Is it our future to be agnostic?

As interest in data and data analysis grows, future students interested in the career have to work harder to understand the boundaries and guidelines. It won’t always be as simple as it was for Evan Thorne ‘15, who came to Wesleyan thinking he wanted to study Economics before discovering the QAC department. “I was starting to work with data sets in my math and computer science classes when I heard about big data,” Evan said, explaining that it was soon after he began taking classes with the QAC that he realized he wanted this as a career.

But what is “this”? Data science? Data analysis? Data manipulation? Sometimes it can be hard to define. But Evan did not flounder when I asked him for a definition of his job at CKM Advisors, the company where he was hired right after graduation. He began by explaining to me that an analyst is someone who is able to take in what’s readily available to them and then dissect it to look at more basic stats and trends. Data scientists, however, are able to find things that aren’t available – unstructured data – and take it in raw. “Every data scientist is an analyst in a way,” Evan explained, “but it’s at a much bigger level.” At CKM, Evan is a data scientist, and he is responsible for all of the analytic process: data ingestion, wrangling, manipulation, analysis, and visualization.

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Data Visualization and the Transparency of Truth

Transparency is a hot issue; in politics, in business, and in journalism, people are all itching to know how truthful the truths their being fed really are. However, truth is no longer as easy a thing to gauge as it once was. It turns out, the public can be fed information that is, technically, true, yet at the same time only one version of the truth.

A good example to look at is weather forecasts. Most people think of weather as easy and straight-forward data to access. There are tons of websites that allow search by location (eg/ www.weather.com), and on TV news we can be given an explanation of a weather chart, as seen below:

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Data from Surprising Origins: Looking at the Work of R. Luke Dubois

When R. Luke Dubois sat down with a group of students for lunch on Friday, November 20th, he could have begun by introducing himself: Known as R. Luke Dubois or just Luke Dubois, he is an artist based in New York City with many notable works related to data, some of which have been on display at the Zilkha Gallery since the beginning of the semester. But instead he began by asking us what we were working on.

At first, most of us nervously fidgeted in silence. We hadn’t been expecting the spotlight to be on us. After a couple awkward moments, I offered up an explanation of my final project for my data analysis class. Dubois responded with interest and gave some suggestions. After that, other students slowly began to come forward with their ideas, and he continued to react excitedly. He then powered up the projector behind him and showed us some related work by other artists, such as Fernanda Viegas and Martin Wattenberg.

After this discussion had gone on for a while, I realized that Dubois wasn’t going to talk about himself or his work unless he was prodded to. I turned the spotlight back on him by asking whether he thinks of himself as an artist or data researcher. Dubois jerked his eyes upwards, and when they re-centered on us he had a funny smile on his face. “I’m a musician,” he responded. “I play the cello badly. I played so badly that I switched to a computer.”

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Data and a Polygraph: A Look into Data Journalism

As the uses and values of data become more well-known, more and more unique ways of exploring and presenting data are emerging to the forefront of the Internet. When Wesleyan invited one of these explorers, Matt Daniels, to give a talk on data journalism and media art, I immediately dug into his portfolio. Daniels hosts his projects on a website called Polygraph, and currently has only focused one exploring data related to music. I was immediately transfixed by the name of his site – polygraph isn’t a word commonly connected to data or information – and, due to blanking on the definition, Googled it. I found the following:

pol·y·graph [ˈpälēˌɡraf]

NOUN

  1. A machine designed to detect and record changes in physiological characteristics, such as a person’s pulse and breathing rates, used especially as a lie detector.

With this definition swirling in my head, I came to Daniels’ talk eager to learn what he was all about. Daniels, one of the many young creators who are storming the tech industry, began by clicking to a slide of the visualization that made him “internet famous.” He describes that the goal of this project was to look at the usage of unique words by rappers in their songs. The visualization charts these usages, along with the amount of unique words used by authors ranging from Shakespeare to Melville. The visualization was then followed by some text that further fleshed out what he had discovered. And there you find Daniel’s formula, the foundation of this data journalism he has fallen into: a code narrative + a prose narrative = an interesting and interactive read.

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Don’t Count Data Out: A Conversation with Dana Louie ‘14

When I mention that I’m taking classes in the QAC department, I’m often met with blinking eyes and blank stares. Few people know what it is, or if they do they ask something along the lines of: “Oh, that <em>data</em> thing?” They say data like it’s some sort of disease that is not understandable or conquerable.

Data is far from a disease, but it <em>is</em> capable of spreading everywhere. Data are not static numbers on a screen; data are what is behind your favorite <em>New York Times</em> article. Data is extremely customizable and manipulatable and, most importantly, for everyone.

Despite those who have never heard of the QAC before, the department has been running at Wesleyan for years, and many now graduated students stumbled their way into their first QAC class only to leave with a career in data analysis. One of those students is Dana Louie ’14, who I had the pleasure of chatting to when she came to campus to give an info session for Analysis Group, the firm she works for. Dana’s discovery of the QAC happened through the QAC summer program, where she took classes in morning and then worked on research with professor in the afternoon. The following year, she was selected to be QAC tutor, and her fate in the department was sealed.

“People can succeed [in QAC classes] even with no background,” Dana said confidently, referring to the fear that keeps a lot of students from getting off the bench and entering the world of the QAC. When talking with my friends about by own experiences in the QAC, they often say something along the lines of “Wow, that sounds really cool. I wish I could do that.” I always respond with “You can,” just as Dana as saying. There are many intro classes in the QAC (QAC201, QAC211), and many chances to start to learn one of the programming languages.

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Data Analysis Beyond the QAC: A Conversation with Zach ’15 and Sanvir ‘15

Do you ever wonder how the fascinating theories you’re learning at Wesleyan might help you get a job after graduation? It’s so easy to be romanced by Wesleyan’s niche majors and broad-based interdisciplinary options. And that’s how it should be – you should definitely take advantage of that eye-opening class on Race & Medicine and those lectures on the origins of medieval eastern-European dance. But as Aunt Mildred and Uncle Al like to remind you at family reunions, knowing a lot about the political history of the Sung Dynasty isn’t enough to get you a job.

That’s where QAC comes in. As the QAC web site explains, QAC “coordinates support for quantitative analysis across the curriculum, and provides an institutional framework for collaboration across departments and disciplines.” Putting it another way, data analysis skills combine beautifully with the critical thinking skills and broad-based theories you’re learning in your other classes, and open the door to research and employment opportunities across a wide spectrum of fields. “Irrespective of your major, you can do data analysis work to help you with whatever you’re doing,” Sanvir ’15 pointed out. “If you really look into it, you can do something with data to make your work more interesting. An example would be English word mapping.”

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