problem-solving ability
All positions, skills and knowledge are to solve problems. The professional essence of data analyst is to use data analysis skills to help business/boss achieve their goals. In the process of achieving our goals, we will encounter many problems. We may use data to find opportunities and predict risks, and we may also use data comparison to do feasibility analysis and use data to find problems in time. Each analysis topic may correspond to different methods and analysis models, but the core point is that we need to know what situations apply to what problems and respond flexibly. This ability to respond flexibly is the ability to solve problems.
Logical thinking ability
The boss gave you something. Can you quickly understand what the core is? When you first arrive in a department, can you quickly sort out the business logic inside without being at a loss? When writing the analysis conclusion, can it be clear and clear?
Logical thinking ability is trained, such as writing analytical reports. Only by optimizing and modifying again and again will you know that a sentence can be so refined and directed at people's hearts. Of course, it also needs the guidance of theoretical knowledge. It is suggested that we can learn the contents of logic training such as logic, mathematical analysis, golden pagoda principle and strategic analysis. I like writing since I was a child, and I studied mathematics in college. The first offer I got after graduation was market analysis. Somehow, I have a feeling that I am destined to be a data analyst.
learning ability
Learning ability here does not mean the ability to get high marks in exams. Of course, students who can get high marks have strong learning ability.
The professional characteristics of data analysts lead to the need to constantly learn new business knowledge. You need to know an industry in a short time and give your own professional advice, which requires you to have a strong learning ability. At the same time, the tools change rapidly in the era of big data, so you need to master more skills to help you improve your efficiency. An analyst who can quickly find the source data from the database and find the problems will definitely reach an analysis conclusion earlier than an analyst who will only wait anxiously for the long data development process. Of course, a reasonable division of labor and cooperation can improve the overall efficiency of the team. It is more efficient to plan and analyze the index system in advance and do a good job of split drilling in advance.
What is the core competitiveness of data analysts? Ivy Bian Xiao will share with you here. If you are interested in big data engineering, I hope this article can help you. If you want to know more about the skills and information of data analysts and big data engineers, you can click on other articles on this site to learn.