Shulou(Shulou.com)06/02 Report--

Let me ask you a question:

Have you made up your mind to work for big data many times, but give up because you don't know how to start?

Have you ever interviewed big data for a job, but hit a brick wall because of lack of experience?

You perform very well in the company, and the assigned tasks can always be completed well and quickly, but over the past two years, your salary has been 13,000, and you have asked the leader for a raise many times. As a result, the leader always gets it.

You know in your heart that your job is in a bottleneck, and it's hard to increase your salary by more than 50%, and the only thing you can do is to change careers.

Recently, several programmers around me are learning Spark, Hadoop and other related knowledge, as if they do not keep up with the pace of the times, they will be thrown out of the rhythm of half the street at any time; and open Zhihu, topics such as "how to get started with big data" and "how Java Web programmers transform big data" have also attracted much attention.

McKinsey reports that big data and artificial intelligence are in short supply and demand is surging. They have technical advantages, and big data industry is also very short of people, now is the most appropriate time to join the industry.

So what does big data's popularity depend on?

1. The technology is becoming more and more mature and the application space can be expanded.

Big data technology, which was first mentioned in 1980, has developed by leaps and bounds in recent years. Compared with the stretched computing power of neural network algorithms decades ago, today's processors undoubtedly play a key role in the high-speed processing of large-scale data. With the help of the high performance of the processor, it is possible for us to complete the machine learning and model training of PB-level data in a short time, which lays the foundation for the rapid iteration of image and speech recognition products that are highly dependent on deep learning. Big data's application space has been expanded, thus giving birth to technology companies that provide related products and services.

two。 Attaching importance to data assets, data mining has become inevitable

Modern information technology makes the amount of data generated every day grow exponentially, and the development of enterprises can no longer avoid the mining and utilization of data value.

3. Technology gives birth to a new business model, which contains new opportunities for entrepreneurship

Big data's industrial chain has spawned a new business portfolio model for providing products and services for different sections, whether it is Jinri Toutiao, which uses recommendation algorithms to provide content services, TalkingData, which provides monitoring services based on data integration, or Aliyun, which provides infrastructure support, all found the entrepreneurial opportunities contained in big data's industrial chain.

4. The market is in short supply, and there is plenty of room for job challenges.

According to the survey of mainstream data media, the current talent of big data is only 460000, and the talent gap of big data will be as high as 1.5 million in the next 3-5 years. Some institutions have predicted the salary range and job-hopping increase of popular positions in the domestic science and technology field in first-tier cities in 2018: in big data's direction, due to the high degree of talent scarcity, the salary of big data engineers is generally higher under the same working years, and the salary increase will also exceed that of other positions.

At present, the starting salary of ordinary Hadoop big data engineers is also in 20K/ month. With a little experience, the salary will be much higher, and the salaries of people related to data mining, machine learning and artificial intelligence will be even higher.

(the above data are sorted out from the pull hook net)

For ordinary programmers, working in Hadoop big data and data mining is the best choice for three reasons:

1. The threshold is low, and you can learn it if you have the basis of programming.

2. Compared with other development positions, the salary is 10-200000 higher, and the annual salary of 250000 is only the lowest level.

3. Python is the most mainstream programming language in the field of artificial intelligence, so mastering Python big data technology now is more conducive to seamlessly entering the AI field in the future.

How to learn to get started quickly and master it?

When you really start learning, you always don't know where to start, resulting in inefficiency, affecting the confidence to continue learning, and even affecting the current work.

Big data's systematic study materials have been carefully prepared for you. From the Linux-Hadoop-spark-., you can click to enter.

In fact, the most important thing is that you do not know which techniques need to be mastered, step in frequently while learning, and end up wasting a lot of time, so it is necessary to have a set of practical video courses to follow.

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