Big Data has spawned a number of careers related to big data processing, through the mining and analysis of data to influence the business decisions of enterprises, this group of people in foreign countries are called data scientists. In China, the application of big data has just sprouted, the talent market is not so mature, it is difficult to have a generalist to complete all the links in the whole chain. More companies will recruit talents who can complement their existing teams according to their existing resources and shortcomings. The requirements for big data jobs vary from company to company: some emphasize database programming, some highlight knowledge of applied mathematics and statistics, some require experience in consulting firms or investment banks, and some hope to find application-oriented talents who understand products and markets. Because of this, many companies will give some new titles and definitions to this group of people dealing with big data for their business type and team division of labor: data mining engineers, big data specialists, data researchers, user analytics specialists and so on. These different career positions can be broadly categorized into two groups, one technical and one business.

And want to get started in the field of big data, there will generally be the following requirements:

1. math and statistics-related background

Baidu's Chief Data Scientist Shen Zhiyong that the lack of theoretical background of the data workers, it is more likely to enter a skills on the danger zone (Danger Zone) - a bunch of numbers, and the data workers are more likely to enter a skills on the Danger Zone (Danger Zone) - a bunch of numbers. According to different data models and algorithms can always be primed with some results, but if you don't know what that means, it's not really meaningful results, and that kind of result is also easy to mislead you. "Only with some theoretical knowledge can you understand models, reuse them and even innovate them to solve real problems."

2. Computer coding skills

Practical development skills and the ability to work with data on a large scale are also considered essential skills for being a big data engineer. "Because much of the value of data comes from the process of mining, you have to be hands-on to find the gold." Zheng Lifeng said.

For example, many of the records people generate on social networks are now unstructured data, and how to grab meaningful information from all that clueless text, voice, images, and even video requires big data engineers to do the digging themselves. Even in some teams where the big data engineer's role is focused on business analytics, it's important to be familiar with the way computers process big data.

3. Knowledge of a specific application domain or industry

Big data cannot be divorced from the marketplace because big data can only generate value when combined with domain-specific applications. So, experience in one or more verticals forms your knowledge of that industry, which helps a lot to become a big data engineer afterwards, and thus it is a more convincing plus point when applying for this job. You can't just understand data. You also have to have an in-depth knowledge of certain industries. Preferably one that fits your company's business direction.

If you want to engage in the technical direction, many of the learning paths of the above highly praised answers are very detailed, if you want to engage in the business direction of big data analytics work, the requirements for the technical background is not so high. Currently on the market BI products have crossed into the stage of intelligent BI, the user level emphasizes low-code (or zero-code) development, seamless docking, flexible deployment, and, with the ability of AI algorithms to build future-based analysis models, such as sales forecasting, intelligent scheduling and so on. Also recommend you a BI product, DataFocus, I think it is the country's current easier to get started, want to start big data analytics white very friendly products.