  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 3Vs with additional attributes of Big Data
to make it more comprehensive and relevant. We show that Big Data is not just
3Vs, but 32 Vs, that is, 9 Vs covering the fundamental motivation behind Big
Data, which is to incorporate Business Intelligence (BI) based on different
hypothesis or statistical models so that Big Data Analytics (BDA) can enable
decision makers to make useful predictions for 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.
