How to quickly become a data analyst? hello

With the advent of the era of big data, more and more companies begin to pay attention to data, hoping to find valuable information from the data, help companies make correct decisions and make the company's development smoother. Data analyst has also become a career that more and more people yearn for. So, how to become a data analyst quickly? Master the following four points.

Professional competence

The most important thing in data analysis is business ability. As long as you have really worked in the practical field, you will really understand that business knowledge is the basis of your analysis. Learning business knowledge takes time to accumulate. The cultivation of business knowledge will far exceed the study of technical tools. Data analysis is actually a deeper thinking and summary based on business. For business learning, you can learn according to previous reports and cases. This is a process that takes time to precipitate, and it is also the ability that needs to be continuously improved. There is no one.

elaborative faculty

When we get the data report, the whole data is in front of us, and it won't tell you on its own initiative. This requires us to deduce and analyze, find the law from it, quickly evaluate the key attributes and decisive factors of the problem, form our own unique opinions and summarize the report. The so-called thoughtful, watertight, without thinking logic, there is no analytical thinking. We cultivate our own thinking ability, which can bring us different ways of thinking and perspectives through interdisciplinary knowledge; In addition, we should also develop the habit of thinking. "Learning without thinking is useless, thinking without learning is dangerous", thinking itself is a kind of practice, which makes what you have learned more systematic and in-depth.

Communication ability

Data analysis runs through the whole workflow chain of an enterprise. You need to face different positions and roles. At this time, you need good communication skills and use different languages and expressions to get what you want. Communication ability is the bridge between data and business. In re-communication, don't stick to your own point of view, but adopt the opinions of others, especially those with wisdom, which can help us reduce the error rate and improve the accuracy of analysis, so that our analysis will be more convincing.

technical competence

We have studied Excel, MySql, Python, SPSS and other related technologies. If you just step into data analysis, Excel is actually enough. If you want to have a deeper grasp, you can learn Python, R, SPSS and so on. They provide powerful mining function and graphic function. In particular, it is very convenient for R and Python to refer to their own libraries, but the technology is also very mature.

The above is what Bian Xiao shared with you today about "How to become a data analyst quickly?

Look at the relevant content here, I hope it will help everyone. Bian Xiao believes that if you want to make achievements in the big data industry, you need to obtain some data analyst certificates with high gold content, which will have more core competitiveness and competitive capital.