First Impression
When I first read about the data science course offered by Flatiron school, I immediately thought about the research process that takes place in universities: devising an experiment, collecting data, analyzing the data, organizing it, drawing a conclusion from it, and presenting it. I had experience in the process, so I knew I would enjoy it. Although, I will admit that I thought it only applied in this field alone.
Something More
However, after starting the Flatiron Data Science Bootcamp Prep, I started to realize data science very much applied outside of academia. In fact, my first example came when I read about what type of structure a song might need to have in order to be classified as a hit record. Here is the article: https://pudding.cool/2017/05/song-repetition/. Basically, this article talks about how most hit songs share a percentage of size reducibility; that is, a song’s repetitiveness in words and lyrical structure. From analyzing 15,000 songs from the Billboard Hot 100 between 1958 – 2017, a data scientist could advise an artist, song composer, or studio about what range of size reducibility should be achieved for the next big hit song. My next example outside of academia came when I talked to my aunt who described what she did at Alcon Inc. in Fort Worth, TX. In short, she analyzed how customer reception, product quantity, manufacturing demand, and net profit would be affected by increasing or decreasing the cost of Alcon products. She told me she loved how she could tell her boss what would happen next–like a fortune teller of sorts. This real-life example really showed me the power of data science and how businesses rely on what data has to say about the future.
Possibilities
Some time has passed since I last discussed with my aunt, and I ran into a data science related show called The Human Face of Big Data from Curiosity Stream. This episode introduced me to so many different situations where data scientists gave new insights into previously speculated theories or established new theories all in a visually impactful way for anybody to easily understand. It is interesting what data had to say to each of those scientists. My hope is that I can be named among these data scientists one day and uncover what data has to say to me.