In the age of big data analytics, there are hardly any data-rich companies that do not want their data to be extracted, evaluated, and inferred to provide more business inside. In the past, analyzing large datasets (structured or unstructured) that span terabytes or petabytes used to be expensive and a technically challenging task to a team; distributed computing was harder to keep track of, and hardware to support this kind of infrastructure was not financially feasible to everyone.