There are many books on data analysis in the market. Here I simply recommend data analysis to you. For people with basic knowledge, it can be called recreational reading.
But it still has a certain effect on newcomers. When reading, you don't need to know much, just pay attention to the process of data analysis, application scenarios, and some data analysis tools mentioned in the book, without worrying about the realization of the analysis model. Five hours is enough for you to establish a preliminary impression of data analysis and eliminate strangeness.
Second, understand statistical knowledge-10 class hours 15 class hours is only enough for you to understand statistical knowledge, which is enough as an introduction, but you should know that you need to learn more statistical knowledge with the deepening of your work in the future.
At this stage, I recommend two books: statistics is easy to understand and statistics: from data to conclusion. To understand the commonly used mathematical statistical models (describing statistical indicators, clustering, decision trees, Bayesian classification, regression, etc.). ), and focuses on the working principle, input content and output content of the learning model. As for the specific mathematical derivation, we can put it aside for the time being and come back to see it when necessary.
Third, learn the primary tool-20 hours for non-technical data analysts, only one primary tool is recommended: EXCEL. The recommended book is Who says novices can't analyze data? You must learn the basic articles, but you don't have to learn the improved articles (you can use other advanced EXCEL books), and you can also learn various open classes on the Internet.
At this stage, we should focus on the use of EXCEL intermediate functions (pivot table, function, various chart usage scenarios and how to make them). If you have free time, you can learn VBA.
Fourth, improve PPT ability-10 hour As a data analyst, PPT production ability is an extremely important ability, so it takes some time to understand how to make a focused and clear PPT, and how to insert various charts in PPT to easily update data. 10 hours is not much, but it is enough (if you haven't done PPT, you need to add some time). Specific books and courses are not recommended. If you catch a lot online, please search for it yourself.
5. Understand the database and programming language-10 hour This stage has two goals: learn basic database and programming knowledge to improve your future work efficiency, and test which advanced data analysis tools are suitable for you to learn. For the former, the database suggests learning MySQL (although Hadoop is very useful, but you are not a technical post, so you won't use it at first), and the programming language suggests learning Python (I really confiscate their money to continue Amway Python ...). It is good for the database to learn joint queries, but there is no need to optimize performance and back up those contents; Python is about learning as much as possible.
Sixth, learn advanced tools-10 hour Although EXCEL can solve more than 70% of the problems, the remaining 30% still need advanced tools to do it (don't trust EXCEL to be a cluster). There are two options for advanced analysis tools: SPSS and R. Although R has various benefits, my suggestion is to decide which tool to learn according to your learning experience in the last step. If learning programming linguistics is painful, learn SPSS. If you are happy to learn R, no matter which tool you use, you should run through the key models you learned when you studied statistics, learn to model and optimize them slightly.
7. Know the industry and position you want to go to-10+ hours Here, I put a "+"in time, because this step doesn't have to take the whole time to study, it runs through your whole learning process. The ability that data analysts need to constantly improve is industry and business knowledge, and there is no one. In which industry and post you want to invest in in the future, you must learn relevant knowledge (for example, if you want to operate a website, you must understand the background knowledge of the Internet, the index system of website operation, and the user's operation knowledge, etc.).
Eight, report-you have learned so much in 25 hours, and now you still can't find a good job when you go out. All recruiters will ask you one question: What practical projects have you done? (Even if you are a freshman)
If you have relevant project experience or internship experience, of course, you can take it out, but if not, what should I do? The answer is simple. Give them a report and tell the recruiter: I have the ability to analyze entry-level (or even class) positions with data. At the same time, making a report will also be the main content of your future work, so there may be another situation: you work hard to make a report, and then find that this is not the life you want, and decide to do other jobs ... This is also a good thing, and people with data analysis ability have an advantage in doing other jobs.
Friends who are interested in big data analysis may wish to start by reading big data analysis books! There are many big data teaching videos on the website, from basic to advanced, which are quite good. The knowledge points are very detailed, and there is a complete version of the learning roadmap. You can also go and see for yourself and download and study.