@Programmer, the same programming, why the monthly salary of big data is tens of thousands higher than me!

As programmers, we all have the same anxiety-that is, when the new wave of new technology hits again and again, we will always follow it desperately involuntarily, and always worry that if we do not keep up with the trend of new technology, we will be abandoned by the times.

Especially in recent years, there have been wave after wave of technology waves, from the Internet of Things, cloud computing, big data, VR/AR, artificial intelligence, autonomous driving, to today's blockchain, every technology wave comes, it is affected by capital. And the market is extremely popular. And a large number of programmers have also joined the entrepreneurial army of popular technologies, which undoubtedly aggravates the anxiety of friends around them.

In fact, anxiety like this is very normal. It is also human nature to have immediate worries without far-sightedness. There is a saying in the ancients: "Be prepared for danger in times of peace, and be prepared when you are prepared, and dare to follow this rule."

But people's energy is limited after all, and it is impossible to follow every wave of technology boom. How to choose in the end, everyone must be full of doubts.

From a long-term perspective, it must be the kind of technology that is slow to be eliminated, can be directly proportional to the accumulation of experience, is easy to form knowledge barriers, and is not easy to be replaced. But in fact, it is quite difficult to find this kind of technical field. This is also the reason why programmers generally lack a sense of security. Taking Java language development as an example, is there a big gap between working for 5 years and working for 3 years?

But in fact, there is one technical field that has such potential, which is big data technology. Gao Yang, senior big data architect and big data expert of Kingsoft Software, once said that for project management and higher-level professionals, big data can help them to think more logically and dialectically to view data, and it is more popular than ever. In the study and work, you can understand what technologies can do and what are the advantages. Such knowledge is of great benefit to a manager in making judgments on the current technological form, estimating the difficulty and cost, and broadening the imagination in innovation, and has important accumulative significance.

At the same time, according to relevant survey data, the employment salary of big data talents is generally higher. Taking Beijing as an example, the average monthly salary of big data developers is 30,230, the average monthly salary of data analysts is 11,130, the average monthly salary of Hadoop engineers is 20,130, the average monthly salary of data mining is 21,740, and the average monthly salary of algorithm engineers is 22,640. Is it very attractive?

In addition, the data also shows that among those who have worked for less than three years, the average annual salaries of big data engineers, AI engineers, and all engineers are 292,200 yuan, 299,800 yuan, and 237,300 yuan respectively; among those with 8-10 years of service. , the average annual salary of the three reached 442,300 yuan, 457,100 yuan, and 399,100 yuan respectively. It can be seen that in the field of big data, with the increase of working years, the salary increases greatly.

Big data has high expectations because data has gradually become the core competitiveness of enterprises. By analyzing and mining the value of data, enterprises can learn about customer needs in advance and predict their consumption habits and trends. All decisions of managers can be based on evidence, no longer blindly, and reduce enterprise risks.

In the past two years, the wave of digital transformation has swept all walks of life, and more and more traditional industries have begun to realize the value of data. Suhabi Abbas, former chairman and CEO of Informatica, once admitted that the single most valuable asset in the information age is data. To better understand customers, improve operational efficiency and business flexibility, data is inseparable. support.

According to a third-party agency forecast, by 2020, each Internet user will generate 1.5GB of traffic per day, a smart factory will generate 1PB of data per day, and cloud video service providers will generate up to 750PB of video per day data.

It can be seen that in the future, the scale of data will reach an unprecedented order of magnitude, and the management needs of enterprises for data will also be greatly improved, especially for big data talents.

Last year (2017), a developer survey was conducted. The survey results showed that the main problem faced by enterprises in building big data platforms is the lack of talents. Of course, big data application planning and technology selection are also practical problems that plague enterprises.

But friends who are exposed to big data in the early days are often confused. Big data contains a lot of technologies, and there are many common frameworks, such as Hadoop, Spark, Storm, Scikit-learn, Mahout, TensorFlow, etc. Where should we learn from? Is your own career more helpful?

In this regard, the author really dare not talk nonsense, after all, professional matters must be handed over to professional technical experts to answer more safely.

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