What is the content of big data major? How about getting a job in Guizhou?

1, subject knowledge: from the professional knowledge points involved in data analysis, mainly these:

(1) Statistics: parametric test, nonparametric test, regression analysis, etc.

(2) Mathematics: linear algebra, calculus, etc.

(3) Sociology: mainly some quantitative statistical knowledge of sociology, such as questionnaire survey and statistical analysis; There is also some sociological knowledge, which is helpful to data analysts engaged in marketing.

(4) Economic Finance: If you are a data analyst in this industry, economic and financial knowledge is necessary, so I won't say much here.

(5) Computer: People engaged in data analysis must know how the data you use is processed and understand the structure and basic principles of the database. At the same time, if the conditions are enough, you can still have enough ability to extract the data you need from the database (such as using SQL to query). This ability to extract data and analyze raw materials is necessary for every data practitioner. In addition, if you want to go further, you must master some programming skills, so that you can borrow some professional data analysis tools to help you finish your work.

..... study hard, although tired, but insist!

2. Software-related: What are the necessary tools for data analysis?

(1) Data analysis report category: Microsoft office software, etc. If you can't even handle the basic operations of excel forms and even PPT reports, then I have to say that you are still far from the post of data analysis. Nowadays, data presentation is no longer just in the form of tables, but more needs to show your data results with visual charts, so data visualization software is essential. It depends on how you choose BDP Personal Edition and ECharts.

(2) Professional data analysis software: Office is not all. To do a good job in data analysis, you must use (at least understand) some commonly used professional data analysis software tools, such as SPSS, SAS, Matlab and so on. These softwares can help us to complete professional algorithm or model analysis, as well as advanced python and R.

(3) Database: You can learn about hive, hadoop, impala and other databases;

(3) Auxiliary tools: such as MindManager (such as MindManager and MindNode Pro). ) can also help us to clarify our analytical thinking.

The most important thing is: theoretical knowledge+software tools+data thinking = data analysis foundation. Finally, we should apply these data analysis foundations to practical work and business, understand business logic well, really use data analysis to drive website operation and business management, and really play the value of data.

Guizhou is a big data industry base, and the demand for talents in big data is relatively large, and the employment prospects will definitely be good.