The salary of data analysts is generally much higher than that of positions at the same level, most of which are between 20% and 30%. At the same time, data analysts are highly valued by enterprises. In many first- and second-tier cities, the annual salary of data analysts is very high, so friends who want to enter the data analysis industry do not have to worry about the salary of data analysis.

And now technology is developing faster and faster, making data analysis develop in more directions, and data analysis talents will become more scarce. Especially in China, which is developing rapidly, the data analysis industry will be vigorously developed. It can be seen that the prospects of data analysts are bright. At the same time, the status of data analysts is not low, no matter which industry they are in. Data analysts are a universal profession and can easily adapt to data analysis positions in various industries.

The work process of a data analyst is simply divided into two parts. The first part is to obtain data, and the second part is to process the data.

Obtaining relevant data is the prerequisite for data analysis. Every enterprise has its own set of storage mechanisms. Therefore, basic SQL language is a must. If you have a basic SQL foundation and then learn the detailed syntax, you can basically get a lot of data. After each requirement is clarified, relevant data must be obtained as needed to make basic data.

If you want to change careers, you can first evaluate your basic and professional background. Generally, those majoring in mathematics, statistics and computer science have the most advantages in changing careers, followed by marketing, e-commerce, economics, etc. Majors. These majors also have certain basic abilities in data analysis, and they can get started quickly when changing careers.

Extended information:

Data analyst requirements:

1. Understand business. The prerequisite for engaging in data analysis work is to understand the business, that is, be familiar with industry knowledge, company business and processes, and it is best to have your own unique insights. If you are divorced from industry knowledge and company business background, the results of the analysis will only be off-line. Kites don't have much use value.

2. Understand management. On the one hand, it is the requirement to build a data analysis framework. For example, to determine the analysis ideas, you need to use marketing, management and other theoretical knowledge to guide you. If you are not familiar with management theory, it will be difficult to build a data analysis framework, and subsequent data analysis will also be difficult to carry out. . On the other hand, the role is to provide instructive analysis suggestions based on data analysis conclusions.

3. Understand analysis. It refers to mastering the basic principles of data analysis and some effective data analysis methods, and being able to flexibly apply them to practical work in order to effectively carry out data analysis.