Broadly
With technological advances in recent years, especially since the turn of the millennium, data science has become a discipline in its own right, separate from computer science and more closely aligned with statistics. A niche has been created where data scientists are dedicated to solving business problems that depend on accessing, processing, and ultimately interpreting data.
This requires a particular skill set, such as a good understanding of programming languages, for example Python and R, to help simplify the analytical workflows required to access large disparate data sets. The skill set of the data scientist combined with that of the economist offers a winning formula for those seeking to distinguish themselves from the rest and dominate the modern economy.
Data and numbers
The above findings are supported by the fact that the prestigious London School of Economics (1) has expanded its curriculum in recent years to include a degree titled BSc Data Science and Business Analytics, with the slogan promising students that “they will learn to analyze.” data to address real-world problems,” real-world problems that are naturally based on economic and business relationships.
Another positive indicator is that former World Bank chief economist (2) and co-winner of the 2018 Nobel Prize in Economic Sciences, Paul Romer, is an advocate of Jupyter Notebook, an open source web application that allows users to create and share documents. including live code, equations, and visualizations to support interactive computing in multiple programming languages. This final observation is the core of Jupyter, the name Jupyter is an acronym that stands for Julia, Python and R, being the three programming languages.
That an economic giant is a strong proponent of a data science tool speaks volumes (no pun intended) and clearly indicates the direction of travel. As Romer noted in a blog post in 2018: “Jupyter rewards transparency; Mathematica rationalizes the secret. Jupyter encourages individual integrity; “Mathematica allows individuals to hide behind corporate evasion.” (3) Here you are comparing Jupyter to a competing platform, Mathematica, however, if…
