Studying Big Data as a career is certainly not for everyone.
Those who plan on having a profession in the field, though, should exhibit specific characteristics, according to a guide titled “The Field Guide to Data Science” by managing and technology consulting firm Booz Allen Hamilton.
Future data scientists should present themselves in these four ways to successfully carry out methodologies, Booz Allen Hamilton reports:
- Curiosity is important to further analyze data problems and find correlations between figures, even those that do not seem to be related.
- Creativity is necessary to develop innovative, new and alternative methods of solving data problems.
- Focus is mandatory to experiment a variety of methods in order to find the best solution. Scientists must be persistent in testing, regardless of the amount of failed procedures or time it takes to produce a successful technique.
- Attention to Detail is necessary to analyze data sets, as scientists must be thorough and rely on methodology and not instincts.
“The Field Guide to Data Science” is a 110-page model that seeks to define data science and explain how it is carried out, propose possible models to solve data problems, analyze data and show already conducted work by the firm, according to its website.
Along with the four aforementioned traits, prospective data scientists should also be skilled in three fields: computer science, mathematics and domain expertise. Computer science is necessary for “data manipulation and processing,” the guide reports.
Mathematics, specifically in subfields like statistics, geometry, linear algebra and calculus, is essential in order to comprehend the foundation for Big Data algorithms. Domain expertise defines the key problem, explains what data is relevant to the problem and provides a framework for evaluation.