Everyone must have a lot of feelings after tasting a book. Now let's write a thoughtful comment. How to write a review and avoid writing a "running account"? The following are 1000 words carefully compiled by me in the era of big data, for reference only. Let's have a look.
After reading the era of big data, 1000 words 1 Now when it comes to new media and the Internet, we have to mention big data. It seems that if you don't say this, you will be out. What's more, there are still many people who follow suit, and many empty talkers haven't even read the classic work in this field-The Age of Big Data by Schon Dove. Who is Schoenberg? He is currently a professor of governance and supervision at the Internet Institute of the Network College of Oxford University, and was the head of the information supervision research project at Kennedy College of Harvard University. His consulting clients include Microsoft, Hewlett-Packard and IBM, and he is the real maker and participant behind the official Internet policy of the European Union. He has also served as a think tank for senior governments in many countries. This Oxford professor, who is known as the "prophet of the era of big data", is really awesome! So, the master said the golden rule? Not necessarily. You must do some homework when reading the works of the masters. If you can do your homework and have a corresponding theoretical basis, you can have an ideological dialogue with them.
Schoenberg discusses big data in three parts, namely thinking change, business change and management change. In the first part, "Thinking Change in the Age of Big Data", Schoenberg clearly stated his three views: First, more: not random samples, but all data; Second, more miscellaneous: not accurate, but miscellaneous; Third, better: not causality, but correlation. I disagree with the first point. On the one hand, it is very difficult to process all the data in terms of technology and equipment. On the other hand, is it necessary for everyone? Is it necessary to collect all the data for data analysis to judge simple facts? I have discussed this issue with Professor Jonathan Zhu from the City University of Hong Kong. Professor Zhu is an expert in communication research methods and data analysis. He thinks that we can find a method of mathematical statistics for analysis, and we don't necessarily need all the data. In connection with the relevance mentioned in Schoenberg's second point of view, I understand that the total data he said refers not to quantity but to range, that is, the random sample of big data is not limited to the target data, but also includes all data outside the target. I don't think big data analysis can rule out random sampling, but the method and scope of sampling should be expanded.
I agree with Schoenberg's second point. I think it is a good supplement to his first point of view, and it is also a reflection on precision communication and precision marketing. The simple algorithm of big data is more effective than the complex algorithm of small data. "More macro vision and oriental philosophical thinking. I can't fully agree with Schoenberg's third point of view. " Not causality, but correlation. You don't need to know why, just what it is. Communication is data, and data is relationship. In the era of small data, people only care about causality, but they don't know enough about correlation. In the era of big data, relevance plays an important role, which cannot be overemphasized, but it should not be completely ruled out. Where does big data come from? What is it used for? If we completely ignore causality and don't know the cause and effect of big data, it will also dispel the humanistic value of big data. Nowadays, in order to elaborate and spread their views, many scholars often make surprising remarks and completely deny old ideas.
The complexity and diversity of anything in the world are not simple either-or. Is Schoenberg also such a naive thinking of binary opposition? In fact, when reading, readers must see clearly what context they are saying, and don't fall into the misunderstanding of taking things out of context because of the shallowness of reading. For example, Schoenberg proposed "not causality, but correlation." In this paper, he also said in the book: "In most cases, once we have completed the correlation analysis of big data and are no longer satisfied with just knowing' what', we will continue to study causality at a deeper level and find out the' why' behind it." [i] It can be seen that all the data and related relationships he said are in a specific context and are options in data mining.
One of the driving forces of big data research is commercialization. In the second part, Schoenberg discusses the business changes in the era of big data. Schoenberg believes that digitalization means that everything can be "quantified". The quantitative analysis of big data can effectively answer the question of "what", but it still can't completely answer the question of "why". So I think we can't rule out qualitative analysis and qualitative research. There is no doubt that data innovation can create value. When discussing the role positioning of big data, Schoenberg still put it in the commercial system of data application, but not in the whole social system, but he discussed this issue in the second part of Management Change in the Age of Big Data. In the risk society, the problem of information security has become increasingly prominent, and data dictatorship and privacy protection have become a pair of contradictions. How to get rid of the dilemma of big data? Schoenberg tried to answer in the last section "Control", but it was basically a cliche. I think maybe kevin kelly's Out of Control can help us answer this question? At least it can provide more thinking dimensions. As Schoenberg said in his conclusion: "Big data is not a cold world full of algorithms and machines, and the role of human beings cannot be completely replaced. What big data provides us is not the final answer, but the reference answer. Help is temporary, and better methods and answers are still in the near future. " Thank you, Brother Xun! Let the big data discussion return from natural science to humanities and social sciences. It can be inferred that "big data era" is not the final answer, nor the standard answer, but the reference answer.
In addition, before reading this book, you must have some basic knowledge and concepts of data science, such as what is data? What is big data? What's the difference between data analysis and data mining, and what's the difference between digitalization and dataization? Do some homework before reading, it will be easier to read.
After reading the era of big data, we are no longer keen on finding causality, but should look for the relationship between things. This proposition is my biggest feeling when I read this book. Personally, it is also the core idea of this book. Let's start from the beginning. First of all, the book puts forward a proposition that subverts my previous cognition-"it is not atoms but information that is the source of everything", and regards the world as an ocean of information and understandable data, which provides us with an unprecedented perspective. This is a world outlook that can penetrate into all fields of life. This idea is described in a paragraph in the last part of this book. I put it at the forefront because I think it is the premise of talking about the digital world, and naturally it is also the premise of talking about big data. There is a section in the middle of the book about the difference between digitalization and digitalization. After sorting out my brain, the proposition of digital world is listed as the second step of big data thinking. Writing here, I can't help but reflect on whether I have understood the essence of the book (the essence I think). This is the first sentence. Because looking back at my whole thinking, I still think according to the old causal thinking mode. Another attraction of this book is that there are many viewpoints, which will be discussed from a philosophical point of view. Although I don't have much ink in my stomach, when I read these descriptions, I will find that I will better understand the proposition put forward by the author. For example, there is a passage in the book
When we say that human beings know the world through causality, we mean that we use two basic methods to understand and explain various phenomena in the world: one is through rapid and illusory causality, and the other is through slow and orderly causality. Big data will change the role of these two basic methods in our understanding of the world.
When attaching some examples, it is easy to understand with the "essence" provided by the author. That's true. Okay, so what has big data changed us? The author gives three points.
The essence of big data lies in three changes when we analyze information. These changes are about changing the way we understand and form society.
The first change is that in the era of big data, we can analyze more data, and sometimes even process all the data related to a specific phenomenon, instead of relying on random sampling (sample = population).
The second change is that there are too many research data, and we are no longer keen on pursuing accuracy.
The third change is caused by the first two changes, that is, we are no longer keen on finding causality, but should look for the correlation between things. Big data tells us "what", not "why". In the era of big data, we don't need to know the reasons behind the phenomenon, we just need to let the data speak for itself. Source: essay, otherwise we will be held accountable, thank you for your support, we will do better!
As we all know, the human brain has the function of comparing newly input stimuli or information with "past experience or accumulated knowledge" and then adjusting and accepting it. If the new reality in front of you can't coordinate with the inherent information stored in your brain, you will unconsciously refuse to accept the new reality (as if you didn't see it); Or through their own little knowledge of arbitrary speculation, so that their awareness of the situation deviated from reality (illusion). This is an instinct of human beings, aiming at keeping oneself calm.
So the author calls it a revolution.
Having said that, what does big data bring us? Here, I just want to talk about what I feel the most, and I can understand other interests by myself. Of course, there are many books, and the most is how much wealth XXX companies or individuals have created by using big data. Aside from these superficial things, what interests me or scares me most is prediction. This is the core thing brought by big data. There is no need to repeat the reasons for being tempted. The computer will tell you when to buy a two-color ball and win the first prize. Think about whether you are a little excited. Of course, it's just an exaggerated metaphor. There is a passage in the book about fear that I like very much.
The basis of fairness and justice is that people need to be responsible for something only after they have done it. After all, it is not a crime to want to do it but not to do it. The basic belief that society is related to personal responsibility is that people should be responsible for the actions they choose. If big data analysis is completely accurate, then our future will be accurately predicted. In the future, we will not only lose the right to choose, but also act according to the prediction. If accurate prediction comes true, we will lose our free will and the right to choose freely. Since we have no choice, we don't need to take responsibility. Isn't that ironic?
Here, by the way, another description of free will in the book.
In the field of philosophy, the debate about the existence of causality has been going on for centuries. After all, if everything has a cause and effect, then we have no freedom to decide anything. If every decision or idea we make is the result of something else. And this result is caused by other reasons. In this cycle, there is no human free will. -All life trajectories are only controlled by causality. Therefore, philosophers argue endlessly about the role of causality in the world, and sometimes they think it is the opposite of free will.
There is an example in the book, the film Minority Report. Seeing this, I said, "Oh, I've actually seen this movie, and now I'm still a little excited to think about it." You can have a look if you are interested. Probably the police arrested criminals in advance through prediction, but not through big data, but through superhuman means. When everything you do is predictable, it means you are completely exposed to the sun. If it were you, would you be afraid?
Finally, two postscript are attached, one is a passage in the book, and the other is made up by myself.
Big data is not a cold world full of algorithms and machines, and the role of human beings still cannot be completely replaced. What big data provides us is not the final answer, but the reference answer. Help is temporary, and better methods and answers are still in the near future.
Big data will eventually affect us, and it will be a double-edged sword like other technologies. Use it well, be tempted, abuse, and be afraid. Just like nuclear technology, if it is used, it will benefit the earth. If it is abused, it will still explode if it gives you a diamond earth. I believe that the future development of big data will be a revolution in life, work and thinking, as the author said.
After reading "The Age of Big Data", the word "Big Data" quietly appeared in our lives. In order to find out, I chose the book "Big Data Age".
The author first briefly describes the influence of big data on our life, work and thinking from the overall situation, and then writes with hundreds of academic and commercial examples from three aspects. The specific characteristics of the era of big data, such as sample = crowd, pursuit of accuracy and relevance, are presented one by one. At the same time, the author also analyzes the hidden worries in big data from the perspective of individuals and enterprises.
There are so many contents in the book that it is impossible to summarize them all here. Although there are many proper nouns in this book, the author used his popular language and many examples to let me smell a little freshness in the era of big data.
Why is it fresh? Because the contents of the book seem to open a world that I am familiar with and unfamiliar with. We are now in the network age, and a lot of data are generated in daily simple operations. However, at the beginning, we just used a lot of technology to solve the immediate problem. Those big data are like gold in the sand, and their value has not been discovered. Today, whenever we buy books online, we will always see "Guess what you like" column, Google search and flu prediction, Farecast and air ticket price prediction system. All this comes from big data that has been neglected, which proves that "prediction is the core of big data" has created an unprecedented quantifiable dimension for our lives. When I read this part, I can't help but feel that my life is already enjoying the benefits brought by big data. Just like "Guess What You Like", I came into contact with more books that suit my taste, and let me see details that I couldn't find before. Corporate giants with large amounts of data, such as Google and Amazon, vigorously develop new industries and research-related projects related to big data. With the convenience of the Internet age, big data has become the most commercially valuable thing today, and all quantifiable trends have begun to appear. "Essentially, the world is made up of information." Faced with this statement, the era of big data seems just around the corner.
While marveling at the unimaginable things that big data can do for us and its great value, I also agree that big data can greatly optimize our lives, but I can't help worrying about this era. Once the era of big data comes, not only our privacy may no longer be privacy, as the book says, "We are always exposed to the' third eye': Amazon monitors our shopping habits, Google monitors our shopping habits, and Weibo seems to know everything", but also we can use big data to predict many things, and the efficiency is very high. Once people rely on big data and rarely use human innovation and other abilities to be bound by data, the world will only become a very dynamic mechanical environment. And I think the biggest worry is the impact of the era of big data on the spiritual fields of human beings' own thinking, thoughts and beliefs. Now that we are all living in data, the era of big data may come gradually in a few years, which makes me ask: what have we always believed? I think it's hard for me to figure out this problem. When the world changes, it changes. Everything is good and bad. I don't know if I worry too much.
So I continued to explore the author's thinking on this issue. "The bigger data lies in people themselves", and the author also said that "we are creating a better future" and "in an era of prophecy, the free will of human beings is inviolable, which cannot be underestimated. When we use big data, we should remain humble and remember the foundation of human nature. " Clifford Gilder, an anthropologist, once said, "Try to apply it and expand it where it can be applied and expanded;" Stop where it cannot be applied or extended. "These words, like sunshine, dispelled my worries about the era of big data and my inner fear of it. I believe that only by adhering to our hearts and free will can big data benefit our human world and give full play to the warm light behind it.
In the face of changes in the times, I will strive to adhere to my free will and "embrace big data".
The essence of the world is data. When you master the data, you control the world-you can easily predict the development of things through the correlation in the data and nip all unfavorable factors in the bud-which is far better than "nip in the bud".
The book "Big Data Age" has made three major changes to our concept: don't sample all, don't be absolutely accurate in efficiency, and don't be causal. The book introduces three major changes in the era of "big data": thinking change, business change and management change. Under the "impact" of these great changes, the operation mode of modern society will inevitably undergo tremendous changes. If you don't conform to this changing trend, just like ancient China, you will stand still and finally open to the outside world with a long hook and halberd, which will inevitably be plundered and left behind in the world process, so you must change your thinking.
"We are no longer keen on finding causality, but should look for the correlation between things", which I think is the core idea of this book. In the era of big data, information and data have become the source of everything. We live in a sea of data. From another perspective, it seems that there are countless "invisible lines" that connect us with these data, which we have never had before and which we have never thought of. Big data has changed the way we used to know the world through causality, providing several new ways, because in the era of big data, we can analyze more data, and sometimes even process all the data related to a special phenomenon, namely: sample = population; Moreover, with so much research data, what we are keen on is not "accuracy" but "chaos". If we don't accept "chaos", 95% of unstructured data can't be used, which will not enable us to establish a complete data world. After analyzing more and more comprehensive data, we can explore their correlation from these data, that is, "what" rather than "why" only analyzes how it affects other things, that is, "let the data speak for itself", which completely subverts the previous methods of exploring data and shows a brand-new world.
This idea has brought great impact to the current knowledge situation with amazing power. Through the analysis of massive data, we can get valuable products and services or profound insights. For example, when h 1n 1 became popular in 2009, Google handled 34 search terms by detecting them. After predicting 500 million different data models and comparing them with the actual influenza cases recorded by CDC in 2007 and 2008, 45 search word combinations were determined. After using them in a specific mathematical model, the correlation coefficient between the predicted results and the official data is as high as 97%. This big data technology has obtained the spread range of influenza through massive data analysis in an unprecedented way, providing a faster and more efficient tool for forecasting influenza.
At the same time, although big data can benefit mankind and fight diseases, it is limited to mastering this technology. If we don't pay attention to this technology, it will be our disaster when our competitors build this data network before us. Think about it. Although the core of big data is prediction, when the enemy uses this method to predict our next move-such as where your missile will be launched, where it will fly, and where your army will move, it will be terrible. In short, all the "future" will be in the hands of the enemy, and the enemy can even find those who have "great achievements" in the future, thus infiltrating or strangling them, which is undoubtedly fatal to our development. Therefore, we must speed up the construction process of big data system as soon as possible.
For our national defense students, we should also conform to this development trend. The future era is bound to be an era in which data is easily available and data networks are enjoyed. Through these data, a data model can be established, which can accurately analyze and give a plan suitable for everyone, such as the amount of exercise, training intensity, etc., and can "see ahead" and guide a person's negative emotions in time to find them in time. These will surely become a reality. We must keep up with the times and do this.
Thinking in the era of big data 1000 word 5 "Everyone should speak with data except God." -This is an impressive sentence in Big Data, and it is also the message that this book tries to convey. In the digital information age, data is as ubiquitous as air. For some people, data is meaningless, while for others, data is truth.
The United States is the protagonist of "Big Data". The book tells the history of information opening and technological innovation in the United States for more than half a century, the twists and turns of public and financial transparency, the hidden secrets behind the data quality law, the waves of the national health care reform bill, the century-old entanglement of unified ID cards, the innovative legend of street police, the tragic history of American mine disasters, the past lives of business intelligence, the global rise of the data opening movement, Web3 0 and the next generation Internet.
Through this book, a three-dimensional American and American people's thoughts are presented to us-the American people are obsessed with the protection of personal privacy, but spare no effort to promote the transparency and openness of government information.
After reading this book, I suddenly became interested in data and data processing in my life. If one day, we speak with data everywhere, then politics, system and life will be clearer and accidents will drop to the lowest point.
As an information technology teacher, it is necessary to read this book! A wise teacher can certainly dig out unique information technology culture and vivid cases that can be used in teaching from the book.
I hardly have time to read books every day. I always wait until I'm tired at night to open my books. I always insist on reading when my eyes are extremely uncomfortable. So big data has integrated my thoughts in persistence. ...
After reading Big Data, I realized that this is not a boring book. The author tells the legislative story, citizen story, technology story and business story behind the opening, collection and use of data in the United States with cases and stories, which is fascinating and eye-opening.
I wonder, what practical value will the concept of big data have for education? For a long time, China Education has been studying the digitalization of education, such as digital campus. The idea is to digitize the content of our education, and the result is the research and development of electronic teaching materials or the digitization of teaching process. Euphemistically, this is an important connotation of educational technology. In the process of teaching, students' behavior can be digitized, and this research can not be deepened by any major. Too professional, so I think the so-called educational technology is not as real and meaningful as educational digitalization. For a long time, we don't know how the influence of education on a person will be manifested. All we have is an outline, and we are not sure what effect a teacher's behavior will have on students. Therefore, people have always had deep doubts about education. Science? The concept of big data at least puts forward that paying attention to "what" is much more practical than paying attention to "why". And our education just needs to shift our attention from "why" to "what". Only in this way can education develop from "why" to "what may become", which will be an ideological revolution. For the precarious educational technology, the way out is to shift the focus of research from digitalization to digitalization.
How to integrate data into teaching, educators first standardized the teaching template and teaching content by standardizing the teaching prescription of general medicine to ensure that each teaching process and content can be controlled. Then, combined with the daily teaching content, we should deal with the data we face and the classroom feedback naturally, and finally form a teaching system that pays attention to both teaching experience and teaching effect.
At the same time, we should not only pay attention to students' resources in class, but also follow up these resources after class. This is obviously different from the past education and teaching. In the face of the era of big data, it is inevitable that teaching will change. Therefore, no matter how the environment changes and how complex the data is, we must change our teaching to meet the future era of big data.
Schoenberg's "The Age of Big Data" made me re-examine the hot word "Big Data" that suddenly emerged in the information age. As a student majoring in information security, I am more enthusiastic about the word "big data".
The explanation searched on Baidu is: "Big data", or huge amount of data, refers to the information involved that cannot be captured, managed, processed and sorted by mainstream software tools at present, so as to help enterprises make more positive decisions within a reasonable time. Features: quantity, speed, variety and authenticity.
Schoenberg believes that big data cannot define an exact concept. He mentioned that "big data is the source for people to acquire new knowledge and create new value; Big data is also a way to change the relationship between markets, organizations and governments and citizens. " This is a more humane and socialized interpretation.
In this book, it is mainly discussed from three aspects: thinking change, business change and management change. Schoenberg focuses on three points:
First, more: not random samples, but all data.
Second, more miscellaneous: not accurate, but miscellaneous.
Third, better: not causality, but correlation.
I don't agree with the first view. After all, the realization of big data needs some technical support. Obviously, this technology is not mature enough now, and the application of big data in some simple things is more complicated. Therefore, this complex big data processing method is more suitable for some specific situations, such as business forecasting and human dna research.
As for the second point of view, I quite agree with Schoenberg that "the simple algorithm of big data is more effective than the simple algorithm of small data". In the rapid development of computer industry, a new simple and feasible algorithm has emerged, which is far less rapid than the development of computers in terms of operation speed and storage capacity, and big data algorithm seems to be more able to cater to this general trend.
The association mentioned in viewpoint 3 is a heavyweight in big data, which can quickly find the law of things and the corresponding solutions. Of course, causality cannot be completely ignored. After all, people are more likely to accept the results of causal analysis in their thinking, and the prediction of big data needs people to adapt slowly. When we have finished the correlation analysis and are not satisfied with knowing only "what", we can turn to the study of "why". After all, the root of the problem lies in causality. Schoenberg's entire data and related relationships are a shortcut in the era of big data.
However, in the information age, the problem of information security has become increasingly prominent, and the contradiction between data dictatorship and privacy protection has become the target of public criticism. In the last chapter of this book, Schoenberg tried to find a solution to get rid of this dilemma, but he finally failed, but he proposed that "big data is not a cold world full of algorithms and machines, and the role of human beings cannot be completely replaced." This shows that people are equally important in the data age. Data serves human beings and is also driven by human beings to accomplish corresponding purposes.
In such a big environment, it often causes me to think and worry more.
The era of big data is both an opportunity and a challenge for us. Some countries have begun to step into the ranks of the era of big data, and began to conduct research and use in various fields. As for China, which has a large population and a large land area, it can provide us with data protection in the era of big data. Whether we can face up to the challenge and stand out in the new round of great power role competition requires solving technical problems, gradually opening up data in various fields in policy, ensuring that data sources and permissions are solved, and constantly learning advanced computer technology to narrow the gap with other countries.
Industrialization and informatization, we have handed over an answer that the world cannot underestimate;
How will we be in an invincible position in the new wind storm in the era of big data? If the era of big data is an inevitable trend, then this is the responsibility of our generation and our new battlefield!
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