Note that I originally wrote a version this post for my analytics students on our class WordPress site.
I’ve taught CIS450: Enterprise Analytics Capstone more than a few times. Still, this is most likely the first time that you’re taking it. What’s more, I’d bet that you haven’t undertaken a project akin to the individual research that you’ll do this semester.
This begs the question: What would I do if I were a 21-year-old student?
You already know that I’m a huge fan of the English neo-prog band Marillion. Let’s say that I already had my post-graduation job lined up. That is, I wasn’t using the project to show recruiters my knowledge of a specific problem, industry, or the like.
I would scrape tour data from the Marillion site. I don’t know if import.io would work but, if not, then I’d use a Python library such as Beautiful Soup. I would be prepared to investigate some of the other tools that my Marillion-obsessed professor has mentioned.
Once I obtained the data, I would attempt to calculate things such as:
- the total number of shows that the band has played by year, month, etc. (and related trends)
- the most and least frequently played song (and related trends)
For interviews, I’d try to talk to one of band’s members or even its manager. (As it turns out, I’ve interviewed almost everyone at least once for HuffPo.)
With my data, I’d attempt to answer questions such as:
- In what country/venue has the band played the most gigs?
- Where does it tend to play longer/shorter sets?
- Which prior staples has the band retired? Which have returned after their hiatuses?
- Does the band play more frequently upon releasing a new studio album?
- Has the band slowed down as its members have aged?
- Which band/artist most frequently opened for the band?
What’s more, I would create interactive data visualizations with Tableau. I would promptly publish that dataviz on Tableau Public so recruiters could find it. Here’s a Sankey diagram showing the band’s albums by decade:
I’d demonstrate my findings in a way that would let my professor play around with the data and make his/her own discoveries.
Enjoy some “Sugar Mice.”
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