Can choose to enter the city first.

I wrote this aspires into a cafe on Shattuck Ave, Berkeley. You tomorrow.