Big Data is no longer a buzzword that it used to be. It has become part of everyday discussions and has even been added to the English language dictionary. An entire ecosystem of tools and techniques around Big Data has evolved in the form of a multi-billion dollar industry and “Data Scientist” is said to be the best job of this decade. As the tools, technology and know-how of Big Data become mainstream, it is expected that a formula for successful implementation of Big Data initiatives must have become available by now resulting in a large number of companies successfully using Big Data analytics. However, in reality, a huge number of these initiatives continue to fail costing the companies lost investments and missed opportunities. This paper takes a look at the Big Data challenges mentioned in the literature. After going through various classifications of the problems, it was found that most issues arose due to the very nature of Big Data and the properties which make it different from traditional data. Additionally, it was seen that in some industries some of these properties had a much larger impact on the success of Big Data projects compared to other properties. Thus, a need to study the characteristics of Big Data in the context of different industries was felt and the 10 Vs model describing the ten properties of Big Data was chosen for it.