阅读笔记金融英语

The bestselling book named PREDICTIVE ANALYTICS is the one that I

choose to read and to write for a report. Although I am a student major

in computer science, I am also interested in business analytics. Actually I

have an idea about changing my major into Finance during my gradual

time. So let us talk about this amazing book.

Eric Siegel is the author of the book who is an outstanding

Columbia

University professor and a pioneer in business analytics field. He and his

book have been featured in Businessweek, CBS MoneyWatch,

Forbes,

Forrester, Fortune, The Huffington Post, The New York Times, Newsweek,

The Wall Street Journal, The Washington Post, and WSJ MarketWatch. In

his book, he is making his effort to fulfill the world about predictive

analytics. In other words, we are going to understand how captivate the

analysis is and what is the point that will lead to the prediction.

This book is been divided in to several sections. These chapters are the

gradual processes to let us know the PREDICTIVE ANALYTICS. There are

so many uncertainties in the information era. As we all know, the further

is undefined, but if we collective the most useful messages, we can make

predictions based on those information. And predictions will help the

humankinds to avoid business risks, violent crimes, and increase sales

performance.

In the first section, the author gives us some conceptions about the basic

of prediction analytics. He also describes the importance of a company

to adopt the prediction analytics system. By foreseeing the changes and

risks of a person’s assets, the company can make its own strategies from

the predictions when competing in the world. “Data is a new type of oil”

says by Meglena Kuneva, a member of European Consumer Council. That

kind of idea is accordance to the author’s thinking. The forecasting which

is drawn from data will led to huge influence to an organization and bring

profits. That’s sounds magic! The major way for prediction analytics is

observation. The machine will observe massive information and put the

haphazard date in order. In return, the computer will build models to fit

for the appearance of our daily life and make predictions. From this

chapter, I have learned the surface of prediction analytics.

In the next section, there are some doubts on prediction. Some people

have plenty of suspicious on this new technology. Why? It is because that

some companies may use this new way to make predictions on a person

private life. For instance, supermarket will foresee which person is going

to give birth recently. This behavior gives offense to people. On the other

hand, if we use the data prediction in other filed, it will have significant

influence on our life. We also use the example of supermarket. If the supermarket makes well predictions on a family that is going to have

birth, they can put the advertisements to the parents to increase the

products selling. That will bring more profits and save cost because

supermarkets do not have to send majority advertisements to all kinds of

people. The author thinks that data manage is more efficient an easier

than manage people. We can spend less money to gain customers’ data.

In return, the value that a customer will bring to the company is far

beyond the cost. We have to follow the law to keep personal private or

the data will literally erode us. The more the data we gain, the more

responsibility we will take. He takes the knife as a metaphor about data

that some people use knife to cut vegetable, and some people use knife

to commit a crime. So we have to make detail rules to protect the

security of data.