5 thoughts on “How difficult is a little white learning data analyst?”

  1. The following is a life course of a liberal arts student Xiaobai’s data analysis. Share it with you. I believe that you can help friends who are at the intersection of life or people who are in a period of confusion.
    1. Before choosing a data analyst, you must think about it again and again. Although this road looks bright and beautiful (at least the salary income category of the occupation is not much better than other industries), it is also a difficult trip. The road is full of unknown, thorns, and confusion, especially for me from the liberal arts background, the efforts to pay are several times the general science and engineering men. The logical thinking skills of liberal arts and sciences, the degree of acceptance of programming language, and the foundation of mathematical statistical foundation are true. This is also an important reason for Party A to trust the origin of science and engineering. Land to formulate students’ curriculum training programs in accordance with mathematical logic), but it does not mean that liberal arts students have no chance, because before the university, we did not formally come into programming or statistics. , Rather than excellent specialized research ability. Therefore, friends in liberal arts majors are also important factor in interest and decision. You cannot reject yourself with an objective professional background alone.
    3. If you want to choose this road firmly, you must overcome all kinds of dependencies, such as installing an R language or Python software to get the objective conclusion process from a huge data, use the knowledge you learned Analyzing the value of data, etc., be sure to use the brain to combat it. Do not rely on the previous liberal arts thinking (pay more attention to the creation of thinking and the development of personality), rational thinking and objective science are more important. Because this kind of learning habits determine that you will inevitably be fell behind by the interested person of your peers, Baidu, Google, Stack Overflow will always open the door for free;
    4, hands -on practice and internship participation projects are good The beginning of data science or data analysis, only learning or not practicing fakes. Only by directly using actual combat can we see how much you learn what can be implemented and can be used to enhance the value of the business; In the past, if time permitted, the three levels of R language, Python (data science), and SQL (you can choose a platform, such as MySQL) have passed earlier. (If you don’t want to work overtime every day);
    6, if you are still a student, learn to distinguish the priority of various things, such as a variety of boring people to lectures, listening to the marketing brainwashing class, each If you are ineffective entertainment, if you are all used in the learning of data analysis, you will find that you have a lot of time, and naturally you can catch up with the pace of peers earlier;
    7. Go and down to the ground Take your own way, you won’t write more, look at, ask more (ask real valuable questions), summarize, and communicate more, give yourself a sufficient transfer cycle (if you are a science class [statistics, mathematics, computer ], Maybe you will go smoothly, but you must not take it lightly. If not, please choose carefully. At least you must give yourself one to two years of switching buffer. What 7 days are proficient in machine learning and artificial intelligence for three months, do you dare to believe it yourself?)
    8, learn to integrate knowledge in different fields, and move on -the -class, move horizontally. It feels, otherwise you can only increase the thickness of the notebook and increase your troubles.
    The people have the joy and tangles of liberal arts students’ learning data analysis or zero -based switching, but at any time node, if they have been stagnating and hesitant Essence Fortunately, although I am muddy, I was also overwhelmed along the way, but time lived up to me, and after all, I finally got the results! May all liberal arts students want to enter the data analysis industry or the friends who transfer to career will go smoothly.

  2. First of all, we must understand the conceptual difference between big data analysis and traditional data analysis. Compared with traditional data analysis, big data analysis needs to master more skills, and the requirements for practitioners have improved. However, the learning threshold for big data analysis is not too high, and the learning is moderate. Many people can learn big data analysis.

  3. Overall, learn the foundation first, then learn theory, and finally the tool
    1. Learning data analysis basic knowledge, including probability theory, mathematical statistics
    2, and your target industry related theoretical knowledge. For example, financial categories should learn various knowledge such as securities, banking, and finance.
    3. Learning data analysis tools, such as SAS, SPSS, and even Excel (the function of the data analysis module is very powerful)
    Remember, the first step is essential, the basis of data analysis.

  4. With the rise of big data boom, more and more people want to enter the big data industry, especially for people without technical skills. Generally, some big data training courses will be considered to study systematically. I couldn’t help voicing, I had to learn big data and wanted to cry. In fact, the acquisition of any new skills must be worked hard, especially if the foundation is weak, learning difficulties can be imagined.
    . However, there will be such a voice on the Internet recently: big data is too difficult to learn, learning big data to learn to cry. In fact, learning is not so simple. Big data analysis is too difficult to learn to cry. If you do n’t learn big data if you work hard, you should reflect on whether your learning method is wrong. Let ’s take a look at the following editors, is there really so difficult to learn big data?

    Why do you think big data is difficult to learn?

    It is because of interest, but most people go to the big data industry with high salaries and good prospects. Therefore, the starting point of learning may be too utilitarian and eager to achieve success. Of course, it is not because they cannot learn because of this, but that most people just have a moment of head fever, do not consider how to learn, and do not pay much effort. Finally, I wasted a lot of time, and even some people reported a lot of money to waste a lot of money, and regretted it: Learning big data to learn to cry! Big data is really difficult to learn! Is it really difficult to learn big data? Or do you have no determination to study hard at all? I hope that when you feel that learning is difficult, ask yourself how much effort did you pay for it. If you do n’t learn it because you do n’t spend much effort, then you do n’t learn well, then There is nothing to complain about.

  5. I am a very ordinary girl from the countryside. I graduated from college in 17 years and is now an analyst at a big data company in Hangzhou. I want to share with you how I grew up from a piece of white paper I just graduated to a big data analyst. I hope my study and growth journey can be given to my friends who want to go to the big data analysis industry. Some references.
    . When I just graduated, I was very confused like many schoolmates and sisters now, because I did not have a very clear career plan for my future. I don’t know what I can do? There are some inferiority in my heart, because even if I love my university, I have to admit that it is just a very ordinary university, not 985 and 211. In today’s college students, there are so many bulls and fierce employment environments, my education and majors are not much competitive, and I regret why I have not worked hard during college, but it is too late. Graduation means that the starting point of a new life must be brave, and in the future, you can only survive and develop in society by your own ability.
    So, in this way, with the reluctance of his alma mater and classmates, the sorrow of the society, the fear of your inner heart, and the expectations given to me by my family, I started my job search. After half a month’s job, I interviewed 20 and 3 successfuls, but the salary of up to 3500 a month, and the two were sales positions. With computing science), I calculated it, even if I accept these strange and unwilling positions, in cities like Hangzhou, the cost of rental houses and electricity and goods will be about 1500, the bus is at least 200 a month, the living expenses are at least 900, and the telephone fee is the phone fee. The salary of 100,3500 a month will be deducted from five insurances and one fund, and it will be posted every month. I was almost out of collapse, and I felt very useless. I didn’t even have the ability to survive independently in the city. I was very frustrated.
    Perhaps fate is like this. When you face almost despair, you can often look at yourself and understand what you really want. When you calm down, I ask yourself, why do you want a student like me? In fact, everyone knows that one is that there is no work experience, and the other is that nothing can create value for the enterprise; the third is that they are nervous, unconfident, and do not show themselves well. After analyzing this logic, I don’t expect miracles for half a month. Maybe even my last self -confidence will be hit. I vaguely feel that I need to regain myself, and I need to open the distinction with other students. At present, the major I have learned seems to be too different from the ability required by the company. After this analysis, there are three roads in front of me. The first is to accept the work of 3500. I hope to add a little salary for a year and a half to allow myself to live in Hangzhou, and then seek development in the future; the second is to find a job after a small city who returns to my hometown; the third is to choose a talent now In the industry with a large gap, and in the future, there are prospective occupations to learn from scratch, so at least I am one step faster than others.
    The hottest words in the society last year are artificial intelligence and big data. At that time, I checked a lot of information on the Internet, read a lot of news, and also checked the salary of big data positions on the recruitment website, the number of recruiters and technical requirements on the recruitment website In the case, I found that the big data industry is divided into two directions. One is the development of big data engineering, and the other is the big data analysis class. The programming requirements of the development class are relatively high. After listening to some analysis courses, I feel quite interesting and understand. Compared with the development category, I prefer and more suitable analytical categories, so I determined to learn in this direction in data analysis. I spent 10 days to understand the prospects and learning paths of data analysis, but the information on the Internet is too messy. I can only understand one about one. I bought some lessons on the Internet and bought several books. There was no clue, I thought I could get started to learn Hadoop, but I found that the construction of Hadoop was too difficult to set up the later; at this time, I still felt that I still needed to form a formal training. What cares about me more, I remember in early July last year. When I checked the big data analysis training online, I found that Alibaba Cloud and his content provider Hangzhou Cubi Data Technology jointly launched a “Alibaba Cloud Big Data Analyst Enterprise Combat” “Training Camp” needs to be selected to enter. With the trust of the Alibaba Cloud brand, I took the test screening. At that time, the content of the test was two parts, one was the database, the other was C language and Java; I did not expect to receive the notice the next day. I needed to interview on the next day. I doubted whether it was deceiving at the time. When I was interviewed by the phone, I asked the teacher who was in charge. Ten people in the students participated in the selection of 10 people, mainly experimented with the newly developed curriculum system. As a computer -related major, I do n’t understand that Java who only understands the database, the samples are selected. Suddenly there is an experimental feeling. Isn’t this a mouse with me? I asked what other samples were like. The teacher said that one was a junior in the mathematics statistics of the junior. Students, a student with a software development majors, a student who has three years of software development, a student of business management … My God, I was in a circle at that time. The money is not spent in vain, and it is a waste of more than a month. I told my parents that no one supported me. The day before the official opening on July 9, I wanted to understand one thing. In China, even Alibaba Cloud in China Such companies do not have a complete scientific curriculum system at present, and there must be no other families. If it is a deceptive responsible teacher, there is no need to tell me the experiment. On the last day, I chose this training on the last day. Camp, in fact, I was very uneasy.
    The training camp 10 students studied together for 35 days, for nearly 2 months, after systematic training, 10 our classmates were hired by 7 companies in Hangzhou, all of which are data analysis positions. Those who go to financial enterprises, and there are related companies to Ali. I went to the Ali company with the younger brother of the junior. n is very happy. I really thank the teachers of Alibaba Cloud and Alibaba Cloud’s partners, Cassia Data Technology. At that time, all the teachers who gave us classes were very professional. The company was originally a business data consultation, so there are many business cases to share with us. The experimental platform used is Jiudamen’s business data analysis experiment platform.
    It from mice to admission, I have three years of work experience, give you a learning path of learning data analysts, for your reference only;
    1. I suggest you learn the MySQL relationship database first, analyze the analysis, and analyze it. The database in the teacher’s position is often used, and it must be known;
    2. It is recommended that you learn the data modeling, data warehouse, ETL data cleaning, especially in the work. The data quality management is relatively heavy. ETL is often used (of course, the data cleaning tools also have others, ETL is common);
    3, Hadoop distributed in fact, in fact, less use in analysts This large company has ready -made tools. It is not necessary to build it. It can be used directly, which is very convenient.
    4. Analysis tools still need to learn it well. It is recommended that you learn Python. Now most of the company uses this. Excel also needs to learn. Some small data sets and simple BI reports are more convenient. Of course, there are more analysis tools, such as R, SPSS, SAS, etc. are all tools, depending on what you use, you will use a skilled tool. In addition, the Python function is very powerful, and you don’t need to study too deep. In fact, you can often learn it quickly when doing projects. What we often use everyday is that thing.
    5. Next, you need to learn machine learning. It was originally called data mining. Now it is called machine learning, and some are called artificial intelligence. This requires everyone to spend some time to learn. Classification problems, clustering problems, dimension reduction problems, etc., as well as predictions, unsupervised, and optimized are often used. This discipline may require us to study and study for a long time.
    6. In fact, I have never learned the algorithm. There are special algorithm engineers in the project team. In addition, some universal algorithms can be applied, so I think the project team can cooperate to do it. I have no experience in this regard. No suggestions.
    7. I now think that the most important thing for analysts is the idea of ​​looking at the problem and dealing with the problem. In this year’s work, I discovered that the big cows’ ideas to solve the problem are really different from us. In each project team When the meeting, I feel that the most learned thing is the idea and ability to solve the problem; and analysts also need to understand the business in depth, because different industry data structure and business logic are different. It takes time to understand At the same time, I also feel that as a data analyst, I also need to learn business thinking and marketing knowledge.
    8. The other is data visualization. This is mainly to present the data structures we analyzed with images and animations on time. What I am doing now is a large data screen, there are many tools, BAT companies have their own tools. At that time The artistic skills, of course, now there are more templates and can be applied.
    9. In fact, in the process of learning, if you want to learn quickly, it is best to start with project cases. At that time, the data of Alibaba Cloud and his content provider made the data. Scene cases, all the data sets are placed in the server, which is very similar to the scenes we work now. The teacher talked about the knowledge points in the morning. In the afternoon and evening, we did practical experiments. The tool teacher basically did not talk about it. When doing the case project, what was used for a temporary check, and the tools were started in the second time. In the last week, Teacher Zhao Qiang of Canada trained us a large project to simulate the data analysis project of an enterprise. That 5 days were my most hard -hearted unaware. Although the pressure was very strong and the group was carried out, it took 5 days to take us what we learned. All the things were stringed, and the thoughts were all available at once. In the end, everyone had to come to the stage to talk, and also cultivated their own communication skills and speech ability. After the entire project process, it benefited a lot. Teacher Zhao originally did a data consulting project for the world’s top 500 companies. It was also MBA professor of the Shulik Business College in Canada. The project was rich in experience. It is indeed a rare expert in China. The project consultant of this company, thanks to Mr. Zhao’s careful guidance, let me take a lot of detours on the way to become big data analysts. Thank you Teacher Zhao. I also hope that everyone will be on the way to study. Can meet such good teachers and friends.
    10, the last suggestion is that everyone also needs to learn PPT production and lectures. Recently, our project needs to be delivered one after another. Each delivery needs to be explained to the customer. All need training, Alexander.
    has said so much, it can only represent my experience and feelings over the past year, and I don’t know if it will help the younger brothers and sisters. Anyway, if you want to develop the profession of big data analysts, it is recommended that everyone must be sure everyone must be To learn from the project, the tools must be learned but do not study too deep. It will waste time. After work, use it very fast. If you have no clue to study, training is still necessary, but you must find professional people for training. , I think I am very lucky. I met teachers of Alibaba Cloud and Hangzhou Cubi Technology. If the younger brothers and sisters have such ideas, we can learn about it. At that time, we were the first batch of training. They are still doing it. They are starting from the project and are very similar to my current work content. Although the training process is very hard to learn and tired, the gains and influence are huge.
    Mi I got the offer of two companies when the training was over. Both companies were very good because I came out in the Alibaba Cloud Experimental Class, and I chose the Ali company. I am very happy to enter the big data analysis occupation and do the project every day. I am very happy. I believe I can work well in Hangzhou, live a good life, and the graduation season. Essence

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