One of the most important elements of a Big Data project is a rather obvious but often overlooked item: people. Without human involvement or interpretation, Big Data analytics becomes useless, having no purpose and no value. It takes a team to make Big Data work, and even if that team consists of only two individuals, it is still a necessary element.
Bringing people together to build a team can be an arduous process that involves multiple meetings, perhaps recruitment, and, of course, personnel management. Several specialized skills in Big Data are required, and that is what defines the team. Determining those skills is one of the first steps in putting a team together.
One of the first concepts to become acquainted with is the data scientist; a relatively new title, it is not readily recognized or accepted by many organizations, but it is here to stay.
A data scientist is normally associated with an employee or a business intelligence (BI) consultant who excels at analyzing data, particularly large amounts of data, to help a business gain a competitive edge. The data scientist is usually the de facto team leader during a Big Data analytics project.
The title data scientist is sometimes disparaged because it lacks specificity and can be perceived as an aggrandized synonym for data analyst. Nevertheless, the position is gaining acceptance with large enterprises that are interested in deriving meaning from Big Data, the voluminous ...