CSP 2017 Online Program

Data Science, Statistics, Analytics, Data Engineering: What Does It All Mean? (303460)

Keywords: data, science, predictive, analytics, statistics, engineering

In August of 2015, the ASA published a statement on the Role of Statistics in Data Science. The purpose of that statement appears in its final sentence, “The ASA aims to facilitate collaboration between statisticians and other data scientists and thus enable them to achieve more than they could on their own.” Ron Wasserstein, Executive Director of ASA, discussed the statement in his blog and outlined some of the ASA’s efforts to “facilitate further collaboration between statisticians and other data scientists.” This poster is aimed at offering the audience an analysis of what Statisticians, Data Scientists, Data Engineers, and those practicing Predictive Analytics say about their jobs, relationships, and their roles. The analysis here involves data arising from the usage of terms related to recent controversies such as what are statistics, data science, predictive analytics, and data engineering being discussed currently in the ASA Connect Digest Online. This online activity appears in the ASA Blog Posts with the title Data Science and Statistics. What the audience will learn about Data Science, Statistics, Analytics, and Data Engineering will enable them to better: 1) communicate with their clients, collaborators, and customers; 2) to have a positive impact on clients, and their business operations; and 3) to have a positive impact on the organization where those clients, collaborators, and customers live and work. In summary, the session is designed to increase the awareness of participants in the Conference on Statistical Practice of what is meant by the designations of Statistics, Data Science, Predictive Analytics, and Data Engineering when practicing as a statistician. The analysis of the blog contents involves a Word Cloud, also known as a Wordle, which will facilitate the visualization of the blog contents and display what is important to statisticians, data scientists and others who work in this area. The conclusion is that data is king and everything else is secondary to collaboration between those who say they are statisticians, data scientists, those who do predictive analytics, and those who are data engineers. This knowledge should help CSP 2017 participants to fulfill the purpose of the ASA statement on the Role of Statistics in Data Science.