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Top2. The Meaning Of “Big Data” – Big Data Analytics
It seems that there is no standard definition on “Big data” as researchers adopt different views depending on the situation they are interested in. Mashey (1999) seems to be the first commonly used the term. Big data is (a) a combination of a massive amount of various types of information and various types of analytical tools (Russom, 2011) or (b) the datasets that are beyond the ability of classic database software tools to accumulate, manage and analyse (Manyika et al., 2011). Additionally, big data is “big” and significant because the available datasets are very voluminous. Big data can generate knowledge and added value because of their conversion in useful information that improves decision-making (Markus & Topi, 2015).
Various Vs characterise big data. Laney (2001) introduces the 3Vs of big data as he describes the data management in three dimensions. Laney’s three Vs are Volume, Velocity and Variety. Veracity becomes the 4th V (IBM, 2014). Nowadays, researchers suggest that big data are characterized by many Vs and one C. The Vs are Volume, Velocity, Variety, Veracity, Validity, Variability, Visualization/Visibility, Virtual and Value. The C has to do with Complexity.