Shulou(Shulou.com)06/03 Report--

In the prevalence of the Internet today, to be able to predict the future need to rely on more data support, from the data trends and analysis, we can grasp the future development trend incisively and vividly. Under the background of big data, professionals who are proficient in big data will become the most important business role of the enterprise. Big data employees' salary continues to grow, and the talent gap is huge.

Recently, in answering fan questions, I found a question: many people do not understand big data's position system, and some people who want to get started with big data have been confused. They do not know whether they should change careers to study big data. I don't know whether I want to change my major or not. I'll give you an analysis here (personal point of view).

Data analysts refer to professionals in different industries who specialize in industry data collection, collation, analysis, and make industry research, evaluation and prediction based on the data.

The Internet itself has the characteristics of digitalization and interaction, which brings revolutionary breakthroughs to data collection, collation and research. In the past, data analysts in the "atomic world" spent a high cost (capital, resources and time) to obtain the data to support research and analysis, and the richness, comprehensiveness, continuity and timeliness of the data were much worse than those in the Internet era.

Compared with traditional data analysts, data analysts in the Internet era face not a lack of data, but a glut of data. Therefore, data analysts in the Internet era must learn to use technical means for efficient data processing. More importantly, data analysts in the Internet era should constantly make innovations and breakthroughs in the methodology of data research.

As far as the industry is concerned, the value of data analysts is similar. As far as the press and publishing industry is concerned, whether the media operators can accurately, detailedly and timely understand the audience situation and changing trends in any era is the key to the success or failure of the media.

In addition, for the content industry such as press and publication, what is more critical is that data analysts can play the function of content consumer data analysis, which is a key function to support news and publishing organizations to improve customer service.

Skill requirement

1. Understand business. The premise of engaging in data analysis work will need to understand the business, that is, familiar with the industry knowledge, the company's business and processes, it is best to have their own unique views, if separated from the industry cognition and the company's business background, the result of the analysis will only be kites that are off-line. it doesn't have much use value.

2. Understand management. On the one hand, the requirements of building a data analysis framework, for example, to determine the analysis ideas need to use marketing, management and other theoretical knowledge to guide, if you are not familiar with management theory, it is difficult to build a data analysis framework, follow-up data analysis is also very difficult. On the other hand, the function is to put forward instructive suggestions for the conclusions of data analysis.

3. Know how to analyze. Means to master the basic principles of data analysis and some effective data analysis methods, and can be flexibly applied to practical work, in order to effectively carry out data analysis. The basic analysis methods are: comparative analysis, grouping analysis, cross analysis, structure analysis, funnel chart analysis, comprehensive evaluation analysis, factor analysis, matrix correlation analysis and so on. The advanced analysis methods are: correlation analysis, regression analysis, cluster analysis, discriminant analysis, principal component analysis, factor analysis, correspondence analysis, time series and so on.

4. Know the tools. It refers to mastering common tools related to data analysis. The data analysis method is the theory, and the data analysis tool is the tool to realize the data analysis method theory. in the face of more and more huge data, we can not rely on the calculator to carry on the analysis. we must rely on powerful data analysis tools to help us complete the data analysis work.

5. know how to design. Understanding design refers to the use of charts to effectively express the analytical views of data analysts, so that the analysis results are clear at a glance. Chart design is a great knowledge, such as the choice of graphics, layout design, color matching and so on, all need to master certain design principles.

Once again, engineer big data

First, how to become an excellent big data engineer

1. In terms of ability, first of all, engineer big data needs to have computer coding ability, because in the face of massive unstructured data, you need to design algorithms and write programs to realize it if you want to dig out something valuable from it. The most powerful ability of programmers is to write concise and efficient code to realize people's wild dreams for the future. The stronger the coding ability, the more likely the programmer is to become a good big data engineer.

two。 Secondly, big data engineers need the ability background related to statistics and applied mathematics, and data mining and analysis need to design data models and algorithms. It should be said that programmers have this foundation. Generally speaking, excellent big data engineers do not have a professional background, but usually majored in mathematics, so improving algorithm design ability is a key factor for programmers to transform into big data engineers.

3. Big data engineers need to have professional knowledge of the industry. The ultimate goal of big data's technology is to serve the society and enterprises, and to play a major role in promoting the development of the market and enterprises, which is the value of big data. Therefore, engineer big data can not be separated from the market.

There is a saying that three people must have my teacher, in fact, as a developer, there is a learning atmosphere

It is very important to have a communication circle. This is my big data communication study group 531629188.

Whether you are rookie or Daniel, welcome to join us, and those who are looking for a job can also join us.

Let's communicate and study together, learn from each other, make progress together, and cheer up together.

2. Salary and treatment of big data engineer

A really good big data engineer needs to constantly learn new knowledge and accumulate self-experience. Of course, the more experience, the higher the salary. The future of big data engineer is very bright. In the United States, big data engineer earns an average annual salary of 175000 US dollars, and in China's top Internet companies. Big data engineer's salary is more than 30% higher than that of other positions at the same level. Big data's technological development is so fast that the momentum of development in China is so fierce that big data talents have failed to keep up with big data's development and will be in short supply in the next few years. It is predicted that the data talent gap will be as high as 1.5 million in the next 3-5 years.

Therefore, enterprises often hire big data technical talents with high salary. Under the circumstances that demand exceeds supply, the value of data talents goes up. Data talents can work as data analysts, hadoop development engineers, data mining engineers, algorithm engineers and big data development engineers. Is the salary of big data engineer in Beijing high? The average salary of big data engineers in Beijing ranges from 10630 yuan / month to 30230 yuan / month in June 2017. with the increase of the talent gap, big data's salary may become higher in the future.

As a result, big data's industry ranks first in the Internet industry with an average monthly salary of 212k, far higher than the Internet of things and smart hardware industry, which ranks second or third.

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