Do you know about the career development of positions in the field of big data

Methods/steps

The National Information Center's "2017 China's Big Data Industry Development Report" comprehensively analyzes the development of China's big data industry in a number of dimensions, including talent, policy, investment and financing, innovation and entrepreneurship, industrial development, regional potential, and the influence of institutions and people. The results show that China's big data development is generally in its infancy. However, the heat of capital in the field of big data is still firm and rising against the trend, the total amount of financing for big data enterprises and the average amount of financing for a single project show an accelerated upward trend, and the field of big data has become a blue ocean of capital.

From the position, from big data development, mining, algorithm, analysis, to architecture. From the level point of view, from engineers, senior engineers, to architects, and even to scientists. Moreover, fitting different industry sectors, there are positions derived specifically for these industries, such as data analysts involved in the financial sector.

There are many jobs related to big data, including data analysts, data mining engineers, big data development engineers, big data product managers, visualization engineers, crawler engineers, big data operations managers, big data architects, data scientists and so on, and the following is about a few of these positions.

Data analyst: daily work content has three aspects, the first is a temporary number, the second is the report of the demand analysis, the third is the analysis of business topics.

Data mining engineers: daily work content is mainly five categories. The first is user base research, the second is personalized recommendation algorithm, the third is the model applied in the field of wind control, the fourth is the knowledge base of the product, the fifth is text mining, text analysis, semantic analysis, image recognition.

Data product manager: daily work content: the first is the construction of big data platform, make it easier to get data, use data, build a perfect indicator system, realize the whole process of monitoring the business, improve the efficiency of decision-making, reduce the operating costs, improve the level of receivables; the second is the analysis of data needs, the formation of data products, internally can improve efficiency, control costs, externally to increase the generation of income, and ultimately realize the value of data. Ultimately, the realization of the value of the data.

Big Data R&D Engineer: This position is the most in demand, and the daily work has three aspects: the first is the collection of data, such as crawlers, log collection, etc.; the second is data preprocessing, ETL work, such as data cleansing, transformation, integration, statute, etc.; and the third is the development of big data applications and visualization.

In addition, more and more industry sectors are now involved in big data, which can be roughly divided into two categories: big data engineering and big data analytics. These areas are independent and interrelated.

With the arrival of AI (Artificial Intelligence), the future of big data needs to rely on the massive computing power of the cloud computing platform, while providing content to AI through big data. So in the next ten years, cloud computing, big data, artificial intelligence is the most far-reaching impact on society in this era of technology, for which we need to prepare in advance.