Four Typical Features of Big Data

Big data refers to "massive and complex data sets that cannot be extracted, stored, searched, * * * * enjoyed, analyzed and processed by existing software tools." The industry usually uses four V's (namely, volume, category, value and speed) to summarize the characteristics of big data.

One is the huge amount of data. Up to now, the data volume of all printed materials produced by human beings is 200PB( 1PB=2 10TB), while the data volume of all characters spoken by human beings in history is about 5EB( 1EB=2 10PB). At present, the typical personal computer hard disk capacity is in the order of TB, while the data volume of some large enterprises is close to the order of EB.

The second is the diversity of data types. This diversity also makes data divided into structured data and unstructured data. Compared with the structured data based on text that was easy to store in the past, there are more and more unstructured data now, including web logs, audio, video, pictures, geographical location information and so on. These types of data put forward higher requirements for data processing ability.

Third, the value density is low. The value density is inversely proportional to the total amount of data. Take video as an example, a video of 1 hour may only have one or two seconds of useful data in continuous monitoring. How to "purify" the value of data faster through powerful machine algorithms has become an urgent problem in the context of big data.

The fourth is fast processing speed (speed). This is the most striking feature that distinguishes big data from traditional data mining. According to IDC's "Digital Universe" report, it is estimated that by 2020, the global data usage will reach 35.2 ZB. In the face of such massive data, the efficiency of data processing is the life of an enterprise.