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Data Science: A new breed of study

April 27, 2016 | Raid Amin, Professor, Department of Mathematics and Statistics | ramin@uwf.edu

As students begin to leverage their university education for entry into the job market, universities look beyond traditional fields of study to those that lead to future-ready careers, such as a data science. So, what is data science? Data Science is an interdisciplinary field that extracts knowledge or insights from data in various forms, a direct extension of data analysis fields like statistics, data mining, and predictive analytics. 

Data scientists are a new breed of data analysis experts with the technical skills to solve complex problems and the curiosity to explore whatever problems need to be solved. They are part statistician, part mathematician, part computer scientist and part trend-spotter. And, because they link both the business and IT worlds, they are highly sought-after and well paid. Who wouldn’t want to be one? Typical job duties of a data scientist may include the following:

  • Collecting large amounts of “messy” data and transforming it into a more usable format.
  • Solving business-related problems using data-driven techniques.
  • Working with a variety of programming languages, including SAS, R and Python.
  • Using statistical tests and distributions, and analytical techniques such as machine learning, deep learning, and text analytics to solve problems.
  • Communicating and collaborating with both IT and Business.
  • Finding order and patterns in data, as well as spotting trends that can help a business’s bottom line.  [http://www.sas.com/en_us/insights/analytics/what-is-a-data-scientist.html].

The American Statistical Association states: “The rise of data science, including Big Data and data analytics, has recently attracted enormous attention in the popular press for its spectacular contributions in a wide range of scholarly disciplines and commercial endeavors. These successes are largely the fruit of the innovative and entrepreneurial spirit that characterize this burgeoning field. Nonetheless, its interdisciplinary nature means that a substantial collaborative effort is needed for it to realize its full potential for productivity and innovation. Certainly, data science intersects with numerous other disciplines and areas of research. Indeed, it is difficult to think of an area of science, industry, commerce, or government that is not in some way involved in the data revolution. But it is databases, statistics, and distributed systems that provide the core pipeline.” [http://magazine.amstat.org/blog/2015/10/01/asa-statement-on-the-role-of-statistics-in-data-science/]

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