Data Science Principal Areas

There are many areas, processes, and disciplines relating to data science. A cursory search on Google alone would reveal different frameworks, theories, and opinions on wide varieties of topics relating to data science. For the average people, all these diverse topics can be confusing when all they need is just a cursory understanding of what data science is all about. Despite that, in my opinion, majority of the materials, diverse as they are, do share a common pattern and theme when stripped down to the basics. As such, a generalization can be made from the patterns and themes that will enable understanding of data science in lay terms.


The Rule of Three

For that purpose, I shall utilize the “rule of three” to articulate this generalization. Why rule of three? In lay terms, we humans tend to remember things easier in groups of three. Perhaps you have heard of the magical number seven, plus or minus two (7 ± 2), which has been touted as the limit of our brain’s working memory capacity. This research paper by George A. Miller explains the magic number in greater detail. Other research by Steven J. Luck and Edward K. Vogel indicates this number is actually closer to four. In a follow-up research, Edward K. Vogel (same one) and Maro G. Machizawa provide neurological methods that prove the difference in working memory capacity based on individual brains, which may explain why some people can hold more information at a time than others.

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