Enormous amounts of data have been generated and stored over the past few years. The McKinsey Global Institute reports this huge volume of data, which is generated, stored, and mined to support both strategic and operational decisions, is increasingly relevant to businesses, government, and consumers alike,7 as they extract useful knowledge from it.11
There is no globally accepted definition of "big data," although the Vs concept introduced by Gartner analyst Doug Laney in 2001 has emerged as a common structure to describe it. Initially, 3Vs were used, and another 3Vs were added later.13 The 6Vs that characterize big data today are volume, or very large amounts of data; velocity, or data generated and processed quickly; variety, or a large number of structured and unstructured data types processed; value, or aiming to generate significant value for the organization; veracity, or reliability of the processed data; and variability, or the flexibility to adapt to new data formats through collecting, storing, and processing.
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