Why The 3V’s Are Not Sufficient To Describe Big Data
Resource Origin: DataFloq
"It is generally accepted that big data can be explained according to three V’s: Velocity, Variety and Volume. In a 2001 research report, META Group (now Gartner) analyst Doug Laney defined big data as being three-dimensional, i.e. increasing volume (amount of data), velocity (speed of data in and out), and variety (range of data types and sources). Later in 2012 Gartner updated the definition of big data as high volume, high velocity, high variety.
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Resource Origin: DataFloq
"It is generally accepted that big data can be explained according to three V’s: Velocity, Variety and Volume. In a 2001 research report, META Group (now Gartner) analyst Doug Laney defined big data as being three-dimensional, i.e. increasing volume (amount of data), velocity (speed of data in and out), and variety (range of data types and sources). Later in 2012 Gartner updated the definition of big data as high volume, high velocity, high variety.