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This article mainly introduces the 4V characteristics of big data, which has a certain reference value, friends who need can refer to it. I hope you will learn a lot after reading this article. Next, let the editor take you to learn about it.

Big data's 4V features are: 1, Volume; with the rapid development of information technology, data began to grow explosively. 2. High speed (Velocity). 3. Diversity (Variety); mainly reflected in many data sources, many data types and strong correlation between data; 4, Value.

Big data (big data), IT industry term, refers to the data set that can not be captured, managed and processed with conventional software tools within a certain period of time. It is a massive, high growth rate and diversified information asset that requires a new processing model to have stronger decision-making power, insight and process optimization ability.

The 4v characteristics of big data

Big data's characteristics, put forward by Viktor Scheinberg and Kenneth Keyer in the big data era, big data's 4V characteristics: Volume, Velocity, Variety, Value.

(1) scale

With the rapid development of information technology, data began to grow explosively. The data in big data is no longer measured in units of a few GB or TB, but in terms of PB (1000 T), EB (1 million T) or ZB (1 billion T).

(2) Diversity

Diversity is mainly reflected in three aspects: many data sources, many data types and strong correlation between data.

There are many sources of ① data, and the traditional data faced by enterprises are mainly transaction data, while the development of the Internet and the Internet of things has brought data from many sources, such as social networking sites, sensors and so on.

The diversity of big data's forms is determined by the fact that the data comes from different application systems and different devices. Generally can be divided into three categories: first, structured data, such as financial system data, information management system data, medical system data, etc., which is characterized by strong causal relationship between data; second, unstructured data, such as video, pictures, audio, etc., which is characterized by no causal relationship between data; third, semi-structured data, such as HTML documents, e-mails, web pages, etc., which is characterized by weak causal relationship between data.

There are many types of ② data, and it is mainly unstructured data. In traditional enterprises, data are saved in the form of tables. In big data, 70% of the data is 85% of the data, such as pictures, audio, video, web logs, link information and other unstructured and semi-structured data.

There is a strong correlation between ③ data and frequent interactions, such as photos and logs uploaded by tourists on the way to travel, which are strongly related to tourists' location, itinerary and other information.

(3) High speed

This is the most prominent feature that distinguishes big data from traditional data mining. The important difference between big data and massive data lies in two aspects: on the one hand, big data's data scale is larger; on the other hand, big data has stricter requirements for the response speed of data processing. Real-time analysis rather than batch analysis, data input, processing and discarding are effective immediately, with almost no delay. The growth rate and processing speed of data is an important embodiment of big data's high-speed.

(4) value

Although the enterprise has a lot of data, it is only a very small part of it that brings value. The hidden value behind big data is huge. Because the proportion of valuable data in big data is very small, and the real value of big data is reflected in a large number of irrelevant various types of data. Mining valuable data for future trend and pattern prediction and analysis, and through in-depth analysis of machine learning methods, artificial intelligence methods or data mining methods, and applied to agriculture, finance, medical and other fields, in order to create greater value.

Thank you for reading this article carefully. I hope the editor will share what the 4v features of big data are helpful to you. At the same time, I also hope you can support us, pay attention to the industry information channel, and find out if you have any problems. detailed solutions are waiting for you to learn!

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