The graduation season is coming soon, and the senior students are already thinking about how to get an offer of data analysis. There are also some students in the lower grades, freshmen and sophomores, thinking about whether they want to develop into category email list data analysis? For this part of the students, skills projects and so on. Learning is not particularly rushed. One of the first questions to think about is whether you are suitable for data analysis? 1. Several characteristics suitable for data analysis First, let’s talk about the characteristics category email list of people who are suitable for data analysis. 1. Good at learning The skills required for data analysis jobs are simply too many and too complex.
This is much more demanding than other positions. Business students need to understand business knowledge and some tool skills. Technical students should master technical principles and engineering implementation. Data analysis students must not only understand business, but also know technology, and even understand communication, business, and marketing. If you only have basic data processing skills. Of course, data analysis is category email list also possible. But the risk of this kind of data analysis being obsolete is very high. If you want to do data analysis well, category email list you must continue to learn. No strong learning ability. It is very difficult for you to do a good job in data analysis.
It can be said that your learning ability determines the ceiling of your data analysis. 2. Delayed gratification The learning path of category email list data analysis is very tortuous. For business students, put two different advertisements. Their conversion efficiency, reading volume, etc., these data are immediately available. Quickly compare different schemes, their category email list pros and cons. For technical students, their learning can still be timely feedback. When you learn a new algorithm, you can try it out in code right away. But for data analysis, it is difficult for them to get timely feedback on their learning. Because data analysis is more about combining the operating conditions of the entire enterprise. Provide strategic decision-making support to senior management.