◾ Data Process and Analysis Technologies of Big Data
Shui Yu, Xiaodong Lin, Jelena Misic, Xuemin (Sherman) Shen
Abstract
Shui Yu, Xiaodong Lin, Jelena Misic, Xuemin (Sherman) Shen
Abstract
Mayer-Schonberger and Cukier dene Big Data as “the ability of society to harness information in novel ways to produce useful insights or goods and services of signicant value [1].” roughout the current literature, Big Data is usually dened by the three Vs: volume, velocity, and variety. Volume refers to the large amount of data. “Large” ranges from gigabytes to petabytes. Typically, the volume increases, but the data itself does not change. Velocity refers to the speed at which the data volume grows. For instance, on Facebook more than 500 TB of data is created daily [2]. Variety describes the data types in Big Data. Big Data usually consists of structured, semistructured, and unstructured data. Big Data requires all 3 Vs to apply (Figure 6.1).
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Mayer-Schonberger and Cukier dene Big Data as “the ability of society to harness information in novel ways to produce useful insights or goods and services of signicant value [1].” roughout the current literature, Big Data is usually dened by the three Vs: volume, velocity, and variety. Volume refers to the large amount of data. “Large” ranges from gigabytes to petabytes. Typically, the volume increases, but the data itself does not change. Velocity refers to the speed at which the data volume grows. For instance, on Facebook more than 500 TB of data is created daily [2]. Variety describes the data types in Big Data. Big Data usually consists of structured, semistructured, and unstructured data. Big Data requires all 3 Vs to apply (Figure 6.1).
Key concepts: Big data, Computer science, Process (computing), Data science, Data mining, Operating system