Current location - Education and Training Encyclopedia - Educational institution - What does it take to be a big data analyst?
What does it take to be a big data analyst?
We told you a lot about big data thinking in the last article. It can be seen that big data thinking is objective. Thinking and solving problems with big data thinking is the practice of every big data engineer, but what does it take to be a big data analyst? The following is to introduce these contents for everyone.

At present, the domestic big data work is still in a stage to be developed, and how much value can be extracted from it depends entirely on the personal ability of engineers. Experts who have been in this industry have given a general framework of talent demand, including computer coding ability, mathematics and statistical background. Of course, if you can have a deeper understanding of some specific fields or industries, it will be more helpful for them to quickly judge and grasp key factors. In a big company, a master's degree is better, but the current education is not the most important factor. Experience in large-scale data processing and curiosity about data ocean treasure hunting will be more suitable for this job.

In addition, an excellent big data engineer should have certain logical analysis ability and be able to quickly locate the key attributes and determinants of a business problem. We need to know what is relevant and important, what kind of data is the most valuable, and how to quickly find the core requirements of each business. Learning ability can help big data engineers adapt to different projects quickly and become data experts in this field in a short time, while communication ability can make their work go smoothly, because the work of big data engineers is mainly divided into two ways. The first one is promoted by the marketing department and the data analysis department. The former needs to know the development requirements from the product manager frequently, and the second is to find the operation department to understand the actual transformation of the data model.

Of course, we can take the above requirements as the direction of becoming a big data engineer, which is a big talent gap. At present, domestic big data applications are mostly concentrated in the Internet field, and more than one enterprise is preparing to carry out big data research. Therefore, it is also suggested that some companies originally engaged in data work can consider transformation.

The above content is what big data engineers introduced by Bian Xiao need to pay attention to and have. If you want to be a big data engineer, please absorb these contents. I hope this article can help you. If you like our content, please pay close attention to our article. Finally, thank you for reading.