Big Data Security Management

Background

Big Data is generally considered to have three defining characteristics: volume, variety and velocity (Zikopoulos, et al. 2012). When at least one of the dimensions is significantly high, the data is labeled big. Traditional techniques and technologies are not sufficient to handle big data. With the enormous size, speed, and/or multiplicity, big data processing requires a set of new forms of technologies and approaches to achieve effective decision support, insight discovery, and process optimization (Lancy, 2001). Although the three V’s of big data definition has wide acceptance, recently, there have been attempts to expand the dimension of big data to include value and veracity (Demchenko, et al., 2013). The value dimension of big data deals with drawing inferences and testing hypothesis, and the veracity dimension is about authenticity, accountability, availability, and trustworthiness. Some researchers (e.g., Biehn, 2013) have suggested adding value and viability to the three V’s.

Although big data has been discussed for over a decade since 2000, interest in big data has only experienced significant growth in the last few years. Figure 1 shows the Google search interest for the search term “Big Data” from January 2004 to June 2014. The figure does not show actual search volume. The y axis represents search interest relative to the highest point, with the highest point being scaled to100. For more historical information about big data, the reader is referred to Press (2013), which documents the history of big data that dates back to the 1940s.

Figure 1.

Big Data Web Search Interest, January 2004 – June 2014

Source: Google Trends