"Data science and big data technology" is a profession established only in recent years, some people say that specialists should not learn data science and big data, because data science and big data is more difficult to learn. However, the employment prospects of big data professionals is very broad, a serious shortage of talent, forcing companies to constantly lower the threshold of work experience, and even go out of their way to cultivate talents from zero, so it is still worthwhile for all the specialists to learn.

Big Data specialists are good at finding jobs

Because Big Data is a relatively hot project in the IT industry, the demand for Big Data-related talent from various employers is now particularly high. Relevant statistics show that in the next 3~5 years, China needs 1.8 million data talents, but currently there are only about 300,000 people. So compared to the saturated state of other jobs, big data is in the blue ocean, learning big data related knowledge can catch up with the big data boom, to meet the current demand for jobs in various employers.

Secondly, because of the big gap in big data talent, the employers of big data-related positions are more ideal than other positions in the salary treatment of employees.

We take big data development engineers to do a reference, from the point of view of the employment data of specialists, big data engineers in the 8K salary below the specialization of students accounted for only 2%, the other students graduated from the work of a year after the starting salary of all more than 8K, the salary of more than 1W specialists for the majority.

Emphasis on big data has become more and more institutions, up to the Ministry of Defense, down to the Internet startups, financial institutions need to do innovation drive through big data projects, the need for data analysis or processing positions are also a lot; common food manufacturing, retail e-commerce, medical manufacturing, traffic detection, etc. also need data analysis and processing, such as optimization of inventory, cost reduction, forecasting demand and so on. Talent is mainly divided into three main categories: big data system development class, big data application development class, big data analysis class.

(1) big data system development engineers: suitable for learning big data specialists in employment. Mainly responsible for big data system research and development work, including large-scale unstructured data business model construction, big data storage, database architecture design and database detailed design, optimize the database architecture, solve the database center construction design problems. They are also responsible for the daily operation of the cluster, monitoring and configuration of the system, and integration of Hadoop with other systems.

(2) Big data application development engineers: responsible for building big data application platforms and developing analytic applications. They are familiar with tools or algorithms, programming, packaging, optimizing, or deploying different MapReduce transactions. They develop a variety of applications and industry solutions based on big data technologies.

(3) Big Data Analyst: Suitable for specialists studying Big Data. Mainly responsible for the use of algorithms to solve analytical problems, and engaged in big data mining work. Their greatest skill is to be able to make data tell the truth; in addition, they also have a certain field of expertise to help develop data products and promote the continuous updating of data solutions.

(4) Data Visualization Engineers: have good communication skills and team spirit, strong sense of responsibility, and excellent problem solving skills. They are responsible for the application of graphical tools and means in the collected high-quality data to reveal the complex information in the data at a glance, to help companies better develop big data applications and discover the great wealth behind big data.