Access control for big data management systems

The term Big Data refers to a phenomenon characterized by “5 V”. By analyzing huge Volumes of data with a high Variety of formats, Big Data analytic platforms allow making predictions with high Velocity, thus, in a timely manner, low Veracity, therefore with low uncertainties, and with a high Value, namely, with an expected significant gain (Jin et al. 2015). As a matter of fact, business strategies are more and more driven by the integrated analysis of huge volumes of heterogeneous data, coming from different sources (e.g., social media, IoT devices).

This phenomenon has been pushed by numerous technological advancements. The most significant include the birth of NoSQL data-stores (Cattell 2011), and distributed computational paradigms, like MapReduce (Dean and Ghemawat 2004), which have jointly opened the way to the management and systematic analysis of huge volumes of semi-structured data (e.g., transactions, electronic documents and emails).

Overall, the support provided by Big Data platforms for the storage and analysis of huge and heterogeneous data-sets cannot find a counterpart within traditional data management systems. In addition, the advantages of these new systems are not only related to the outstanding flexibility and efficacy of the analysis services, as Big Data platforms outperform traditional systems even with respect to performance and scalability.

Source: https://cybersecurity.springeropen.com/articles/10.1186/s42400-018-0020-9