What we consider Big Data today will change with innovation and technological progress. However, a generally accepted definition is a collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications (Wah, Cheng, & Wang, 2015). The amount of digital data available has increased exponentially, from 25% in 2000 to more than 98% in 2015. It is expected to double every two years, with a current capacity of 130 exabytes and is expected to reach around 40,000 exabytes of here 2020. For a quick understanding of exactly how big this number is, one exabyte is equivalent to 1 billion gigabytes of data. Due to its size, it offers businesses an untapped resource with vast potential. Big data can be seen as the new oil that will fuel the future information economy (Wah et al., 2015). There are four distinct categorizations for Big Data: structured, unstructured, semi-structured and mixed. Structured data is data that can be parsed into existing data models and the hard information is extractable. Unfortunately, structured data only makes up about five percent of all big data. The majority is unstructured data that cannot be analyzed using traditional data processing methods and includes text, audio, video and images. Semi-structured refers to data that is analyzable but lacks a formal data model structure. And finally, mixed is a combination of the three previous data