First, mathematics major
As the saying goes, "If you learn math and physics well, you are not afraid to travel all over the world". Data analysis is nothing more than looking for hidden rules from a large number of messy data. Mathematics often makes people think more logically and more sensitive to data.
Second, statistics major
Statistics is the basic skill of data analysis, which runs through the whole process of data analysis. At the same time, after systematically studying statistics, the ability to understand and analyze data will be more professional and profound.
Three, computer science and technology major
Data analysis will be exposed to many tools and programming languages. If you are a computer major, you will have an advantage in programming and get started faster when using tools.
Fourth, sociology major.
From the perspective of economics, people are economical and will pursue the maximization of interests. But from a sociological point of view, people with sociality will also be influenced by social group psychology. A data analyst with a sociological background can explain the market phenomenon more reasonably.
V. Marketing Major
Data analysts need to support the marketing decision of enterprises, and data analysts who know marketing will have clearer and broader ideas.
Financial management major of intransitive verbs
Financial management is the basis for enterprises to choose investment projects, the index for evaluating financial situation and the scale for evaluating decision-making effect. Data analysts who understand financial management can grasp the law more accurately.
Seven, psychology major
Talents are the cornerstone of the stable development of enterprises, and users are the parents of enterprises. If an enterprise wants to increase its market share, it must first increase its people's share. Therefore, data analysts who understand psychology can more accurately perceive the real thoughts of employees or users.
Therefore, not only people with science and engineering backgrounds such as mathematics, statistics and computer can engage in data analysis, but also people with other backgrounds, especially liberal arts students, have the same opportunity.
After all, choice is greater than ability, ability is greater than specialty, and interest and hard work determine how far we can go in the future.
Data analysis is not an IT industry, so there is no need to master too many programming languages. Data analysis pays more attention to practical operation and business ability, and current data analysis tools, such as Python and PowerBI, are relatively easy to use.
Engaged in data analysis, what really needs to be improved is logical thinking ability, keen insight and good communication and expression ability ... these can be achieved through hard work without relying on the background.