One, multi-source big data collection and processing capabilities

Only to achieve accurate, real-time collection of a large number of different structures of raw data, and to achieve the fusion of different structures of data standardized processing, in order to ensure that big data intelligent analysis of the source? the right source?

Two, data mining algorithm capabilities

Data mining and algorithms will be clustered, segmented, isolated analysis, through internal exploration and mining, through all kinds of tools, able to extract intelligent data information from documents, photographs and other non-structural data, to solve the problem of the amount of data and the speed. Become a kernel booster for big data intelligent analysis.

Three, predictive analytics

Data mining algorithms to enable data analysis to better understand the data, through modeling of the data mining results of the predictability of the judgment is particularly important. It can be said that the ability to predictive analytics is the very essence of big data intelligent analytics.

Four, data quality management capabilities

Through the different platforms, different structures, different types of effective intelligent management and practice, so as to build a reasonable different types of databases, is the key to the big data intelligent analysis.

Fifth, the ability to visualize

Data visualization is the most basic requirement for big data intelligent analysis, through visualization can intuitively show the data, so that the data move, so that the data speak for themselves.

Sixth, intelligent analytics technology productization capabilities

The data industry has developed so far, the data analysis technology is no longer a moat. The future of data is the main point of competition, application scenarios is the key, it is imperative that the technology servicing, service platform, platform productization, so that intelligent analytics technology as soon as possible to achieve commercialization landing.

On what capabilities of big data intelligent analytics, Qingteng Xiaobian will share 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.