Big Data Analytics = Machine Learning + Cloud Computing

“Big Data” can mean different things to different people. The scale and challenges of Big Data are often described using three attributes, namely volume, velocity, and variety (3Vs), which only reflect some of the aspects of data. In this chapter, we review historical aspects of the term “big data” and the associated analytics. We augment the 3Vs with additional attributes of big data to make it more comprehensive and relevant. We show that Big Data is not just the 3Vs, but actually 3 2 Vs; that is, 9Vs covering the fundamental motivation behind Big Data, which is to incorporate business intelligence based on different hypothesis or statistical models so that Big Data analytics (BDA) can enable decision makers to make useful predictions for making some crucial decisions or researching results. History of Big Data has demonstrated that the most cost-effective way of performing BDA is to employ machine learning (ML) on the cloud computing (CC)-based infrastructure or simply, ML + CC → BDA. This chapter is devoted to help decision makers by defining BDA as a solution and opportunity to address their business needs.

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