Basic Qualities of data analysts

Basic Qualities of data analysts

Mr. Lin is very happy to see the high morale of Xiao Bai: it is not easy to be a good data analyst. Although the major you have learned is irrelevant to data analysis, you can learn data analysis through practice at work. It takes a lot of time and energy to study data analysis. Without some cold bones, how can you get plum blossom?

Next, I will introduce you to the five essential instincts and qualities that a Qualified Data Analyst needs.

Rigorous and responsible attitude

Rigorous and responsible is one of the essential qualities of data analysts. Only with a rigorous and responsible attitude can we ensure that data is objective and accurate. In an enterprise, data analysts can be said to be doctors of an enterprise. They analyze the enterprise operation data to find the crux and problems for the enterprise. A qualified data analyst should have a rigorous and responsible attitude, maintain a neutral position, objectively evaluate the problems existing in the enterprise development process, and provide an effective reference for the decision-making layer; data should not be changed due to other factors, and the existing problems of the enterprise should be concealed. This is very unfavorable for the development of the enterprise, and may even cause serious consequences. In addition, for data analysts themselves, the future is also ruined, and the data analysis results will be questioned since you are no longer trustworthy, trust has been lost in front of colleagues, leaders, and customers. Therefore, a data analyst must have a rigorous and responsible attitude, which is also the most basic professional ethics.

 

Strong curiosity

Curiosity is everywhere, but as a data analyst, this curiosity should be more intense, and we should actively discover and explore the truth hidden in the data. In the minds of data analysts, there should be countless "why", why is such a result, why is it not such a result, and why is it, why is the result not as expected. This series of questions should be raised during data analysis, and a satisfactory answer should be provided through data analysis. The better the data analyst, the less satisfied the curiosity. After answering a question, a new question will be thrown out and the study will continue. Only by having such a deep understanding can we be sensitive to data and conclusions and find out the truth behind the data.

Clear Logic Thinking

In addition to a curiosity about the truth, data analysts also need to be able to think carefully and make logical reasoning clear. I remember a master said: the structure is king. What is structure? The structure is what we often say. Whether talking or writing articles, we must be organized and purposeful.

Generally, the business problems we face when engaging in data analysis are complicated. We need to consider the complicated factors and analyze various complex environmental factors, select an optimal direction among several development possibilities. This requires us to have a sufficient understanding of the facts. At the same time, we also need to be able to truly clarify the overall and local structure of the problem, and after in-depth consideration, clarify the logical relationships between the two structures, only in this way can we find it objectively and scientifically

 

Good at imitating

When doing data analysis, it is important to have your own ideas. However, it is also very necessary to learn how to learn. It can help data analysts grow rapidly. Therefore, imitation is an effective way to quickly improve learning outcomes. The Imitation mentioned here mainly refers to the excellent analysis ideas and methods of others, rather than directly copying them ". Successful imitation requires understanding the essence of others' methods, understanding their analysis principles, and achieving the essence through the surface. Be good at converting these essence into your own knowledge. Otherwise, you can only "always imitate, never surpass ".

Innovation

Through imitation, you can learn from others' successful experiences, but the imitation time should not be too long. In addition, we recommend that you make a summary after each imitation, put forward the improvements, and even make some innovations. Innovation is the spirit that an excellent data analyst should possess. Only continuous innovation can improve the level of analysis, so that they can analyze questions from a higher perspective.

 

When I heard this, Xiao Bai began to count himself as qualified as several excellent data analysts.

Mr. Lin continued: these qualities and abilities do not mean they are available. They need to be developed slowly and cannot be achieved overnight.

Tom :......

 

This article is excerpted from the book "Who says cainiao does not analyze data.

Book details: http://blog.csdn.net/broadview2006/article/details/6603131