What are the job prospects for big data?

At present, the demand for big data talents is relatively large, and the development of big data in China as a whole is still in its infancy, although the pattern of rapid development has been basically formed, but a large number of big data professionals are needed in data openness and sharing, core technology breakthroughs, and big data-driven development. If you need big data training, it is recommended to choose [Danai Education]. Big Data Employment:

1. Big data positions can be divided into three categories: big data system R&D personnel, big data application development talents and big data analysis talents. The amount of big data salary depends on one's own technical strength and one's own opportunities.

2. Among the employment directions chosen by big data personnel, the most common and in demand are big data system R&D engineers, [big data application development engineers] and data analysts. The current IT industry as a whole is interested in...

Big Data Career Prospects.

With the maturity of big data technology, the popularization and development of big data applications have just begun, and we expect that the next 20 years, or even longer, will be the first stage of development of big data, and related industries will attract huge development opportunities. Most industries need it, and there are many needs related to marketing, marketing, and operations. Big data is not a position, after learning the big data certification, you can work as a big data mining expert, senior industry analyst, big data business architect, big data architect, big data algorithm engineer, big data development engineer, big data operation and maintenance engineer.

Whether at home or abroad, big data-related talents are in short supply. At present, the market is in urgent need of big data-related management talents who can use the results of big data analysis.

According to the "Big Data Talent Report" released by the Digital Union Xunying, there are only 460,000 big data talents in the country, and the gap of big data talents will be as high as 1.5 million in the next 3-5 years.

According to the "2016 China Internet Hottest Jobs Talent Report" released by the professional social networking platform LinkedIn, R&D engineers, product managers, human resources, marketing, operations and data analysis are the six most in-demand talent positions in China's Internet industry. Among them, R&D engineers are in the greatest demand, while data analysis talents are the most scarce. The LinkedIn report shows that the supply index of data analytics talent is the lowest, which is only high, which is highly scarce.

Data analysis talents also have the fastest job hopping speed, with an average job hopping speed of one month. According to the statistics of the Data Analysis Professional Committee of the China General Chamber of Commerce, the gap of basic data analysis talents in China will reach 14 million in the future, and more than 60% of the positions recruited by BAT enterprises are recruiting big data talents.

Big data employment direction.

1.Hadoop big data development.

The market demand is strong, the main body of big data training, and the current focus of IT training institutions.

Corresponding positions: big data development engineer, crawler engineer, data analyst, etc.

2.Data Mining, Data Analysis & Machine Learning.

The starting point of learning is high and difficult, and there are only a few training institutions on the market to do it.

Corresponding positions: data scientist, data mining engineer, machine learning engineer, etc.

3.Big data operation and maintenance & cloud computing.

The market demand is medium, and it is more inclined to Linux and cloud computing disciplines.

Corresponding position: big data operation and maintenance engineer.

The outlook for big data employment is very positive.

As a new Internet industry, big data is still in the early stage of rapid development, and in this rapidly developing field, new things are being generated all the time.

From the perspective of overall development, the future of the big data industry will show a straight upward trend.

There are three main directions of employment in big data:

The first is data analysis big data talents, the second is system research and development big data talents, and the third is application development big data talents.

Their basic positions are big data system R&D engineers, big data application development engineers, and big data analysts.

First of all, the technology of big data is a mature technology, with mature open source platforms, solutions, and technical routes. Therefore, if a company wants to engage in big data business, it only needs to recruit suitable engineers and follow the steps, and the core is only to deal with big data business.

Artificial intelligence is a cutting-edge technology and is fundamentally in the exploration stage.

First of all, there are very few companies that can master the lowest level of deep learning technology, and the companies that can apply the learning model of large companies to process business are actually very limited. This is the most fundamental embodiment of a technology's immaturity, because industrialization is characterized by division of labor and assembly lines, and computer technology is the same, if you can only rely on the laboratory to be an alpha dog, it is far from meeting the standards of industry and commercialization.

In addition, whether deep learning is the branch or core of artificial intelligence is not only a technical question, but also a theoretical question. I think the ultimate goal of artificial intelligence is the autonomous consciousness of the machine, and the theoretical basis of consciousness still needs the support of human brain science and neuroscience, and these theories are still under continuous research, so it is impossible for human beings to have an essential breakthrough in artificial intelligence without 100% understanding the brain and consciousness.

So the current artificial intelligence companies are either a gimmick to cheat money, or sell dog meat on the head of a sheep. Of course, there are also teams that are inspired by the underlying R&D, but there are only a handful, and there are a small number of companies that want to make products on immature platforms, which is actually very risky, and immature technology also means that the iteration speed is fast, waste resources, and produce some outdated products.

Big data is the development trend of the future, and we are very optimistic about the employment prospects.

The employment prospects of big data are still very good.

The value of big data is reflected in the following aspects:

1) Enterprises that provide products or services to a large number of consumers can use big data for precision marketing.

2) Small and medium-sized micro enterprises with a small and beautiful model can use big data to do service transformation;

3) In the face of the pressure of the Internet, traditional enterprises that must transform need to keep pace with the times and make full use of the value of big data.

However, the great significance of "big data" in economic development does not mean that it can replace all social problems.

Rational thinking, scientific development.

The logic can't be lost in massive amounts of data.

Middle. Famous economist Ludwig von Mises.

He once reminded: "Today, there are many people who are so busy with the useless accumulation of information that they lose their understanding of the special economic significance of selling and solving problems." "This is really something to be wary of.

In this era of rapidly evolving smart hardware, one of the most important questions plaguing application developers is how to find that delicate balance between power, range, transfer rate, and cost.

Organizations use data and analytics to help them reduce costs, increase efficiency, develop new products, make more informed business decisions, and more. For example, by combining big data and high-performance analytics, the following can be beneficial to the business:

1) Timely analysis of the root causes of failures, problems, and defects can potentially save businesses billions of dollars every year.

2) Plan real-time this pure core traffic route for thousands of delivery vehicles to avoid congestion.

3) Analyze all SKUs, price and clear inventory with the goal of maximizing profits.

4) According to the customer's buying habits, push the preferential information that he may be interested in.

5) Quickly identify gold customers from a large number of customers.

6) Use clickstream analytics and data mining.

to circumvent fraud.

1.From the national big data strategy in 2018, it can be seen that the development of the big data industry is a big mess.

2.At present, there are only 460,000 big data practitioners in the country, and the talent gap is 1 million, and the talent gap will gradually expand in the next 2-3 years.

3.In 2018, the average monthly salary of the big data industry ranked first among all industries, and far exceeded it.

Second, the third place 6-7k.

4.The connection between big data and artificial intelligence and cloud computing is getting closer and closer, and big data is docking with various industries, and its application will gradually expand to urban affairs, industrial manufacturing, agriculture, tourism and other aspects, and the future jobs will continue to increase.

As the girlfriend of a sophomore majoring in big data management and application, I learned from my boyfriend that this major is very good, and it has very good employment prospects for this information age.

<> I will talk about these three aspects separately

What does Chun Tangerine learn in Big Data Management and Application Major?

The courses studied in the data management and application major mainly include microeconomics, macroeconomics, fundamentals of management, operations research, applied statistics, econometrics, business data analysis, multivariate statistical analysis and r modeling, time series analysis methods, big data foundations, facility object-oriented programming, database systems, data warehouse and data mining, text analysis and text mining, network society marketing analysis, quantitative financial methods, etc.