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The content of this article mainly focuses on what is the basic knowledge of big data's introduction to analysis. the content of the article is clear and clear, which is very suitable for beginners to learn and is worth reading. Interested friends can follow the editor to read together. I hope you can get something through this article!

To do a good job in data analysis, it is necessary to master many aspects of knowledge and skills, and soft power includes communication ability, expression ability, design ability and so on. Learning big data analysis requires knowledge of visual analysis, data mining algorithms, predictive analysis, semantic engine, data quality and data management.

Big data, let's take a look at the basics of getting started.

I. Visual analysis

The users of big data's analysis are big data analysts and ordinary users, but the most basic requirement for big data's analysis is visual analysis, because visual analysis can intuitively show the characteristics of big data. At the same time, it can be easily accepted by readers, as simple and clear as looking at the picture.

Second, data mining algorithm

The core of big data's analysis theory is the data mining algorithm, and all kinds of data mining algorithms based on different data types and formats can more scientifically show the characteristics of the data itself. all kinds of statistical methods recognized by statisticians all over the world can go deep into the data and dig out the recognized value. On the other hand, it is because of these data mining algorithms that big data can be processed more quickly.

III. Predictive analysis ability

Big data analysis is one of the application areas of predictive analysis, mining the characteristics from big data, through the scientific establishment of the model, through the model into the new data to predict the future data.

IV. Semantic engine

Big data analysis is widely used in network data mining, which can analyze and judge users' needs from users' search keywords, tag keywords, or other input semantics, so as to achieve better user experience and advertising matching.

V. data quality and data management

Big data's analysis is inseparable from data quality and data management, high-quality data and effective data management, which can ensure the authenticity and value of the analysis results in both academic research and business applications.

Big data's analysis is based on the above aspects, data analysis needs to have a variety of theoretical basis, such as basic data analysis knowledge: statistics, probability theory, basic theory of data mining, etc., for people engaged in data analysis industry, it is also important for the thinking and understanding of the theory.

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