Although the term Big Data is well known to people, there is no common definition. Among the various existing definitions of big data, the one proposed by Gantz and Reinsel in 2011 is relatively more recognized. Their definition states that big data represents very large volumes of all types of data [2]. Another widely recognized definition is proposed in a report by McKinsey & Company [3]. The report states: “Big data refers to data sets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze.” From these definitions, we can know that an important characteristic of big data is large size. However, the definition of “large size” can vary over time. In recent years, with the emergence and development of social networks (e.g. Facebook, Twitter), e-commerce (e.g. eBay, Amazon) and other network platforms, the volume of data has grown very rapidly. In the past, we considered gigabytes (GB) to be “large,” but today only above the petabyte (PB) level can we be defined as “large.” Although large volume is a characteristic of big data, it does not mean that big data is equivalent to mass data. There are also some other characteristics that can distinguish