Large Volume of Data (Volume)

The first characteristic is large volume of data. The starting unit of measurement for Big Data is at least P (1000 T), E (1 million T) or Z (1 billion T).

Variety

The second characteristic is the variety of data types. Including web logs, audio, video, images, geolocation information, and so on, multiple types of data put higher demands on the processing power of data.

Low value density (Value)

The third characteristic is the relatively low value density of data. With the widespread application of the Internet of Things, information perception is ubiquitous, the amount of information, but the value of low density, how to complete the value of the data more quickly through powerful machine algorithms "purification", is the big data era need to be resolved.

Velocity (Velocity)

The fourth feature is fast processing speed, high timeliness requirements. This is the most significant feature of big data that distinguishes it from traditional data mining.

The established technical architecture and route, has been unable to efficiently deal with such a huge amount of data, and for the relevant organizations, if the huge investment in the collection of information can not be processed in a timely manner through the feedback of effective information, it will be more than worth the loss. It can be said that the era of big data has posed a new challenge to human data mastery, and has also provided unprecedented space and potential for people to gain more profound and comprehensive insights.