Big data involves too wide a range of industries, in politics, education, media, medicine, business, industry, agriculture, the Internet and many other aspects are applied. In terms of the comprehensive value potential of big data applications, the four major industries of information technology, finance and insurance, government and wholesale trade have the highest high potential. Specifically, in terms of the amount of data per company in the industry, the four categories of information, finance and insurance, computer and electronic equipment, and utilities have the largest amount of data. It can be seen that both the scale of investment and application potential, the information industry and the financial industry is the focus of the application of big data industry.

The application of big data first of all need to the complexity of the big data sets, obscure and difficult to understand the data report into easy to read, friendly, easy to understand, visualization is undoubtedly the best choice. In terms of the application of big data visualization, the scope of application is extremely wide, such as government applications, business decision-making, public **** services and so on.

The application of big data requires accurate customer profiling, and enterprise customer profiling includes enterprise production, circulation, operation, finance, sales and customer data, and related industry chain upstream and downstream data. It is only on the basis of customer profiling that accurate marketing can be carried out effectively. Through big data analysis and mining the user group's cultural concepts, consumer income, consumption habits, lifestyle and other data, the user group will be divided into more refined categories, according to the different user groups to formulate different brand promotion strategies and marketing strategies to improve user loyalty, cultivate potential customers that can bring high value to the enterprise, and increase market share.

What are the prospects for the application of big data visualization, Qingteng Xiaobian has shared with you here. If you have a strong interest in big data engineering, I hope this article can help you. If you still want to learn more about data analysts, big data engineers tips and materials, you can click on other articles on this site to learn.